Actual source code: itfunc.c
petsc-3.15.0 2021-03-30
1: /*
2: Interface KSP routines that the user calls.
3: */
5: #include <petsc/private/kspimpl.h>
6: #include <petsc/private/matimpl.h>
7: #include <petscdm.h>
9: PETSC_STATIC_INLINE PetscErrorCode ObjectView(PetscObject obj, PetscViewer viewer, PetscViewerFormat format)
10: {
13: PetscViewerPushFormat(viewer, format);
14: PetscObjectView(obj, viewer);
15: PetscViewerPopFormat(viewer);
16: return(0);
17: }
19: /*@
20: KSPComputeExtremeSingularValues - Computes the extreme singular values
21: for the preconditioned operator. Called after or during KSPSolve().
23: Not Collective
25: Input Parameter:
26: . ksp - iterative context obtained from KSPCreate()
28: Output Parameters:
29: . emin, emax - extreme singular values
31: Options Database Keys:
32: . -ksp_view_singularvalues - compute extreme singular values and print when KSPSolve completes.
34: Notes:
35: One must call KSPSetComputeSingularValues() before calling KSPSetUp()
36: (or use the option -ksp_view_eigenvalues) in order for this routine to work correctly.
38: Many users may just want to use the monitoring routine
39: KSPMonitorSingularValue() (which can be set with option -ksp_monitor_singular_value)
40: to print the extreme singular values at each iteration of the linear solve.
42: Estimates of the smallest singular value may be very inaccurate, especially if the Krylov method has not converged.
43: The largest singular value is usually accurate to within a few percent if the method has converged, but is still not
44: intended for eigenanalysis.
46: Disable restarts if using KSPGMRES, otherwise this estimate will only be using those iterations after the last
47: restart. See KSPGMRESSetRestart() for more details.
49: Level: advanced
51: .seealso: KSPSetComputeSingularValues(), KSPMonitorSingularValue(), KSPComputeEigenvalues(), KSP
52: @*/
53: PetscErrorCode KSPComputeExtremeSingularValues(KSP ksp,PetscReal *emax,PetscReal *emin)
54: {
61: if (!ksp->calc_sings) SETERRQ(PetscObjectComm((PetscObject)ksp),4,"Singular values not requested before KSPSetUp()");
63: if (ksp->ops->computeextremesingularvalues) {
64: (*ksp->ops->computeextremesingularvalues)(ksp,emax,emin);
65: } else {
66: *emin = -1.0;
67: *emax = -1.0;
68: }
69: return(0);
70: }
72: /*@
73: KSPComputeEigenvalues - Computes the extreme eigenvalues for the
74: preconditioned operator. Called after or during KSPSolve().
76: Not Collective
78: Input Parameters:
79: + ksp - iterative context obtained from KSPCreate()
80: - n - size of arrays r and c. The number of eigenvalues computed (neig) will, in
81: general, be less than this.
83: Output Parameters:
84: + r - real part of computed eigenvalues, provided by user with a dimension of at least n
85: . c - complex part of computed eigenvalues, provided by user with a dimension of at least n
86: - neig - actual number of eigenvalues computed (will be less than or equal to n)
88: Options Database Keys:
89: . -ksp_view_eigenvalues - Prints eigenvalues to stdout
91: Notes:
92: The number of eigenvalues estimated depends on the size of the Krylov space
93: generated during the KSPSolve() ; for example, with
94: CG it corresponds to the number of CG iterations, for GMRES it is the number
95: of GMRES iterations SINCE the last restart. Any extra space in r[] and c[]
96: will be ignored.
98: KSPComputeEigenvalues() does not usually provide accurate estimates; it is
99: intended only for assistance in understanding the convergence of iterative
100: methods, not for eigenanalysis. For accurate computation of eigenvalues we recommend using
101: the excellent package SLEPc.
103: One must call KSPSetComputeEigenvalues() before calling KSPSetUp()
104: in order for this routine to work correctly.
106: Many users may just want to use the monitoring routine
107: KSPMonitorSingularValue() (which can be set with option -ksp_monitor_singular_value)
108: to print the singular values at each iteration of the linear solve.
110: Level: advanced
112: .seealso: KSPSetComputeSingularValues(), KSPMonitorSingularValue(), KSPComputeExtremeSingularValues(), KSP
113: @*/
114: PetscErrorCode KSPComputeEigenvalues(KSP ksp,PetscInt n,PetscReal r[],PetscReal c[],PetscInt *neig)
115: {
122: if (n<0) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Requested < 0 Eigenvalues");
124: if (!ksp->calc_sings) SETERRQ(PetscObjectComm((PetscObject)ksp),4,"Eigenvalues not requested before KSPSetUp()");
126: if (n && ksp->ops->computeeigenvalues) {
127: (*ksp->ops->computeeigenvalues)(ksp,n,r,c,neig);
128: } else {
129: *neig = 0;
130: }
131: return(0);
132: }
134: /*@
135: KSPComputeRitz - Computes the Ritz or harmonic Ritz pairs associated to the
136: smallest or largest in modulus, for the preconditioned operator.
137: Called after KSPSolve().
139: Not Collective
141: Input Parameters:
142: + ksp - iterative context obtained from KSPCreate()
143: . ritz - PETSC_TRUE or PETSC_FALSE for ritz pairs or harmonic Ritz pairs, respectively
144: . small - PETSC_TRUE or PETSC_FALSE for smallest or largest (harmonic) Ritz values, respectively
145: - nrit - number of (harmonic) Ritz pairs to compute
147: Output Parameters:
148: + nrit - actual number of computed (harmonic) Ritz pairs
149: . S - multidimensional vector with Ritz vectors
150: . tetar - real part of the Ritz values
151: - tetai - imaginary part of the Ritz values
153: Notes:
154: -For GMRES, the (harmonic) Ritz pairs are computed from the Hessenberg matrix obtained during
155: the last complete cycle, or obtained at the end of the solution if the method is stopped before
156: a restart. Then, the number of actual (harmonic) Ritz pairs computed is less or equal to the restart
157: parameter for GMRES if a complete cycle has been performed or less or equal to the number of GMRES
158: iterations.
159: -Moreover, for real matrices, the (harmonic) Ritz pairs are possibly complex-valued. In such a case,
160: the routine selects the complex (harmonic) Ritz value and its conjugate, and two successive columns of S
161: are equal to the real and the imaginary parts of the associated vectors.
162: -the (harmonic) Ritz pairs are given in order of increasing (harmonic) Ritz values in modulus
163: -this is currently not implemented when PETSc is built with complex numbers
165: One must call KSPSetComputeRitz() before calling KSPSetUp()
166: in order for this routine to work correctly.
168: Level: advanced
170: .seealso: KSPSetComputeRitz(), KSP
171: @*/
172: PetscErrorCode KSPComputeRitz(KSP ksp,PetscBool ritz,PetscBool small,PetscInt *nrit,Vec S[],PetscReal tetar[],PetscReal tetai[])
173: {
178: if (!ksp->calc_ritz) SETERRQ(PetscObjectComm((PetscObject)ksp),4,"Ritz pairs not requested before KSPSetUp()");
179: if (ksp->ops->computeritz) {(*ksp->ops->computeritz)(ksp,ritz,small,nrit,S,tetar,tetai);}
180: return(0);
181: }
182: /*@
183: KSPSetUpOnBlocks - Sets up the preconditioner for each block in
184: the block Jacobi, block Gauss-Seidel, and overlapping Schwarz
185: methods.
187: Collective on ksp
189: Input Parameter:
190: . ksp - the KSP context
192: Notes:
193: KSPSetUpOnBlocks() is a routine that the user can optinally call for
194: more precise profiling (via -log_view) of the setup phase for these
195: block preconditioners. If the user does not call KSPSetUpOnBlocks(),
196: it will automatically be called from within KSPSolve().
198: Calling KSPSetUpOnBlocks() is the same as calling PCSetUpOnBlocks()
199: on the PC context within the KSP context.
201: Level: advanced
203: .seealso: PCSetUpOnBlocks(), KSPSetUp(), PCSetUp(), KSP
204: @*/
205: PetscErrorCode KSPSetUpOnBlocks(KSP ksp)
206: {
207: PC pc;
209: PCFailedReason pcreason;
213: KSPGetPC(ksp,&pc);
214: PCSetUpOnBlocks(pc);
215: PCGetFailedReasonRank(pc,&pcreason);
216: /* TODO: this code was wrong and is still wrong, there is no way to propogate the failure to all processes; their is no code to handle a ksp->reason on only some ranks */
217: if (pcreason) {
218: ksp->reason = KSP_DIVERGED_PC_FAILED;
219: }
220: return(0);
221: }
223: /*@
224: KSPSetReusePreconditioner - reuse the current preconditioner, do not construct a new one even if the operator changes
226: Collective on ksp
228: Input Parameters:
229: + ksp - iterative context obtained from KSPCreate()
230: - flag - PETSC_TRUE to reuse the current preconditioner
232: Level: intermediate
234: .seealso: KSPCreate(), KSPSolve(), KSPDestroy(), PCSetReusePreconditioner(), KSP
235: @*/
236: PetscErrorCode KSPSetReusePreconditioner(KSP ksp,PetscBool flag)
237: {
238: PC pc;
243: KSPGetPC(ksp,&pc);
244: PCSetReusePreconditioner(pc,flag);
245: return(0);
246: }
248: /*@
249: KSPGetReusePreconditioner - Determines if the KSP reuses the current preconditioner even if the operator in the preconditioner has changed.
251: Collective on ksp
253: Input Parameters:
254: . ksp - iterative context obtained from KSPCreate()
256: Output Parameters:
257: . flag - the boolean flag
259: Level: intermediate
261: .seealso: KSPCreate(), KSPSolve(), KSPDestroy(), KSPSetReusePreconditioner(), KSP
262: @*/
263: PetscErrorCode KSPGetReusePreconditioner(KSP ksp,PetscBool *flag)
264: {
270: *flag = PETSC_FALSE;
271: if (ksp->pc) {
272: PCGetReusePreconditioner(ksp->pc,flag);
273: }
274: return(0);
275: }
277: /*@
278: KSPSetSkipPCSetFromOptions - prevents KSPSetFromOptions() from call PCSetFromOptions(). This is used if the same PC is shared by more than one KSP so its options are not resetable for each KSP
280: Collective on ksp
282: Input Parameters:
283: + ksp - iterative context obtained from KSPCreate()
284: - flag - PETSC_TRUE to skip calling the PCSetFromOptions()
286: Level: intermediate
288: .seealso: KSPCreate(), KSPSolve(), KSPDestroy(), PCSetReusePreconditioner(), KSP
289: @*/
290: PetscErrorCode KSPSetSkipPCSetFromOptions(KSP ksp,PetscBool flag)
291: {
294: ksp->skippcsetfromoptions = flag;
295: return(0);
296: }
298: /*@
299: KSPSetUp - Sets up the internal data structures for the
300: later use of an iterative solver.
302: Collective on ksp
304: Input Parameter:
305: . ksp - iterative context obtained from KSPCreate()
307: Level: developer
309: .seealso: KSPCreate(), KSPSolve(), KSPDestroy(), KSP
310: @*/
311: PetscErrorCode KSPSetUp(KSP ksp)
312: {
314: Mat A,B;
315: Mat mat,pmat;
316: MatNullSpace nullsp;
317: PCFailedReason pcreason;
322: /* reset the convergence flag from the previous solves */
323: ksp->reason = KSP_CONVERGED_ITERATING;
325: if (!((PetscObject)ksp)->type_name) {
326: KSPSetType(ksp,KSPGMRES);
327: }
328: KSPSetUpNorms_Private(ksp,PETSC_TRUE,&ksp->normtype,&ksp->pc_side);
330: if (ksp->dmActive && !ksp->setupstage) {
331: /* first time in so build matrix and vector data structures using DM */
332: if (!ksp->vec_rhs) {DMCreateGlobalVector(ksp->dm,&ksp->vec_rhs);}
333: if (!ksp->vec_sol) {DMCreateGlobalVector(ksp->dm,&ksp->vec_sol);}
334: DMCreateMatrix(ksp->dm,&A);
335: KSPSetOperators(ksp,A,A);
336: PetscObjectDereference((PetscObject)A);
337: }
339: if (ksp->dmActive) {
340: DMKSP kdm;
341: DMGetDMKSP(ksp->dm,&kdm);
343: if (kdm->ops->computeinitialguess && ksp->setupstage != KSP_SETUP_NEWRHS) {
344: /* only computes initial guess the first time through */
345: (*kdm->ops->computeinitialguess)(ksp,ksp->vec_sol,kdm->initialguessctx);
346: KSPSetInitialGuessNonzero(ksp,PETSC_TRUE);
347: }
348: if (kdm->ops->computerhs) {
349: (*kdm->ops->computerhs)(ksp,ksp->vec_rhs,kdm->rhsctx);
350: }
352: if (ksp->setupstage != KSP_SETUP_NEWRHS) {
353: if (kdm->ops->computeoperators) {
354: KSPGetOperators(ksp,&A,&B);
355: (*kdm->ops->computeoperators)(ksp,A,B,kdm->operatorsctx);
356: } else SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_WRONGSTATE,"You called KSPSetDM() but did not use DMKSPSetComputeOperators() or KSPSetDMActive(ksp,PETSC_FALSE);");
357: }
358: }
360: if (ksp->setupstage == KSP_SETUP_NEWRHS) return(0);
361: PetscLogEventBegin(KSP_SetUp,ksp,ksp->vec_rhs,ksp->vec_sol,0);
363: switch (ksp->setupstage) {
364: case KSP_SETUP_NEW:
365: (*ksp->ops->setup)(ksp);
366: break;
367: case KSP_SETUP_NEWMATRIX: { /* This should be replaced with a more general mechanism */
368: if (ksp->setupnewmatrix) {
369: (*ksp->ops->setup)(ksp);
370: }
371: } break;
372: default: break;
373: }
375: if (!ksp->pc) {KSPGetPC(ksp,&ksp->pc);}
376: PCGetOperators(ksp->pc,&mat,&pmat);
377: /* scale the matrix if requested */
378: if (ksp->dscale) {
379: PetscScalar *xx;
380: PetscInt i,n;
381: PetscBool zeroflag = PETSC_FALSE;
382: if (!ksp->pc) {KSPGetPC(ksp,&ksp->pc);}
383: if (!ksp->diagonal) { /* allocate vector to hold diagonal */
384: MatCreateVecs(pmat,&ksp->diagonal,NULL);
385: }
386: MatGetDiagonal(pmat,ksp->diagonal);
387: VecGetLocalSize(ksp->diagonal,&n);
388: VecGetArray(ksp->diagonal,&xx);
389: for (i=0; i<n; i++) {
390: if (xx[i] != 0.0) xx[i] = 1.0/PetscSqrtReal(PetscAbsScalar(xx[i]));
391: else {
392: xx[i] = 1.0;
393: zeroflag = PETSC_TRUE;
394: }
395: }
396: VecRestoreArray(ksp->diagonal,&xx);
397: if (zeroflag) {
398: PetscInfo(ksp,"Zero detected in diagonal of matrix, using 1 at those locations\n");
399: }
400: MatDiagonalScale(pmat,ksp->diagonal,ksp->diagonal);
401: if (mat != pmat) {MatDiagonalScale(mat,ksp->diagonal,ksp->diagonal);}
402: ksp->dscalefix2 = PETSC_FALSE;
403: }
404: PetscLogEventEnd(KSP_SetUp,ksp,ksp->vec_rhs,ksp->vec_sol,0);
405: PCSetErrorIfFailure(ksp->pc,ksp->errorifnotconverged);
406: PCSetUp(ksp->pc);
407: PCGetFailedReasonRank(ksp->pc,&pcreason);
408: /* TODO: this code was wrong and is still wrong, there is no way to propogate the failure to all processes; their is no code to handle a ksp->reason on only some ranks */
409: if (pcreason) {
410: ksp->reason = KSP_DIVERGED_PC_FAILED;
411: }
413: MatGetNullSpace(mat,&nullsp);
414: if (nullsp) {
415: PetscBool test = PETSC_FALSE;
416: PetscOptionsGetBool(((PetscObject)ksp)->options,((PetscObject)ksp)->prefix,"-ksp_test_null_space",&test,NULL);
417: if (test) {
418: MatNullSpaceTest(nullsp,mat,NULL);
419: }
420: }
421: ksp->setupstage = KSP_SETUP_NEWRHS;
422: return(0);
423: }
425: /*@C
426: KSPConvergedReasonView - Displays the reason a KSP solve converged or diverged to a viewer
428: Collective on ksp
430: Parameter:
431: + ksp - iterative context obtained from KSPCreate()
432: - viewer - the viewer to display the reason
434: Options Database Keys:
435: + -ksp_converged_reason - print reason for converged or diverged, also prints number of iterations
436: - -ksp_converged_reason ::failed - only print reason and number of iterations when diverged
438: Notes:
439: To change the format of the output call PetscViewerPushFormat(viewer,format) before this call. Use PETSC_VIEWER_DEFAULT for the default,
440: use PETSC_VIEWER_FAILED to only display a reason if it fails.
442: Level: beginner
444: .seealso: KSPCreate(), KSPSetUp(), KSPDestroy(), KSPSetTolerances(), KSPConvergedDefault(),
445: KSPSolveTranspose(), KSPGetIterationNumber(), KSP, KSPGetConvergedReason(), PetscViewerPushFormat(), PetscViewerPopFormat()
446: @*/
447: PetscErrorCode KSPConvergedReasonView(KSP ksp, PetscViewer viewer)
448: {
449: PetscErrorCode ierr;
450: PetscBool isAscii;
451: PetscViewerFormat format;
454: if (!viewer) viewer = PETSC_VIEWER_STDOUT_(PetscObjectComm((PetscObject)ksp));
455: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isAscii);
456: if (isAscii) {
457: PetscViewerGetFormat(viewer, &format);
458: PetscViewerASCIIAddTab(viewer,((PetscObject)ksp)->tablevel);
459: if (ksp->reason > 0 && format != PETSC_VIEWER_FAILED) {
460: if (((PetscObject) ksp)->prefix) {
461: PetscViewerASCIIPrintf(viewer,"Linear %s solve converged due to %s iterations %D\n",((PetscObject) ksp)->prefix,KSPConvergedReasons[ksp->reason],ksp->its);
462: } else {
463: PetscViewerASCIIPrintf(viewer,"Linear solve converged due to %s iterations %D\n",KSPConvergedReasons[ksp->reason],ksp->its);
464: }
465: } else if (ksp->reason <= 0) {
466: if (((PetscObject) ksp)->prefix) {
467: PetscViewerASCIIPrintf(viewer,"Linear %s solve did not converge due to %s iterations %D\n",((PetscObject) ksp)->prefix,KSPConvergedReasons[ksp->reason],ksp->its);
468: } else {
469: PetscViewerASCIIPrintf(viewer,"Linear solve did not converge due to %s iterations %D\n",KSPConvergedReasons[ksp->reason],ksp->its);
470: }
471: if (ksp->reason == KSP_DIVERGED_PC_FAILED) {
472: PCFailedReason reason;
473: PCGetFailedReason(ksp->pc,&reason);
474: PetscViewerASCIIPrintf(viewer," PC failed due to %s \n",PCFailedReasons[reason]);
475: }
476: }
477: PetscViewerASCIISubtractTab(viewer,((PetscObject)ksp)->tablevel);
478: }
479: return(0);
480: }
482: /*@C
483: KSPConvergedReasonViewSet - Sets an ADDITIONAL function that is to be used at the
484: end of the linear solver to display the convergence reason of the linear solver.
486: Logically Collective on KSP
488: Input Parameters:
489: + ksp - the KSP context
490: . f - the ksp converged reason view function
491: . vctx - [optional] user-defined context for private data for the
492: ksp converged reason view routine (use NULL if no context is desired)
493: - reasonviewdestroy - [optional] routine that frees reasonview context
494: (may be NULL)
496: Options Database Keys:
497: + -ksp_converged_reason - sets a default KSPConvergedReasonView()
498: - -ksp_converged_reason_view_cancel - cancels all converged reason viewers that have
499: been hardwired into a code by
500: calls to KSPConvergedReasonViewSet(), but
501: does not cancel those set via
502: the options database.
504: Notes:
505: Several different converged reason view routines may be set by calling
506: KSPConvergedReasonViewSet() multiple times; all will be called in the
507: order in which they were set.
509: Level: intermediate
511: .seealso: KSPConvergedReasonView(), KSPConvergedReasonViewCancel()
512: @*/
513: PetscErrorCode KSPConvergedReasonViewSet(KSP ksp,PetscErrorCode (*f)(KSP,void*),void *vctx,PetscErrorCode (*reasonviewdestroy)(void**))
514: {
515: PetscInt i;
517: PetscBool identical;
521: for (i=0; i<ksp->numberreasonviews;i++) {
522: PetscMonitorCompare((PetscErrorCode (*)(void))f,vctx,reasonviewdestroy,(PetscErrorCode (*)(void))ksp->reasonview[i],ksp->reasonviewcontext[i],ksp->reasonviewdestroy[i],&identical);
523: if (identical) return(0);
524: }
525: if (ksp->numberreasonviews >= MAXKSPREASONVIEWS) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Too many KSP reasonview set");
526: ksp->reasonview[ksp->numberreasonviews] = f;
527: ksp->reasonviewdestroy[ksp->numberreasonviews] = reasonviewdestroy;
528: ksp->reasonviewcontext[ksp->numberreasonviews++] = (void*)vctx;
529: return(0);
530: }
532: /*@
533: KSPConvergedReasonViewCancel - Clears all the reasonview functions for a KSP object.
535: Collective on KSP
537: Input Parameter:
538: . ksp - iterative context obtained from KSPCreate()
540: Level: intermediate
542: .seealso: KSPCreate(), KSPDestroy(), KSPReset()
543: @*/
544: PetscErrorCode KSPConvergedReasonViewCancel(KSP ksp)
545: {
547: PetscInt i;
551: for (i=0; i<ksp->numberreasonviews; i++) {
552: if (ksp->reasonviewdestroy[i]) {
553: (*ksp->reasonviewdestroy[i])(&ksp->reasonviewcontext[i]);
554: }
555: }
556: ksp->numberreasonviews = 0;
557: return(0);
558: }
560: /*@
561: KSPConvergedReasonViewFromOptions - Processes command line options to determine if/how a KSPReason is to be viewed.
563: Collective on ksp
565: Input Parameters:
566: . ksp - the KSP object
568: Level: intermediate
570: .seealso: KSPConvergedReasonView()
571: @*/
572: PetscErrorCode KSPConvergedReasonViewFromOptions(KSP ksp)
573: {
574: PetscViewer viewer;
575: PetscBool flg;
576: PetscViewerFormat format;
577: PetscErrorCode ierr;
578: PetscInt i;
582: /* Call all user-provided reason review routines */
583: for (i=0; i<ksp->numberreasonviews; i++) {
584: (*ksp->reasonview[i])(ksp,ksp->reasonviewcontext[i]);
585: }
587: /* Call the default PETSc routine */
588: PetscOptionsGetViewer(PetscObjectComm((PetscObject)ksp),((PetscObject)ksp)->options,((PetscObject)ksp)->prefix,"-ksp_converged_reason",&viewer,&format,&flg);
589: if (flg) {
590: PetscViewerPushFormat(viewer,format);
591: KSPConvergedReasonView(ksp, viewer);
592: PetscViewerPopFormat(viewer);
593: PetscViewerDestroy(&viewer);
594: }
595: return(0);
596: }
598: /*@C
599: KSPConvergedRateView - Displays the reason a KSP solve converged or diverged to a viewer
601: Collective on ksp
603: Input Parameters:
604: + ksp - iterative context obtained from KSPCreate()
605: - viewer - the viewer to display the reason
607: Options Database Keys:
608: . -ksp_converged_rate - print reason for convergence or divergence and the convergence rate (or 0.0 for divergence)
610: Notes:
611: To change the format of the output, call PetscViewerPushFormat(viewer,format) before this call.
613: Suppose that the residual is reduced linearly, $r_k = c^k r_0$, which means $log r_k = log r_0 + k log c$. After linear regression,
614: the slope is $\log c$. The coefficient of determination is given by $1 - \frac{\sum_i (y_i - f(x_i))^2}{\sum_i (y_i - \bar y)}$,
615: see also https://en.wikipedia.org/wiki/Coefficient_of_determination
617: Level: intermediate
619: .seealso: KSPConvergedReasonView(), KSPGetConvergedRate(), KSPSetTolerances(), KSPConvergedDefault()
620: @*/
621: PetscErrorCode KSPConvergedRateView(KSP ksp, PetscViewer viewer)
622: {
623: PetscViewerFormat format;
624: PetscBool isAscii;
625: PetscReal rrate, rRsq, erate, eRsq;
626: PetscInt its;
627: const char *prefix, *reason = KSPConvergedReasons[ksp->reason];
628: PetscErrorCode ierr;
631: KSPGetOptionsPrefix(ksp, &prefix);
632: KSPGetIterationNumber(ksp, &its);
633: KSPComputeConvergenceRate(ksp, &rrate, &rRsq, &erate, &eRsq);
634: if (!viewer) viewer = PETSC_VIEWER_STDOUT_(PetscObjectComm((PetscObject)ksp));
635: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isAscii);
636: if (isAscii) {
637: PetscViewerGetFormat(viewer, &format);
638: PetscViewerASCIIAddTab(viewer,((PetscObject)ksp)->tablevel);
639: if (ksp->reason > 0) {
640: if (prefix) {PetscViewerASCIIPrintf(viewer, "Linear %s solve converged due to %s iterations %D", prefix, reason, its);}
641: else {PetscViewerASCIIPrintf(viewer, "Linear solve converged due to %s iterations %D", reason, its);}
642: PetscViewerASCIIUseTabs(viewer, PETSC_FALSE);
643: if (rRsq >= 0.0) {PetscViewerASCIIPrintf(viewer, " res rate %g R^2 %g", rrate, rRsq);}
644: if (eRsq >= 0.0) {PetscViewerASCIIPrintf(viewer, " error rate %g R^2 %g", erate, eRsq);}
645: PetscViewerASCIIPrintf(viewer, "\n");
646: PetscViewerASCIIUseTabs(viewer, PETSC_TRUE);
647: } else if (ksp->reason <= 0) {
648: if (prefix) {PetscViewerASCIIPrintf(viewer, "Linear %s solve did not converge due to %s iterations %D", prefix, reason, its);}
649: else {PetscViewerASCIIPrintf(viewer, "Linear solve did not converge due to %s iterations %D", reason, its);}
650: PetscViewerASCIIUseTabs(viewer, PETSC_FALSE);
651: if (rRsq >= 0.0) {PetscViewerASCIIPrintf(viewer, " res rate %g R^2 %g", rrate, rRsq);}
652: if (eRsq >= 0.0) {PetscViewerASCIIPrintf(viewer, " error rate %g R^2 %g", erate, eRsq);}
653: PetscViewerASCIIPrintf(viewer, "\n");
654: PetscViewerASCIIUseTabs(viewer, PETSC_TRUE);
655: if (ksp->reason == KSP_DIVERGED_PC_FAILED) {
656: PCFailedReason reason;
657: PCGetFailedReason(ksp->pc,&reason);
658: PetscViewerASCIIPrintf(viewer," PC failed due to %s \n",PCFailedReasons[reason]);
659: }
660: }
661: PetscViewerASCIISubtractTab(viewer,((PetscObject)ksp)->tablevel);
662: }
663: return(0);
664: }
666: #include <petscdraw.h>
668: static PetscErrorCode KSPViewEigenvalues_Internal(KSP ksp, PetscBool isExplicit, PetscViewer viewer, PetscViewerFormat format)
669: {
670: PetscReal *r, *c;
671: PetscInt n, i, neig;
672: PetscBool isascii, isdraw;
673: PetscMPIInt rank;
677: MPI_Comm_rank(PetscObjectComm((PetscObject) ksp), &rank);
678: PetscObjectTypeCompare((PetscObject) viewer, PETSCVIEWERASCII, &isascii);
679: PetscObjectTypeCompare((PetscObject) viewer, PETSCVIEWERDRAW, &isdraw);
680: if (isExplicit) {
681: VecGetSize(ksp->vec_sol,&n);
682: PetscMalloc2(n, &r, n, &c);
683: KSPComputeEigenvaluesExplicitly(ksp, n, r, c);
684: neig = n;
685: } else {
686: PetscInt nits;
688: KSPGetIterationNumber(ksp, &nits);
689: n = nits+2;
690: if (!nits) {PetscViewerASCIIPrintf(viewer, "Zero iterations in solver, cannot approximate any eigenvalues\n");return(0);}
691: PetscMalloc2(n, &r, n, &c);
692: KSPComputeEigenvalues(ksp, n, r, c, &neig);
693: }
694: if (isascii) {
695: PetscViewerASCIIPrintf(viewer, "%s computed eigenvalues\n", isExplicit ? "Explicitly" : "Iteratively");
696: for (i = 0; i < neig; ++i) {
697: if (c[i] >= 0.0) {PetscViewerASCIIPrintf(viewer, "%g + %gi\n", (double) r[i], (double) c[i]);}
698: else {PetscViewerASCIIPrintf(viewer, "%g - %gi\n", (double) r[i], -(double) c[i]);}
699: }
700: } else if (isdraw && !rank) {
701: PetscDraw draw;
702: PetscDrawSP drawsp;
704: if (format == PETSC_VIEWER_DRAW_CONTOUR) {
705: KSPPlotEigenContours_Private(ksp,neig,r,c);
706: } else {
707: if (!ksp->eigviewer) {PetscViewerDrawOpen(PETSC_COMM_SELF,NULL,isExplicit ? "Explicitly Computed Eigenvalues" : "Iteratively Computed Eigenvalues",PETSC_DECIDE,PETSC_DECIDE,400,400,&ksp->eigviewer);}
708: PetscViewerDrawGetDraw(ksp->eigviewer,0,&draw);
709: PetscDrawSPCreate(draw,1,&drawsp);
710: PetscDrawSPReset(drawsp);
711: for (i = 0; i < neig; ++i) {PetscDrawSPAddPoint(drawsp,r+i,c+i);}
712: PetscDrawSPDraw(drawsp,PETSC_TRUE);
713: PetscDrawSPSave(drawsp);
714: PetscDrawSPDestroy(&drawsp);
715: }
716: }
717: PetscFree2(r, c);
718: return(0);
719: }
721: static PetscErrorCode KSPViewSingularvalues_Internal(KSP ksp, PetscViewer viewer, PetscViewerFormat format)
722: {
723: PetscReal smax, smin;
724: PetscInt nits;
725: PetscBool isascii;
729: PetscObjectTypeCompare((PetscObject) viewer, PETSCVIEWERASCII, &isascii);
730: KSPGetIterationNumber(ksp, &nits);
731: if (!nits) {PetscViewerASCIIPrintf(viewer, "Zero iterations in solver, cannot approximate any singular values\n");return(0);}
732: KSPComputeExtremeSingularValues(ksp, &smax, &smin);
733: if (isascii) {PetscViewerASCIIPrintf(viewer, "Iteratively computed extreme singular values: max %g min %g max/min %g\n",(double)smax,(double)smin,(double)(smax/smin));}
734: return(0);
735: }
737: static PetscErrorCode KSPViewFinalResidual_Internal(KSP ksp, PetscViewer viewer, PetscViewerFormat format)
738: {
739: PetscBool isascii;
743: PetscObjectTypeCompare((PetscObject) viewer, PETSCVIEWERASCII, &isascii);
744: if (ksp->dscale && !ksp->dscalefix) SETERRQ(PetscObjectComm((PetscObject) ksp), PETSC_ERR_ARG_WRONGSTATE, "Cannot compute final scale with -ksp_diagonal_scale except also with -ksp_diagonal_scale_fix");
745: if (isascii) {
746: Mat A;
747: Vec t;
748: PetscReal norm;
750: PCGetOperators(ksp->pc, &A, NULL);
751: VecDuplicate(ksp->vec_rhs, &t);
752: KSP_MatMult(ksp, A, ksp->vec_sol, t);
753: VecAYPX(t, -1.0, ksp->vec_rhs);
754: VecNorm(t, NORM_2, &norm);
755: VecDestroy(&t);
756: PetscViewerASCIIPrintf(viewer, "KSP final norm of residual %g\n", (double) norm);
757: }
758: return(0);
759: }
761: static PetscErrorCode KSPMonitorPauseFinal_Internal(KSP ksp)
762: {
763: PetscInt i;
767: if (!ksp->pauseFinal) return(0);
768: for (i = 0; i < ksp->numbermonitors; ++i) {
769: PetscViewerAndFormat *vf = (PetscViewerAndFormat *) ksp->monitorcontext[i];
770: PetscDraw draw;
771: PetscReal lpause;
773: if (!vf) continue;
774: if (vf->lg) {
776: if (((PetscObject) vf->lg)->classid != PETSC_DRAWLG_CLASSID) continue;
777: PetscDrawLGGetDraw(vf->lg, &draw);
778: PetscDrawGetPause(draw, &lpause);
779: PetscDrawSetPause(draw, -1.0);
780: PetscDrawPause(draw);
781: PetscDrawSetPause(draw, lpause);
782: } else {
783: PetscBool isdraw;
786: if (((PetscObject) vf->viewer)->classid != PETSC_VIEWER_CLASSID) continue;
787: PetscObjectTypeCompare((PetscObject) vf->viewer, PETSCVIEWERDRAW, &isdraw);
788: if (!isdraw) continue;
789: PetscViewerDrawGetDraw(vf->viewer, 0, &draw);
790: PetscDrawGetPause(draw, &lpause);
791: PetscDrawSetPause(draw, -1.0);
792: PetscDrawPause(draw);
793: PetscDrawSetPause(draw, lpause);
794: }
795: }
796: return(0);
797: }
799: static PetscErrorCode KSPSolve_Private(KSP ksp,Vec b,Vec x)
800: {
802: PetscBool flg = PETSC_FALSE,inXisinB=PETSC_FALSE,guess_zero;
803: Mat mat,pmat;
804: MPI_Comm comm;
805: MatNullSpace nullsp;
806: Vec btmp,vec_rhs=NULL;
809: comm = PetscObjectComm((PetscObject)ksp);
810: if (x && x == b) {
811: if (!ksp->guess_zero) SETERRQ(comm,PETSC_ERR_ARG_INCOMP,"Cannot use x == b with nonzero initial guess");
812: VecDuplicate(b,&x);
813: inXisinB = PETSC_TRUE;
814: }
815: if (b) {
816: PetscObjectReference((PetscObject)b);
817: VecDestroy(&ksp->vec_rhs);
818: ksp->vec_rhs = b;
819: }
820: if (x) {
821: PetscObjectReference((PetscObject)x);
822: VecDestroy(&ksp->vec_sol);
823: ksp->vec_sol = x;
824: }
826: if (ksp->viewPre) {ObjectView((PetscObject) ksp, ksp->viewerPre, ksp->formatPre);}
828: if (ksp->presolve) {(*ksp->presolve)(ksp,ksp->vec_rhs,ksp->vec_sol,ksp->prectx);}
830: /* reset the residual history list if requested */
831: if (ksp->res_hist_reset) ksp->res_hist_len = 0;
832: if (ksp->err_hist_reset) ksp->err_hist_len = 0;
834: if (ksp->guess) {
835: PetscObjectState ostate,state;
837: KSPGuessSetUp(ksp->guess);
838: PetscObjectStateGet((PetscObject)ksp->vec_sol,&ostate);
839: KSPGuessFormGuess(ksp->guess,ksp->vec_rhs,ksp->vec_sol);
840: PetscObjectStateGet((PetscObject)ksp->vec_sol,&state);
841: if (state != ostate) {
842: ksp->guess_zero = PETSC_FALSE;
843: } else {
844: PetscInfo(ksp,"Using zero initial guess since the KSPGuess object did not change the vector\n");
845: ksp->guess_zero = PETSC_TRUE;
846: }
847: }
849: /* KSPSetUp() scales the matrix if needed */
850: KSPSetUp(ksp);
851: KSPSetUpOnBlocks(ksp);
853: VecSetErrorIfLocked(ksp->vec_sol,3);
855: PetscLogEventBegin(KSP_Solve,ksp,ksp->vec_rhs,ksp->vec_sol,0);
856: PCGetOperators(ksp->pc,&mat,&pmat);
857: /* diagonal scale RHS if called for */
858: if (ksp->dscale) {
859: VecPointwiseMult(ksp->vec_rhs,ksp->vec_rhs,ksp->diagonal);
860: /* second time in, but matrix was scaled back to original */
861: if (ksp->dscalefix && ksp->dscalefix2) {
862: Mat mat,pmat;
864: PCGetOperators(ksp->pc,&mat,&pmat);
865: MatDiagonalScale(pmat,ksp->diagonal,ksp->diagonal);
866: if (mat != pmat) {MatDiagonalScale(mat,ksp->diagonal,ksp->diagonal);}
867: }
869: /* scale initial guess */
870: if (!ksp->guess_zero) {
871: if (!ksp->truediagonal) {
872: VecDuplicate(ksp->diagonal,&ksp->truediagonal);
873: VecCopy(ksp->diagonal,ksp->truediagonal);
874: VecReciprocal(ksp->truediagonal);
875: }
876: VecPointwiseMult(ksp->vec_sol,ksp->vec_sol,ksp->truediagonal);
877: }
878: }
879: PCPreSolve(ksp->pc,ksp);
881: if (ksp->guess_zero) { VecSet(ksp->vec_sol,0.0);}
882: if (ksp->guess_knoll) { /* The Knoll trick is independent on the KSPGuess specified */
883: PCApply(ksp->pc,ksp->vec_rhs,ksp->vec_sol);
884: KSP_RemoveNullSpace(ksp,ksp->vec_sol);
885: ksp->guess_zero = PETSC_FALSE;
886: }
888: /* can we mark the initial guess as zero for this solve? */
889: guess_zero = ksp->guess_zero;
890: if (!ksp->guess_zero) {
891: PetscReal norm;
893: VecNormAvailable(ksp->vec_sol,NORM_2,&flg,&norm);
894: if (flg && !norm) ksp->guess_zero = PETSC_TRUE;
895: }
896: if (ksp->transpose_solve) {
897: MatGetNullSpace(pmat,&nullsp);
898: } else {
899: MatGetTransposeNullSpace(pmat,&nullsp);
900: }
901: if (nullsp) {
902: VecDuplicate(ksp->vec_rhs,&btmp);
903: VecCopy(ksp->vec_rhs,btmp);
904: MatNullSpaceRemove(nullsp,btmp);
905: vec_rhs = ksp->vec_rhs;
906: ksp->vec_rhs = btmp;
907: }
908: VecLockReadPush(ksp->vec_rhs);
909: if (ksp->reason == KSP_DIVERGED_PC_FAILED) {
910: VecSetInf(ksp->vec_sol);
911: }
912: (*ksp->ops->solve)(ksp);
913: KSPMonitorPauseFinal_Internal(ksp);
915: VecLockReadPop(ksp->vec_rhs);
916: if (nullsp) {
917: ksp->vec_rhs = vec_rhs;
918: VecDestroy(&btmp);
919: }
921: ksp->guess_zero = guess_zero;
923: if (!ksp->reason) SETERRQ(comm,PETSC_ERR_PLIB,"Internal error, solver returned without setting converged reason");
924: ksp->totalits += ksp->its;
926: KSPConvergedReasonViewFromOptions(ksp);
928: if (ksp->viewRate) {
929: PetscViewerPushFormat(ksp->viewerRate,ksp->formatRate);
930: KSPConvergedRateView(ksp, ksp->viewerRate);
931: PetscViewerPopFormat(ksp->viewerRate);
932: }
933: PCPostSolve(ksp->pc,ksp);
935: /* diagonal scale solution if called for */
936: if (ksp->dscale) {
937: VecPointwiseMult(ksp->vec_sol,ksp->vec_sol,ksp->diagonal);
938: /* unscale right hand side and matrix */
939: if (ksp->dscalefix) {
940: Mat mat,pmat;
942: VecReciprocal(ksp->diagonal);
943: VecPointwiseMult(ksp->vec_rhs,ksp->vec_rhs,ksp->diagonal);
944: PCGetOperators(ksp->pc,&mat,&pmat);
945: MatDiagonalScale(pmat,ksp->diagonal,ksp->diagonal);
946: if (mat != pmat) {MatDiagonalScale(mat,ksp->diagonal,ksp->diagonal);}
947: VecReciprocal(ksp->diagonal);
948: ksp->dscalefix2 = PETSC_TRUE;
949: }
950: }
951: PetscLogEventEnd(KSP_Solve,ksp,ksp->vec_rhs,ksp->vec_sol,0);
952: if (ksp->guess) {
953: KSPGuessUpdate(ksp->guess,ksp->vec_rhs,ksp->vec_sol);
954: }
955: if (ksp->postsolve) {
956: (*ksp->postsolve)(ksp,ksp->vec_rhs,ksp->vec_sol,ksp->postctx);
957: }
959: PCGetOperators(ksp->pc,&mat,&pmat);
960: if (ksp->viewEV) {KSPViewEigenvalues_Internal(ksp, PETSC_FALSE, ksp->viewerEV, ksp->formatEV);}
961: if (ksp->viewEVExp) {KSPViewEigenvalues_Internal(ksp, PETSC_TRUE, ksp->viewerEVExp, ksp->formatEVExp);}
962: if (ksp->viewSV) {KSPViewSingularvalues_Internal(ksp, ksp->viewerSV, ksp->formatSV);}
963: if (ksp->viewFinalRes) {KSPViewFinalResidual_Internal(ksp, ksp->viewerFinalRes, ksp->formatFinalRes);}
964: if (ksp->viewMat) {ObjectView((PetscObject) mat, ksp->viewerMat, ksp->formatMat);}
965: if (ksp->viewPMat) {ObjectView((PetscObject) pmat, ksp->viewerPMat, ksp->formatPMat);}
966: if (ksp->viewRhs) {ObjectView((PetscObject) ksp->vec_rhs, ksp->viewerRhs, ksp->formatRhs);}
967: if (ksp->viewSol) {ObjectView((PetscObject) ksp->vec_sol, ksp->viewerSol, ksp->formatSol);}
968: if (ksp->view) {ObjectView((PetscObject) ksp, ksp->viewer, ksp->format);}
969: if (ksp->viewDScale) {ObjectView((PetscObject) ksp->diagonal, ksp->viewerDScale, ksp->formatDScale);}
970: if (ksp->viewMatExp) {
971: Mat A, B;
973: PCGetOperators(ksp->pc, &A, NULL);
974: if (ksp->transpose_solve) {
975: Mat AT;
977: MatCreateTranspose(A, &AT);
978: MatComputeOperator(AT, MATAIJ, &B);
979: MatDestroy(&AT);
980: } else {
981: MatComputeOperator(A, MATAIJ, &B);
982: }
983: ObjectView((PetscObject) B, ksp->viewerMatExp, ksp->formatMatExp);
984: MatDestroy(&B);
985: }
986: if (ksp->viewPOpExp) {
987: Mat B;
989: KSPComputeOperator(ksp, MATAIJ, &B);
990: ObjectView((PetscObject) B, ksp->viewerPOpExp, ksp->formatPOpExp);
991: MatDestroy(&B);
992: }
994: if (inXisinB) {
995: VecCopy(x,b);
996: VecDestroy(&x);
997: }
998: PetscObjectSAWsBlock((PetscObject)ksp);
999: if (ksp->errorifnotconverged && ksp->reason < 0 && ksp->reason != KSP_DIVERGED_ITS) {
1000: if (ksp->reason == KSP_DIVERGED_PC_FAILED) {
1001: PCFailedReason reason;
1002: PCGetFailedReason(ksp->pc,&reason);
1003: SETERRQ2(comm,PETSC_ERR_NOT_CONVERGED,"KSPSolve has not converged, reason %s PC failed due to %s",KSPConvergedReasons[ksp->reason],PCFailedReasons[reason]);
1004: } else SETERRQ1(comm,PETSC_ERR_NOT_CONVERGED,"KSPSolve has not converged, reason %s",KSPConvergedReasons[ksp->reason]);
1005: }
1006: return(0);
1007: }
1009: /*@
1010: KSPSolve - Solves linear system.
1012: Collective on ksp
1014: Parameters:
1015: + ksp - iterative context obtained from KSPCreate()
1016: . b - the right hand side vector
1017: - x - the solution (this may be the same vector as b, then b will be overwritten with answer)
1019: Options Database Keys:
1020: + -ksp_view_eigenvalues - compute preconditioned operators eigenvalues
1021: . -ksp_view_eigenvalues_explicit - compute the eigenvalues by forming the dense operator and using LAPACK
1022: . -ksp_view_mat binary - save matrix to the default binary viewer
1023: . -ksp_view_pmat binary - save matrix used to build preconditioner to the default binary viewer
1024: . -ksp_view_rhs binary - save right hand side vector to the default binary viewer
1025: . -ksp_view_solution binary - save computed solution vector to the default binary viewer
1026: (can be read later with src/ksp/tutorials/ex10.c for testing solvers)
1027: . -ksp_view_mat_explicit - for matrix-free operators, computes the matrix entries and views them
1028: . -ksp_view_preconditioned_operator_explicit - computes the product of the preconditioner and matrix as an explicit matrix and views it
1029: . -ksp_converged_reason - print reason for converged or diverged, also prints number of iterations
1030: . -ksp_view_final_residual - print 2-norm of true linear system residual at the end of the solution process
1031: - -ksp_view - print the ksp data structure at the end of the system solution
1033: Notes:
1035: If one uses KSPSetDM() then x or b need not be passed. Use KSPGetSolution() to access the solution in this case.
1037: The operator is specified with KSPSetOperators().
1039: Call KSPGetConvergedReason() to determine if the solver converged or failed and
1040: why. The number of iterations can be obtained from KSPGetIterationNumber().
1042: If you provide a matrix that has a MatSetNullSpace() and MatSetTransposeNullSpace() this will use that information to solve singular systems
1043: in the least squares sense with a norm minimizing solution.
1044: $
1045: $ A x = b where b = b_p + b_t where b_t is not in the range of A (and hence by the fundamental theorem of linear algebra is in the nullspace(A') see MatSetNullSpace()
1046: $
1047: $ KSP first removes b_t producing the linear system A x = b_p (which has multiple solutions) and solves this to find the ||x|| minimizing solution (and hence
1048: $ it finds the solution x orthogonal to the nullspace(A). The algorithm is simply in each iteration of the Krylov method we remove the nullspace(A) from the search
1049: $ direction thus the solution which is a linear combination of the search directions has no component in the nullspace(A).
1050: $
1051: $ We recommend always using GMRES for such singular systems.
1052: $ If nullspace(A) = nullspace(A') (note symmetric matrices always satisfy this property) then both left and right preconditioning will work
1053: $ If nullspace(A) != nullspace(A') then left preconditioning will work but right preconditioning may not work (or it may).
1055: Developer Note: The reason we cannot always solve nullspace(A) != nullspace(A') systems with right preconditioning is because we need to remove at each iteration
1056: the nullspace(AB) from the search direction. While we know the nullspace(A) the nullspace(AB) equals B^-1 times the nullspace(A) but except for trivial preconditioners
1057: such as diagonal scaling we cannot apply the inverse of the preconditioner to a vector and thus cannot compute the nullspace(AB).
1060: If using a direct method (e.g., via the KSP solver
1061: KSPPREONLY and a preconditioner such as PCLU/PCILU),
1062: then its=1. See KSPSetTolerances() and KSPConvergedDefault()
1063: for more details.
1065: Understanding Convergence:
1066: The routines KSPMonitorSet(), KSPComputeEigenvalues(), and
1067: KSPComputeEigenvaluesExplicitly() provide information on additional
1068: options to monitor convergence and print eigenvalue information.
1070: Level: beginner
1072: .seealso: KSPCreate(), KSPSetUp(), KSPDestroy(), KSPSetTolerances(), KSPConvergedDefault(),
1073: KSPSolveTranspose(), KSPGetIterationNumber(), MatNullSpaceCreate(), MatSetNullSpace(), MatSetTransposeNullSpace(), KSP,
1074: KSPConvergedReasonView()
1075: @*/
1076: PetscErrorCode KSPSolve(KSP ksp,Vec b,Vec x)
1077: {
1084: ksp->transpose_solve = PETSC_FALSE;
1085: KSPSolve_Private(ksp,b,x);
1086: return(0);
1087: }
1089: /*@
1090: KSPSolveTranspose - Solves the transpose of a linear system.
1092: Collective on ksp
1094: Input Parameters:
1095: + ksp - iterative context obtained from KSPCreate()
1096: . b - right hand side vector
1097: - x - solution vector
1099: Notes:
1100: For complex numbers this solve the non-Hermitian transpose system.
1102: Developer Notes:
1103: We need to implement a KSPSolveHermitianTranspose()
1105: Level: developer
1107: .seealso: KSPCreate(), KSPSetUp(), KSPDestroy(), KSPSetTolerances(), KSPConvergedDefault(),
1108: KSPSolve(), KSP
1109: @*/
1110: PetscErrorCode KSPSolveTranspose(KSP ksp,Vec b,Vec x)
1111: {
1118: if (ksp->transpose.use_explicittranspose) {
1119: Mat J,Jpre;
1120: KSPGetOperators(ksp,&J,&Jpre);
1121: if (!ksp->transpose.reuse_transpose) {
1122: MatTranspose(J,MAT_INITIAL_MATRIX,&ksp->transpose.AT);
1123: if (J != Jpre) {
1124: MatTranspose(Jpre,MAT_INITIAL_MATRIX,&ksp->transpose.BT);
1125: }
1126: ksp->transpose.reuse_transpose = PETSC_TRUE;
1127: } else {
1128: MatTranspose(J,MAT_REUSE_MATRIX,&ksp->transpose.AT);
1129: if (J != Jpre) {
1130: MatTranspose(Jpre,MAT_REUSE_MATRIX,&ksp->transpose.BT);
1131: }
1132: }
1133: if (J == Jpre && ksp->transpose.BT != ksp->transpose.AT) {
1134: PetscObjectReference((PetscObject)ksp->transpose.AT);
1135: ksp->transpose.BT = ksp->transpose.AT;
1136: }
1137: KSPSetOperators(ksp,ksp->transpose.AT,ksp->transpose.BT);
1138: } else {
1139: ksp->transpose_solve = PETSC_TRUE;
1140: }
1141: KSPSolve_Private(ksp,b,x);
1142: return(0);
1143: }
1145: static PetscErrorCode KSPViewFinalMatResidual_Internal(KSP ksp, Mat B, Mat X, PetscViewer viewer, PetscViewerFormat format, PetscInt shift)
1146: {
1147: Mat A, R;
1148: PetscReal *norms;
1149: PetscInt i, N;
1150: PetscBool flg;
1154: PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &flg);
1155: if (flg) {
1156: PCGetOperators(ksp->pc, &A, NULL);
1157: MatMatMult(A, X, MAT_INITIAL_MATRIX, PETSC_DEFAULT, &R);
1158: MatAYPX(R, -1.0, B, SAME_NONZERO_PATTERN);
1159: MatGetSize(R, NULL, &N);
1160: PetscMalloc1(N, &norms);
1161: MatGetColumnNorms(R, NORM_2, norms);
1162: MatDestroy(&R);
1163: for (i = 0; i < N; ++i) {
1164: PetscViewerASCIIPrintf(viewer, "%s #%D %g\n", i == 0 ? "KSP final norm of residual" : " ", shift + i, (double)norms[i]);
1165: }
1166: PetscFree(norms);
1167: }
1168: return(0);
1169: }
1171: /*@
1172: KSPMatSolve - Solves a linear system with multiple right-hand sides stored as a MATDENSE. Unlike KSPSolve(), B and X must be different matrices.
1174: Input Parameters:
1175: + ksp - iterative context
1176: - B - block of right-hand sides
1178: Output Parameter:
1179: . X - block of solutions
1181: Notes:
1182: This is a stripped-down version of KSPSolve(), which only handles -ksp_view, -ksp_converged_reason, and -ksp_view_final_residual.
1184: Level: intermediate
1186: .seealso: KSPSolve(), MatMatSolve(), MATDENSE, KSPHPDDM, PCBJACOBI, PCASM
1187: @*/
1188: PetscErrorCode KSPMatSolve(KSP ksp, Mat B, Mat X)
1189: {
1190: Mat A, vB, vX;
1191: Vec cb, cx;
1192: PetscInt m1, M1, m2, M2, n1, N1, n2, N2, Bbn = PETSC_DECIDE;
1193: PetscBool match;
1202: if (!B->assembled) SETERRQ(PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Not for unassembled matrix");
1203: MatCheckPreallocated(X, 3);
1204: if (!X->assembled) {
1205: MatSetOption(X, MAT_NO_OFF_PROC_ENTRIES, PETSC_TRUE);
1206: MatAssemblyBegin(X, MAT_FINAL_ASSEMBLY);
1207: MatAssemblyEnd(X, MAT_FINAL_ASSEMBLY);
1208: }
1209: if (B == X) SETERRQ(PetscObjectComm((PetscObject)ksp), PETSC_ERR_ARG_IDN, "B and X must be different matrices");
1210: KSPGetOperators(ksp, &A, NULL);
1211: MatGetLocalSize(A, &m1, NULL);
1212: MatGetLocalSize(B, &m2, &n2);
1213: MatGetSize(A, &M1, NULL);
1214: MatGetSize(B, &M2, &N2);
1215: if (m1 != m2 || M1 != M2) SETERRQ4(PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Cannot use a block of right-hand sides with (m2,M2) = (%D,%D) for a linear system with (m1,M1) = (%D,%D)", m2, M2, m1, M1);
1216: MatGetLocalSize(X, &m1, &n1);
1217: MatGetSize(X, &M1, &N1);
1218: if (m1 != m2 || M1 != M2 || n1 != n2 || N1 != N2) SETERRQ8(PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Incompatible block of right-hand sides (m2,M2)x(n2,N2) = (%D,%D)x(%D,%D) and solutions (m1,M1)x(n1,N1) = (%D,%D)x(%D,%D)", m2, M2, n2, N2, m1, M1, n1, N1);
1219: PetscObjectBaseTypeCompareAny((PetscObject)B, &match, MATSEQDENSE, MATMPIDENSE, "");
1220: if (!match) SETERRQ(PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Provided block of right-hand sides not stored in a dense Mat");
1221: PetscObjectBaseTypeCompareAny((PetscObject)X, &match, MATSEQDENSE, MATMPIDENSE, "");
1222: if (!match) SETERRQ(PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Provided block of solutions not stored in a dense Mat");
1223: KSPSetUp(ksp);
1224: KSPSetUpOnBlocks(ksp);
1225: if (ksp->ops->matsolve) {
1226: if (ksp->guess_zero) {
1227: MatZeroEntries(X);
1228: }
1229: PetscLogEventBegin(KSP_MatSolve, ksp, B, X, 0);
1230: KSPGetMatSolveBatchSize(ksp, &Bbn);
1231: /* by default, do a single solve with all columns */
1232: if (Bbn == PETSC_DECIDE) Bbn = N2;
1233: else if (Bbn < 1) SETERRQ1(PetscObjectComm((PetscObject)ksp), PETSC_ERR_ARG_OUTOFRANGE, "KSPMatSolve() block size %D must be positive", Bbn);
1234: PetscInfo2(ksp, "KSP type %s solving using blocks of width at most %D\n", ((PetscObject)ksp)->type_name, Bbn);
1235: /* if -ksp_matsolve_batch_size is greater than the actual number of columns, do a single solve with all columns */
1236: if (Bbn >= N2) {
1237: (*ksp->ops->matsolve)(ksp, B, X);
1238: if (ksp->viewFinalRes) {
1239: KSPViewFinalMatResidual_Internal(ksp, B, X, ksp->viewerFinalRes, ksp->formatFinalRes, 0);
1240: }
1242: KSPConvergedReasonViewFromOptions(ksp);
1244: if (ksp->viewRate) {
1245: PetscViewerPushFormat(ksp->viewerRate,PETSC_VIEWER_DEFAULT);
1246: KSPConvergedRateView(ksp, ksp->viewerRate);
1247: PetscViewerPopFormat(ksp->viewerRate);
1248: }
1249: } else {
1250: for (n2 = 0; n2 < N2; n2 += Bbn) {
1251: MatDenseGetSubMatrix(B, n2, PetscMin(n2+Bbn, N2), &vB);
1252: MatDenseGetSubMatrix(X, n2, PetscMin(n2+Bbn, N2), &vX);
1253: (*ksp->ops->matsolve)(ksp, vB, vX);
1254: if (ksp->viewFinalRes) {
1255: KSPViewFinalMatResidual_Internal(ksp, vB, vX, ksp->viewerFinalRes, ksp->formatFinalRes, n2);
1256: }
1258: KSPConvergedReasonViewFromOptions(ksp);
1260: if (ksp->viewRate) {
1261: PetscViewerPushFormat(ksp->viewerRate,PETSC_VIEWER_DEFAULT);
1262: KSPConvergedRateView(ksp, ksp->viewerRate);
1263: PetscViewerPopFormat(ksp->viewerRate);
1264: }
1265: MatDenseRestoreSubMatrix(B, &vB);
1266: MatDenseRestoreSubMatrix(X, &vX);
1267: }
1268: }
1269: if (ksp->view) {
1270: KSPView(ksp, ksp->viewer);
1271: }
1272: PetscLogEventEnd(KSP_MatSolve, ksp, B, X, 0);
1273: } else {
1274: PetscInfo1(ksp, "KSP type %s solving column by column\n", ((PetscObject)ksp)->type_name);
1275: for (n2 = 0; n2 < N2; ++n2) {
1276: MatDenseGetColumnVecRead(B, n2, &cb);
1277: MatDenseGetColumnVecWrite(X, n2, &cx);
1278: KSPSolve(ksp, cb, cx);
1279: MatDenseRestoreColumnVecWrite(X, n2, &cx);
1280: MatDenseRestoreColumnVecRead(B, n2, &cb);
1281: }
1282: }
1283: return(0);
1284: }
1286: /*@
1287: KSPSetMatSolveBatchSize - Sets the maximum number of columns treated simultaneously in KSPMatSolve().
1289: Logically collective
1291: Input Parameters:
1292: + ksp - iterative context
1293: - bs - block size
1295: Level: advanced
1297: .seealso: KSPMatSolve(), KSPGetMatSolveBatchSize(), -mat_mumps_icntl_27, -matmatmult_Bbn
1298: @*/
1299: PetscErrorCode KSPSetMatSolveBatchSize(KSP ksp, PetscInt bs)
1300: {
1304: ksp->nmax = bs;
1305: return(0);
1306: }
1308: /*@
1309: KSPGetMatSolveBatchSize - Gets the maximum number of columns treated simultaneously in KSPMatSolve().
1311: Input Parameter:
1312: . ksp - iterative context
1314: Output Parameter:
1315: . bs - block size
1317: Level: advanced
1319: .seealso: KSPMatSolve(), KSPSetMatSolveBatchSize(), -mat_mumps_icntl_27, -matmatmult_Bbn
1320: @*/
1321: PetscErrorCode KSPGetMatSolveBatchSize(KSP ksp, PetscInt *bs)
1322: {
1326: *bs = ksp->nmax;
1327: return(0);
1328: }
1330: /*@
1331: KSPResetViewers - Resets all the viewers set from the options database during KSPSetFromOptions()
1333: Collective on ksp
1335: Input Parameter:
1336: . ksp - iterative context obtained from KSPCreate()
1338: Level: beginner
1340: .seealso: KSPCreate(), KSPSetUp(), KSPSolve(), KSPSetFromOptions(), KSP
1341: @*/
1342: PetscErrorCode KSPResetViewers(KSP ksp)
1343: {
1348: if (!ksp) return(0);
1349: PetscViewerDestroy(&ksp->viewer);
1350: PetscViewerDestroy(&ksp->viewerPre);
1351: PetscViewerDestroy(&ksp->viewerRate);
1352: PetscViewerDestroy(&ksp->viewerMat);
1353: PetscViewerDestroy(&ksp->viewerPMat);
1354: PetscViewerDestroy(&ksp->viewerRhs);
1355: PetscViewerDestroy(&ksp->viewerSol);
1356: PetscViewerDestroy(&ksp->viewerMatExp);
1357: PetscViewerDestroy(&ksp->viewerEV);
1358: PetscViewerDestroy(&ksp->viewerSV);
1359: PetscViewerDestroy(&ksp->viewerEVExp);
1360: PetscViewerDestroy(&ksp->viewerFinalRes);
1361: PetscViewerDestroy(&ksp->viewerPOpExp);
1362: PetscViewerDestroy(&ksp->viewerDScale);
1363: ksp->view = PETSC_FALSE;
1364: ksp->viewPre = PETSC_FALSE;
1365: ksp->viewMat = PETSC_FALSE;
1366: ksp->viewPMat = PETSC_FALSE;
1367: ksp->viewRhs = PETSC_FALSE;
1368: ksp->viewSol = PETSC_FALSE;
1369: ksp->viewMatExp = PETSC_FALSE;
1370: ksp->viewEV = PETSC_FALSE;
1371: ksp->viewSV = PETSC_FALSE;
1372: ksp->viewEVExp = PETSC_FALSE;
1373: ksp->viewFinalRes = PETSC_FALSE;
1374: ksp->viewPOpExp = PETSC_FALSE;
1375: ksp->viewDScale = PETSC_FALSE;
1376: return(0);
1377: }
1379: /*@
1380: KSPReset - Resets a KSP context to the kspsetupcalled = 0 state and removes any allocated Vecs and Mats
1382: Collective on ksp
1384: Input Parameter:
1385: . ksp - iterative context obtained from KSPCreate()
1387: Level: beginner
1389: .seealso: KSPCreate(), KSPSetUp(), KSPSolve(), KSP
1390: @*/
1391: PetscErrorCode KSPReset(KSP ksp)
1392: {
1397: if (!ksp) return(0);
1398: if (ksp->ops->reset) {
1399: (*ksp->ops->reset)(ksp);
1400: }
1401: if (ksp->pc) {PCReset(ksp->pc);}
1402: if (ksp->guess) {
1403: KSPGuess guess = ksp->guess;
1404: if (guess->ops->reset) { (*guess->ops->reset)(guess); }
1405: }
1406: VecDestroyVecs(ksp->nwork,&ksp->work);
1407: VecDestroy(&ksp->vec_rhs);
1408: VecDestroy(&ksp->vec_sol);
1409: VecDestroy(&ksp->diagonal);
1410: VecDestroy(&ksp->truediagonal);
1412: KSPResetViewers(ksp);
1414: ksp->setupstage = KSP_SETUP_NEW;
1415: ksp->nmax = PETSC_DECIDE;
1416: return(0);
1417: }
1419: /*@C
1420: KSPDestroy - Destroys KSP context.
1422: Collective on ksp
1424: Input Parameter:
1425: . ksp - iterative context obtained from KSPCreate()
1427: Level: beginner
1429: .seealso: KSPCreate(), KSPSetUp(), KSPSolve(), KSP
1430: @*/
1431: PetscErrorCode KSPDestroy(KSP *ksp)
1432: {
1434: PC pc;
1437: if (!*ksp) return(0);
1439: if (--((PetscObject)(*ksp))->refct > 0) {*ksp = NULL; return(0);}
1441: PetscObjectSAWsViewOff((PetscObject)*ksp);
1443: /*
1444: Avoid a cascading call to PCReset(ksp->pc) from the following call:
1445: PCReset() shouldn't be called from KSPDestroy() as it is unprotected by pc's
1446: refcount (and may be shared, e.g., by other ksps).
1447: */
1448: pc = (*ksp)->pc;
1449: (*ksp)->pc = NULL;
1450: KSPReset((*ksp));
1451: (*ksp)->pc = pc;
1452: if ((*ksp)->ops->destroy) {(*(*ksp)->ops->destroy)(*ksp);}
1454: if ((*ksp)->transpose.use_explicittranspose) {
1455: MatDestroy(&(*ksp)->transpose.AT);
1456: MatDestroy(&(*ksp)->transpose.BT);
1457: (*ksp)->transpose.reuse_transpose = PETSC_FALSE;
1458: }
1460: KSPGuessDestroy(&(*ksp)->guess);
1461: DMDestroy(&(*ksp)->dm);
1462: PCDestroy(&(*ksp)->pc);
1463: PetscFree((*ksp)->res_hist_alloc);
1464: PetscFree((*ksp)->err_hist_alloc);
1465: if ((*ksp)->convergeddestroy) {
1466: (*(*ksp)->convergeddestroy)((*ksp)->cnvP);
1467: }
1468: KSPMonitorCancel((*ksp));
1469: KSPConvergedReasonViewCancel((*ksp));
1470: PetscViewerDestroy(&(*ksp)->eigviewer);
1471: PetscHeaderDestroy(ksp);
1472: return(0);
1473: }
1475: /*@
1476: KSPSetPCSide - Sets the preconditioning side.
1478: Logically Collective on ksp
1480: Input Parameter:
1481: . ksp - iterative context obtained from KSPCreate()
1483: Output Parameter:
1484: . side - the preconditioning side, where side is one of
1485: .vb
1486: PC_LEFT - left preconditioning (default)
1487: PC_RIGHT - right preconditioning
1488: PC_SYMMETRIC - symmetric preconditioning
1489: .ve
1491: Options Database Keys:
1492: . -ksp_pc_side <right,left,symmetric>
1494: Notes:
1495: Left preconditioning is used by default for most Krylov methods except KSPFGMRES which only supports right preconditioning.
1497: For methods changing the side of the preconditioner changes the norm type that is used, see KSPSetNormType().
1499: Symmetric preconditioning is currently available only for the KSPQCG method. Note, however, that
1500: symmetric preconditioning can be emulated by using either right or left
1501: preconditioning and a pre or post processing step.
1503: Setting the PC side often affects the default norm type. See KSPSetNormType() for details.
1505: Level: intermediate
1507: .seealso: KSPGetPCSide(), KSPSetNormType(), KSPGetNormType(), KSP
1508: @*/
1509: PetscErrorCode KSPSetPCSide(KSP ksp,PCSide side)
1510: {
1514: ksp->pc_side = ksp->pc_side_set = side;
1515: return(0);
1516: }
1518: /*@
1519: KSPGetPCSide - Gets the preconditioning side.
1521: Not Collective
1523: Input Parameter:
1524: . ksp - iterative context obtained from KSPCreate()
1526: Output Parameter:
1527: . side - the preconditioning side, where side is one of
1528: .vb
1529: PC_LEFT - left preconditioning (default)
1530: PC_RIGHT - right preconditioning
1531: PC_SYMMETRIC - symmetric preconditioning
1532: .ve
1534: Level: intermediate
1536: .seealso: KSPSetPCSide(), KSP
1537: @*/
1538: PetscErrorCode KSPGetPCSide(KSP ksp,PCSide *side)
1539: {
1545: KSPSetUpNorms_Private(ksp,PETSC_TRUE,&ksp->normtype,&ksp->pc_side);
1546: *side = ksp->pc_side;
1547: return(0);
1548: }
1550: /*@
1551: KSPGetTolerances - Gets the relative, absolute, divergence, and maximum
1552: iteration tolerances used by the default KSP convergence tests.
1554: Not Collective
1556: Input Parameter:
1557: . ksp - the Krylov subspace context
1559: Output Parameters:
1560: + rtol - the relative convergence tolerance
1561: . abstol - the absolute convergence tolerance
1562: . dtol - the divergence tolerance
1563: - maxits - maximum number of iterations
1565: Notes:
1566: The user can specify NULL for any parameter that is not needed.
1568: Level: intermediate
1570: maximum, iterations
1572: .seealso: KSPSetTolerances(), KSP
1573: @*/
1574: PetscErrorCode KSPGetTolerances(KSP ksp,PetscReal *rtol,PetscReal *abstol,PetscReal *dtol,PetscInt *maxits)
1575: {
1578: if (abstol) *abstol = ksp->abstol;
1579: if (rtol) *rtol = ksp->rtol;
1580: if (dtol) *dtol = ksp->divtol;
1581: if (maxits) *maxits = ksp->max_it;
1582: return(0);
1583: }
1585: /*@
1586: KSPSetTolerances - Sets the relative, absolute, divergence, and maximum
1587: iteration tolerances used by the default KSP convergence testers.
1589: Logically Collective on ksp
1591: Input Parameters:
1592: + ksp - the Krylov subspace context
1593: . rtol - the relative convergence tolerance, relative decrease in the (possibly preconditioned) residual norm
1594: . abstol - the absolute convergence tolerance absolute size of the (possibly preconditioned) residual norm
1595: . dtol - the divergence tolerance, amount (possibly preconditioned) residual norm can increase before KSPConvergedDefault() concludes that the method is diverging
1596: - maxits - maximum number of iterations to use
1598: Options Database Keys:
1599: + -ksp_atol <abstol> - Sets abstol
1600: . -ksp_rtol <rtol> - Sets rtol
1601: . -ksp_divtol <dtol> - Sets dtol
1602: - -ksp_max_it <maxits> - Sets maxits
1604: Notes:
1605: Use PETSC_DEFAULT to retain the default value of any of the tolerances.
1607: See KSPConvergedDefault() for details how these parameters are used in the default convergence test. See also KSPSetConvergenceTest()
1608: for setting user-defined stopping criteria.
1610: Level: intermediate
1612: convergence, maximum, iterations
1614: .seealso: KSPGetTolerances(), KSPConvergedDefault(), KSPSetConvergenceTest(), KSP
1615: @*/
1616: PetscErrorCode KSPSetTolerances(KSP ksp,PetscReal rtol,PetscReal abstol,PetscReal dtol,PetscInt maxits)
1617: {
1625: if (rtol != PETSC_DEFAULT) {
1626: if (rtol < 0.0 || 1.0 <= rtol) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Relative tolerance %g must be non-negative and less than 1.0",(double)rtol);
1627: ksp->rtol = rtol;
1628: }
1629: if (abstol != PETSC_DEFAULT) {
1630: if (abstol < 0.0) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Absolute tolerance %g must be non-negative",(double)abstol);
1631: ksp->abstol = abstol;
1632: }
1633: if (dtol != PETSC_DEFAULT) {
1634: if (dtol < 0.0) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Divergence tolerance %g must be larger than 1.0",(double)dtol);
1635: ksp->divtol = dtol;
1636: }
1637: if (maxits != PETSC_DEFAULT) {
1638: if (maxits < 0) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Maximum number of iterations %D must be non-negative",maxits);
1639: ksp->max_it = maxits;
1640: }
1641: return(0);
1642: }
1644: /*@
1645: KSPSetInitialGuessNonzero - Tells the iterative solver that the
1646: initial guess is nonzero; otherwise KSP assumes the initial guess
1647: is to be zero (and thus zeros it out before solving).
1649: Logically Collective on ksp
1651: Input Parameters:
1652: + ksp - iterative context obtained from KSPCreate()
1653: - flg - PETSC_TRUE indicates the guess is non-zero, PETSC_FALSE indicates the guess is zero
1655: Options database keys:
1656: . -ksp_initial_guess_nonzero : use nonzero initial guess; this takes an optional truth value (0/1/no/yes/true/false)
1658: Level: beginner
1660: Notes:
1661: If this is not called the X vector is zeroed in the call to KSPSolve().
1663: .seealso: KSPGetInitialGuessNonzero(), KSPSetGuessType(), KSPGuessType, KSP
1664: @*/
1665: PetscErrorCode KSPSetInitialGuessNonzero(KSP ksp,PetscBool flg)
1666: {
1670: ksp->guess_zero = (PetscBool) !(int)flg;
1671: return(0);
1672: }
1674: /*@
1675: KSPGetInitialGuessNonzero - Determines whether the KSP solver is using
1676: a zero initial guess.
1678: Not Collective
1680: Input Parameter:
1681: . ksp - iterative context obtained from KSPCreate()
1683: Output Parameter:
1684: . flag - PETSC_TRUE if guess is nonzero, else PETSC_FALSE
1686: Level: intermediate
1688: .seealso: KSPSetInitialGuessNonzero(), KSP
1689: @*/
1690: PetscErrorCode KSPGetInitialGuessNonzero(KSP ksp,PetscBool *flag)
1691: {
1695: if (ksp->guess_zero) *flag = PETSC_FALSE;
1696: else *flag = PETSC_TRUE;
1697: return(0);
1698: }
1700: /*@
1701: KSPSetErrorIfNotConverged - Causes KSPSolve() to generate an error if the solver has not converged.
1703: Logically Collective on ksp
1705: Input Parameters:
1706: + ksp - iterative context obtained from KSPCreate()
1707: - flg - PETSC_TRUE indicates you want the error generated
1709: Options database keys:
1710: . -ksp_error_if_not_converged : this takes an optional truth value (0/1/no/yes/true/false)
1712: Level: intermediate
1714: Notes:
1715: Normally PETSc continues if a linear solver fails to converge, you can call KSPGetConvergedReason() after a KSPSolve()
1716: to determine if it has converged.
1719: .seealso: KSPGetErrorIfNotConverged(), KSP
1720: @*/
1721: PetscErrorCode KSPSetErrorIfNotConverged(KSP ksp,PetscBool flg)
1722: {
1726: ksp->errorifnotconverged = flg;
1727: return(0);
1728: }
1730: /*@
1731: KSPGetErrorIfNotConverged - Will KSPSolve() generate an error if the solver does not converge?
1733: Not Collective
1735: Input Parameter:
1736: . ksp - iterative context obtained from KSPCreate()
1738: Output Parameter:
1739: . flag - PETSC_TRUE if it will generate an error, else PETSC_FALSE
1741: Level: intermediate
1743: .seealso: KSPSetErrorIfNotConverged(), KSP
1744: @*/
1745: PetscErrorCode KSPGetErrorIfNotConverged(KSP ksp,PetscBool *flag)
1746: {
1750: *flag = ksp->errorifnotconverged;
1751: return(0);
1752: }
1754: /*@
1755: KSPSetInitialGuessKnoll - Tells the iterative solver to use PCApply(pc,b,..) to compute the initial guess (The Knoll trick)
1757: Logically Collective on ksp
1759: Input Parameters:
1760: + ksp - iterative context obtained from KSPCreate()
1761: - flg - PETSC_TRUE or PETSC_FALSE
1763: Level: advanced
1765: Developer Note: the Knoll trick is not currently implemented using the KSPGuess class
1767: .seealso: KSPGetInitialGuessKnoll(), KSPSetInitialGuessNonzero(), KSPGetInitialGuessNonzero(), KSP
1768: @*/
1769: PetscErrorCode KSPSetInitialGuessKnoll(KSP ksp,PetscBool flg)
1770: {
1774: ksp->guess_knoll = flg;
1775: return(0);
1776: }
1778: /*@
1779: KSPGetInitialGuessKnoll - Determines whether the KSP solver is using the Knoll trick (using PCApply(pc,b,...) to compute
1780: the initial guess
1782: Not Collective
1784: Input Parameter:
1785: . ksp - iterative context obtained from KSPCreate()
1787: Output Parameter:
1788: . flag - PETSC_TRUE if using Knoll trick, else PETSC_FALSE
1790: Level: advanced
1792: .seealso: KSPSetInitialGuessKnoll(), KSPSetInitialGuessNonzero(), KSPGetInitialGuessNonzero(), KSP
1793: @*/
1794: PetscErrorCode KSPGetInitialGuessKnoll(KSP ksp,PetscBool *flag)
1795: {
1799: *flag = ksp->guess_knoll;
1800: return(0);
1801: }
1803: /*@
1804: KSPGetComputeSingularValues - Gets the flag indicating whether the extreme singular
1805: values will be calculated via a Lanczos or Arnoldi process as the linear
1806: system is solved.
1808: Not Collective
1810: Input Parameter:
1811: . ksp - iterative context obtained from KSPCreate()
1813: Output Parameter:
1814: . flg - PETSC_TRUE or PETSC_FALSE
1816: Options Database Key:
1817: . -ksp_monitor_singular_value - Activates KSPSetComputeSingularValues()
1819: Notes:
1820: Currently this option is not valid for all iterative methods.
1822: Many users may just want to use the monitoring routine
1823: KSPMonitorSingularValue() (which can be set with option -ksp_monitor_singular_value)
1824: to print the singular values at each iteration of the linear solve.
1826: Level: advanced
1828: .seealso: KSPComputeExtremeSingularValues(), KSPMonitorSingularValue(), KSP
1829: @*/
1830: PetscErrorCode KSPGetComputeSingularValues(KSP ksp,PetscBool *flg)
1831: {
1835: *flg = ksp->calc_sings;
1836: return(0);
1837: }
1839: /*@
1840: KSPSetComputeSingularValues - Sets a flag so that the extreme singular
1841: values will be calculated via a Lanczos or Arnoldi process as the linear
1842: system is solved.
1844: Logically Collective on ksp
1846: Input Parameters:
1847: + ksp - iterative context obtained from KSPCreate()
1848: - flg - PETSC_TRUE or PETSC_FALSE
1850: Options Database Key:
1851: . -ksp_monitor_singular_value - Activates KSPSetComputeSingularValues()
1853: Notes:
1854: Currently this option is not valid for all iterative methods.
1856: Many users may just want to use the monitoring routine
1857: KSPMonitorSingularValue() (which can be set with option -ksp_monitor_singular_value)
1858: to print the singular values at each iteration of the linear solve.
1860: Level: advanced
1862: .seealso: KSPComputeExtremeSingularValues(), KSPMonitorSingularValue(), KSP
1863: @*/
1864: PetscErrorCode KSPSetComputeSingularValues(KSP ksp,PetscBool flg)
1865: {
1869: ksp->calc_sings = flg;
1870: return(0);
1871: }
1873: /*@
1874: KSPGetComputeEigenvalues - Gets the flag indicating that the extreme eigenvalues
1875: values will be calculated via a Lanczos or Arnoldi process as the linear
1876: system is solved.
1878: Not Collective
1880: Input Parameter:
1881: . ksp - iterative context obtained from KSPCreate()
1883: Output Parameter:
1884: . flg - PETSC_TRUE or PETSC_FALSE
1886: Notes:
1887: Currently this option is not valid for all iterative methods.
1889: Level: advanced
1891: .seealso: KSPComputeEigenvalues(), KSPComputeEigenvaluesExplicitly(), KSP
1892: @*/
1893: PetscErrorCode KSPGetComputeEigenvalues(KSP ksp,PetscBool *flg)
1894: {
1898: *flg = ksp->calc_sings;
1899: return(0);
1900: }
1902: /*@
1903: KSPSetComputeEigenvalues - Sets a flag so that the extreme eigenvalues
1904: values will be calculated via a Lanczos or Arnoldi process as the linear
1905: system is solved.
1907: Logically Collective on ksp
1909: Input Parameters:
1910: + ksp - iterative context obtained from KSPCreate()
1911: - flg - PETSC_TRUE or PETSC_FALSE
1913: Notes:
1914: Currently this option is not valid for all iterative methods.
1916: Level: advanced
1918: .seealso: KSPComputeEigenvalues(), KSPComputeEigenvaluesExplicitly(), KSP
1919: @*/
1920: PetscErrorCode KSPSetComputeEigenvalues(KSP ksp,PetscBool flg)
1921: {
1925: ksp->calc_sings = flg;
1926: return(0);
1927: }
1929: /*@
1930: KSPSetComputeRitz - Sets a flag so that the Ritz or harmonic Ritz pairs
1931: will be calculated via a Lanczos or Arnoldi process as the linear
1932: system is solved.
1934: Logically Collective on ksp
1936: Input Parameters:
1937: + ksp - iterative context obtained from KSPCreate()
1938: - flg - PETSC_TRUE or PETSC_FALSE
1940: Notes:
1941: Currently this option is only valid for the GMRES method.
1943: Level: advanced
1945: .seealso: KSPComputeRitz(), KSP
1946: @*/
1947: PetscErrorCode KSPSetComputeRitz(KSP ksp, PetscBool flg)
1948: {
1952: ksp->calc_ritz = flg;
1953: return(0);
1954: }
1956: /*@
1957: KSPGetRhs - Gets the right-hand-side vector for the linear system to
1958: be solved.
1960: Not Collective
1962: Input Parameter:
1963: . ksp - iterative context obtained from KSPCreate()
1965: Output Parameter:
1966: . r - right-hand-side vector
1968: Level: developer
1970: .seealso: KSPGetSolution(), KSPSolve(), KSP
1971: @*/
1972: PetscErrorCode KSPGetRhs(KSP ksp,Vec *r)
1973: {
1977: *r = ksp->vec_rhs;
1978: return(0);
1979: }
1981: /*@
1982: KSPGetSolution - Gets the location of the solution for the
1983: linear system to be solved. Note that this may not be where the solution
1984: is stored during the iterative process; see KSPBuildSolution().
1986: Not Collective
1988: Input Parameters:
1989: . ksp - iterative context obtained from KSPCreate()
1991: Output Parameters:
1992: . v - solution vector
1994: Level: developer
1996: .seealso: KSPGetRhs(), KSPBuildSolution(), KSPSolve(), KSP
1997: @*/
1998: PetscErrorCode KSPGetSolution(KSP ksp,Vec *v)
1999: {
2003: *v = ksp->vec_sol;
2004: return(0);
2005: }
2007: /*@
2008: KSPSetPC - Sets the preconditioner to be used to calculate the
2009: application of the preconditioner on a vector.
2011: Collective on ksp
2013: Input Parameters:
2014: + ksp - iterative context obtained from KSPCreate()
2015: - pc - the preconditioner object (can be NULL)
2017: Notes:
2018: Use KSPGetPC() to retrieve the preconditioner context.
2020: Level: developer
2022: .seealso: KSPGetPC(), KSP
2023: @*/
2024: PetscErrorCode KSPSetPC(KSP ksp,PC pc)
2025: {
2030: if (pc) {
2033: }
2034: PetscObjectReference((PetscObject)pc);
2035: PCDestroy(&ksp->pc);
2036: ksp->pc = pc;
2037: PetscLogObjectParent((PetscObject)ksp,(PetscObject)ksp->pc);
2038: return(0);
2039: }
2041: /*@
2042: KSPGetPC - Returns a pointer to the preconditioner context
2043: set with KSPSetPC().
2045: Not Collective
2047: Input Parameters:
2048: . ksp - iterative context obtained from KSPCreate()
2050: Output Parameter:
2051: . pc - preconditioner context
2053: Level: developer
2055: .seealso: KSPSetPC(), KSP
2056: @*/
2057: PetscErrorCode KSPGetPC(KSP ksp,PC *pc)
2058: {
2064: if (!ksp->pc) {
2065: PCCreate(PetscObjectComm((PetscObject)ksp),&ksp->pc);
2066: PetscObjectIncrementTabLevel((PetscObject)ksp->pc,(PetscObject)ksp,0);
2067: PetscLogObjectParent((PetscObject)ksp,(PetscObject)ksp->pc);
2068: PetscObjectSetOptions((PetscObject)ksp->pc,((PetscObject)ksp)->options);
2069: }
2070: *pc = ksp->pc;
2071: return(0);
2072: }
2074: /*@
2075: KSPMonitor - runs the user provided monitor routines, if they exist
2077: Collective on ksp
2079: Input Parameters:
2080: + ksp - iterative context obtained from KSPCreate()
2081: . it - iteration number
2082: - rnorm - relative norm of the residual
2084: Notes:
2085: This routine is called by the KSP implementations.
2086: It does not typically need to be called by the user.
2088: Level: developer
2090: .seealso: KSPMonitorSet()
2091: @*/
2092: PetscErrorCode KSPMonitor(KSP ksp,PetscInt it,PetscReal rnorm)
2093: {
2094: PetscInt i, n = ksp->numbermonitors;
2098: for (i=0; i<n; i++) {
2099: (*ksp->monitor[i])(ksp,it,rnorm,ksp->monitorcontext[i]);
2100: }
2101: return(0);
2102: }
2104: /*@C
2105: KSPMonitorSet - Sets an ADDITIONAL function to be called at every iteration to monitor
2106: the residual/error etc.
2108: Logically Collective on ksp
2110: Input Parameters:
2111: + ksp - iterative context obtained from KSPCreate()
2112: . monitor - pointer to function (if this is NULL, it turns off monitoring
2113: . mctx - [optional] context for private data for the
2114: monitor routine (use NULL if no context is desired)
2115: - monitordestroy - [optional] routine that frees monitor context
2116: (may be NULL)
2118: Calling Sequence of monitor:
2119: $ monitor (KSP ksp, PetscInt it, PetscReal rnorm, void *mctx)
2121: + ksp - iterative context obtained from KSPCreate()
2122: . it - iteration number
2123: . rnorm - (estimated) 2-norm of (preconditioned) residual
2124: - mctx - optional monitoring context, as set by KSPMonitorSet()
2126: Options Database Keys:
2127: + -ksp_monitor - sets KSPMonitorResidual()
2128: . -ksp_monitor draw - sets KSPMonitorResidualDraw() and plots residual
2129: . -ksp_monitor draw::draw_lg - sets KSPMonitorResidualDrawLG() and plots residual
2130: . -ksp_monitor_pause_final - Pauses any graphics when the solve finishes (only works for internal monitors)
2131: . -ksp_monitor_true_residual - sets KSPMonitorTrueResidual()
2132: . -ksp_monitor_true_residual draw::draw_lg - sets KSPMonitorTrueResidualDrawLG() and plots residual
2133: . -ksp_monitor_max - sets KSPMonitorTrueResidualMax()
2134: . -ksp_monitor_singular_value - sets KSPMonitorSingularValue()
2135: - -ksp_monitor_cancel - cancels all monitors that have
2136: been hardwired into a code by
2137: calls to KSPMonitorSet(), but
2138: does not cancel those set via
2139: the options database.
2141: Notes:
2142: The default is to do nothing. To print the residual, or preconditioned
2143: residual if KSPSetNormType(ksp,KSP_NORM_PRECONDITIONED) was called, use
2144: KSPMonitorResidual() as the monitoring routine, with a ASCII viewer as the
2145: context.
2147: Several different monitoring routines may be set by calling
2148: KSPMonitorSet() multiple times; all will be called in the
2149: order in which they were set.
2151: Fortran Notes:
2152: Only a single monitor function can be set for each KSP object
2154: Level: beginner
2156: .seealso: KSPMonitorResidual(), KSPMonitorCancel(), KSP
2157: @*/
2158: PetscErrorCode KSPMonitorSet(KSP ksp,PetscErrorCode (*monitor)(KSP,PetscInt,PetscReal,void*),void *mctx,PetscErrorCode (*monitordestroy)(void**))
2159: {
2160: PetscInt i;
2162: PetscBool identical;
2166: for (i=0; i<ksp->numbermonitors;i++) {
2167: PetscMonitorCompare((PetscErrorCode (*)(void))monitor,mctx,monitordestroy,(PetscErrorCode (*)(void))ksp->monitor[i],ksp->monitorcontext[i],ksp->monitordestroy[i],&identical);
2168: if (identical) return(0);
2169: }
2170: if (ksp->numbermonitors >= MAXKSPMONITORS) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Too many KSP monitors set");
2171: ksp->monitor[ksp->numbermonitors] = monitor;
2172: ksp->monitordestroy[ksp->numbermonitors] = monitordestroy;
2173: ksp->monitorcontext[ksp->numbermonitors++] = (void*)mctx;
2174: return(0);
2175: }
2177: /*@
2178: KSPMonitorCancel - Clears all monitors for a KSP object.
2180: Logically Collective on ksp
2182: Input Parameters:
2183: . ksp - iterative context obtained from KSPCreate()
2185: Options Database Key:
2186: . -ksp_monitor_cancel - Cancels all monitors that have
2187: been hardwired into a code by calls to KSPMonitorSet(),
2188: but does not cancel those set via the options database.
2190: Level: intermediate
2192: .seealso: KSPMonitorResidual(), KSPMonitorSet(), KSP
2193: @*/
2194: PetscErrorCode KSPMonitorCancel(KSP ksp)
2195: {
2197: PetscInt i;
2201: for (i=0; i<ksp->numbermonitors; i++) {
2202: if (ksp->monitordestroy[i]) {
2203: (*ksp->monitordestroy[i])(&ksp->monitorcontext[i]);
2204: }
2205: }
2206: ksp->numbermonitors = 0;
2207: return(0);
2208: }
2210: /*@C
2211: KSPGetMonitorContext - Gets the monitoring context, as set by
2212: KSPMonitorSet() for the FIRST monitor only.
2214: Not Collective
2216: Input Parameter:
2217: . ksp - iterative context obtained from KSPCreate()
2219: Output Parameter:
2220: . ctx - monitoring context
2222: Level: intermediate
2224: .seealso: KSPMonitorResidual(), KSP
2225: @*/
2226: PetscErrorCode KSPGetMonitorContext(KSP ksp,void **ctx)
2227: {
2230: *ctx = (ksp->monitorcontext[0]);
2231: return(0);
2232: }
2234: /*@
2235: KSPSetResidualHistory - Sets the array used to hold the residual history.
2236: If set, this array will contain the residual norms computed at each
2237: iteration of the solver.
2239: Not Collective
2241: Input Parameters:
2242: + ksp - iterative context obtained from KSPCreate()
2243: . a - array to hold history
2244: . na - size of a
2245: - reset - PETSC_TRUE indicates the history counter is reset to zero
2246: for each new linear solve
2248: Level: advanced
2250: Notes:
2251: If provided, he array is NOT freed by PETSc so the user needs to keep track of it and destroy once the KSP object is destroyed.
2252: If 'a' is NULL then space is allocated for the history. If 'na' PETSC_DECIDE or PETSC_DEFAULT then a
2253: default array of length 10000 is allocated.
2255: .seealso: KSPGetResidualHistory(), KSP
2257: @*/
2258: PetscErrorCode KSPSetResidualHistory(KSP ksp,PetscReal a[],PetscInt na,PetscBool reset)
2259: {
2265: PetscFree(ksp->res_hist_alloc);
2266: if (na != PETSC_DECIDE && na != PETSC_DEFAULT && a) {
2267: ksp->res_hist = a;
2268: ksp->res_hist_max = na;
2269: } else {
2270: if (na != PETSC_DECIDE && na != PETSC_DEFAULT) ksp->res_hist_max = na;
2271: else ksp->res_hist_max = 10000; /* like default ksp->max_it */
2272: PetscCalloc1(ksp->res_hist_max,&ksp->res_hist_alloc);
2274: ksp->res_hist = ksp->res_hist_alloc;
2275: }
2276: ksp->res_hist_len = 0;
2277: ksp->res_hist_reset = reset;
2278: return(0);
2279: }
2281: /*@C
2282: KSPGetResidualHistory - Gets the array used to hold the residual history
2283: and the number of residuals it contains.
2285: Not Collective
2287: Input Parameter:
2288: . ksp - iterative context obtained from KSPCreate()
2290: Output Parameters:
2291: + a - pointer to array to hold history (or NULL)
2292: - na - number of used entries in a (or NULL)
2294: Level: advanced
2296: Notes:
2297: This array is borrowed and should not be freed by the caller.
2298: Can only be called after a KSPSetResidualHistory() otherwise a and na are set to zero
2300: The Fortran version of this routine has a calling sequence
2301: $ call KSPGetResidualHistory(KSP ksp, integer na, integer ierr)
2302: note that you have passed a Fortran array into KSPSetResidualHistory() and you need
2303: to access the residual values from this Fortran array you provided. Only the na (number of
2304: residual norms currently held) is set.
2306: .seealso: KSPSetResidualHistory(), KSP
2308: @*/
2309: PetscErrorCode KSPGetResidualHistory(KSP ksp, const PetscReal *a[],PetscInt *na)
2310: {
2313: if (a) *a = ksp->res_hist;
2314: if (na) *na = ksp->res_hist_len;
2315: return(0);
2316: }
2318: /*@
2319: KSPSetErrorHistory - Sets the array used to hold the error history. If set, this array will contain the error norms computed at each iteration of the solver.
2321: Not Collective
2323: Input Parameters:
2324: + ksp - iterative context obtained from KSPCreate()
2325: . a - array to hold history
2326: . na - size of a
2327: - reset - PETSC_TRUE indicates the history counter is reset to zero for each new linear solve
2329: Level: advanced
2331: Notes:
2332: If provided, the array is NOT freed by PETSc so the user needs to keep track of it and destroy once the KSP object is destroyed.
2333: If 'a' is NULL then space is allocated for the history. If 'na' PETSC_DECIDE or PETSC_DEFAULT then a default array of length 10000 is allocated.
2335: .seealso: KSPGetErrorHistory(), KSPSetResidualHistory(), KSP
2336: @*/
2337: PetscErrorCode KSPSetErrorHistory(KSP ksp, PetscReal a[], PetscInt na, PetscBool reset)
2338: {
2344: PetscFree(ksp->err_hist_alloc);
2345: if (na != PETSC_DECIDE && na != PETSC_DEFAULT && a) {
2346: ksp->err_hist = a;
2347: ksp->err_hist_max = na;
2348: } else {
2349: if (na != PETSC_DECIDE && na != PETSC_DEFAULT) ksp->err_hist_max = na;
2350: else ksp->err_hist_max = 10000; /* like default ksp->max_it */
2351: PetscCalloc1(ksp->err_hist_max, &ksp->err_hist_alloc);
2353: ksp->err_hist = ksp->err_hist_alloc;
2354: }
2355: ksp->err_hist_len = 0;
2356: ksp->err_hist_reset = reset;
2357: return(0);
2358: }
2360: /*@C
2361: KSPGetErrorHistory - Gets the array used to hold the error history and the number of residuals it contains.
2363: Not Collective
2365: Input Parameter:
2366: . ksp - iterative context obtained from KSPCreate()
2368: Output Parameters:
2369: + a - pointer to array to hold history (or NULL)
2370: - na - number of used entries in a (or NULL)
2372: Level: advanced
2374: Notes:
2375: This array is borrowed and should not be freed by the caller.
2376: Can only be called after a KSPSetErrorHistory() otherwise a and na are set to zero
2377: The Fortran version of this routine has a calling sequence
2378: $ call KSPGetErrorHistory(KSP ksp, integer na, integer ierr)
2379: note that you have passed a Fortran array into KSPSetErrorHistory() and you need
2380: to access the residual values from this Fortran array you provided. Only the na (number of
2381: residual norms currently held) is set.
2383: .seealso: KSPSetErrorHistory(), KSPGetResidualHistory(), KSP
2384: @*/
2385: PetscErrorCode KSPGetErrorHistory(KSP ksp, const PetscReal *a[], PetscInt *na)
2386: {
2389: if (a) *a = ksp->err_hist;
2390: if (na) *na = ksp->err_hist_len;
2391: return(0);
2392: }
2394: /*
2395: KSPComputeConvergenceRate - Compute the convergence rate for the iteration
2397: Not collective
2399: Input Parameter:
2400: . ksp - The KSP
2402: Output Parameters:
2403: + cr - The residual contraction rate
2404: . rRsq - The coefficient of determination, R^2, indicating the linearity of the data
2405: . ce - The error contraction rate
2406: - eRsq - The coefficient of determination, R^2, indicating the linearity of the data
2408: Note:
2409: Suppose that the residual is reduced linearly, $r_k = c^k r_0$, which means $log r_k = log r_0 + k log c$. After linear regression,
2410: the slope is $\log c$. The coefficient of determination is given by $1 - \frac{\sum_i (y_i - f(x_i))^2}{\sum_i (y_i - \bar y)}$,
2411: see also https://en.wikipedia.org/wiki/Coefficient_of_determination
2413: Level: advanced
2415: .seealso: KSPConvergedRateView()
2416: */
2417: PetscErrorCode KSPComputeConvergenceRate(KSP ksp, PetscReal *cr, PetscReal *rRsq, PetscReal *ce, PetscReal *eRsq)
2418: {
2419: PetscReal const *hist;
2420: PetscReal *x, *y, slope, intercept, mean = 0.0, var = 0.0, res = 0.0;
2421: PetscInt n, k;
2425: if (cr || rRsq) {
2426: KSPGetResidualHistory(ksp, &hist, &n);
2427: if (!n) {
2428: if (cr) *cr = 0.0;
2429: if (rRsq) *rRsq = -1.0;
2430: } else {
2431: PetscMalloc2(n, &x, n, &y);
2432: for (k = 0; k < n; ++k) {
2433: x[k] = k;
2434: y[k] = PetscLogReal(hist[k]);
2435: mean += y[k];
2436: }
2437: mean /= n;
2438: PetscLinearRegression(n, x, y, &slope, &intercept);
2439: for (k = 0; k < n; ++k) {
2440: res += PetscSqr(y[k] - (slope*x[k] + intercept));
2441: var += PetscSqr(y[k] - mean);
2442: }
2443: PetscFree2(x, y);
2444: if (cr) *cr = PetscExpReal(slope);
2445: if (rRsq) *rRsq = var < PETSC_MACHINE_EPSILON ? 0.0 : 1.0 - (res / var);
2446: }
2447: }
2448: if (ce || eRsq) {
2449: KSPGetErrorHistory(ksp, &hist, &n);
2450: if (!n) {
2451: if (ce) *ce = 0.0;
2452: if (eRsq) *eRsq = -1.0;
2453: } else {
2454: PetscMalloc2(n, &x, n, &y);
2455: for (k = 0; k < n; ++k) {
2456: x[k] = k;
2457: y[k] = PetscLogReal(hist[k]);
2458: mean += y[k];
2459: }
2460: mean /= n;
2461: PetscLinearRegression(n, x, y, &slope, &intercept);
2462: for (k = 0; k < n; ++k) {
2463: res += PetscSqr(y[k] - (slope*x[k] + intercept));
2464: var += PetscSqr(y[k] - mean);
2465: }
2466: PetscFree2(x, y);
2467: if (ce) *ce = PetscExpReal(slope);
2468: if (eRsq) *eRsq = var < PETSC_MACHINE_EPSILON ? 0.0 : 1.0 - (res / var);
2469: }
2470: }
2471: return(0);
2472: }
2474: /*@C
2475: KSPSetConvergenceTest - Sets the function to be used to determine
2476: convergence.
2478: Logically Collective on ksp
2480: Input Parameters:
2481: + ksp - iterative context obtained from KSPCreate()
2482: . converge - pointer to the function
2483: . cctx - context for private data for the convergence routine (may be null)
2484: - destroy - a routine for destroying the context (may be null)
2486: Calling sequence of converge:
2487: $ converge (KSP ksp, PetscInt it, PetscReal rnorm, KSPConvergedReason *reason,void *mctx)
2489: + ksp - iterative context obtained from KSPCreate()
2490: . it - iteration number
2491: . rnorm - (estimated) 2-norm of (preconditioned) residual
2492: . reason - the reason why it has converged or diverged
2493: - cctx - optional convergence context, as set by KSPSetConvergenceTest()
2496: Notes:
2497: Must be called after the KSP type has been set so put this after
2498: a call to KSPSetType(), or KSPSetFromOptions().
2500: The default convergence test, KSPConvergedDefault(), aborts if the
2501: residual grows to more than 10000 times the initial residual.
2503: The default is a combination of relative and absolute tolerances.
2504: The residual value that is tested may be an approximation; routines
2505: that need exact values should compute them.
2507: In the default PETSc convergence test, the precise values of reason
2508: are macros such as KSP_CONVERGED_RTOL, which are defined in petscksp.h.
2510: Level: advanced
2512: .seealso: KSPConvergedDefault(), KSPGetConvergenceContext(), KSPSetTolerances(), KSP, KSPGetConvergenceTest(), KSPGetAndClearConvergenceTest()
2513: @*/
2514: PetscErrorCode KSPSetConvergenceTest(KSP ksp,PetscErrorCode (*converge)(KSP,PetscInt,PetscReal,KSPConvergedReason*,void*),void *cctx,PetscErrorCode (*destroy)(void*))
2515: {
2520: if (ksp->convergeddestroy) {
2521: (*ksp->convergeddestroy)(ksp->cnvP);
2522: }
2523: ksp->converged = converge;
2524: ksp->convergeddestroy = destroy;
2525: ksp->cnvP = (void*)cctx;
2526: return(0);
2527: }
2529: /*@C
2530: KSPGetConvergenceTest - Gets the function to be used to determine
2531: convergence.
2533: Logically Collective on ksp
2535: Input Parameter:
2536: . ksp - iterative context obtained from KSPCreate()
2538: Output Parameter:
2539: + converge - pointer to convergence test function
2540: . cctx - context for private data for the convergence routine (may be null)
2541: - destroy - a routine for destroying the context (may be null)
2543: Calling sequence of converge:
2544: $ converge (KSP ksp, PetscInt it, PetscReal rnorm, KSPConvergedReason *reason,void *mctx)
2546: + ksp - iterative context obtained from KSPCreate()
2547: . it - iteration number
2548: . rnorm - (estimated) 2-norm of (preconditioned) residual
2549: . reason - the reason why it has converged or diverged
2550: - cctx - optional convergence context, as set by KSPSetConvergenceTest()
2552: Level: advanced
2554: .seealso: KSPConvergedDefault(), KSPGetConvergenceContext(), KSPSetTolerances(), KSP, KSPSetConvergenceTest(), KSPGetAndClearConvergenceTest()
2555: @*/
2556: PetscErrorCode KSPGetConvergenceTest(KSP ksp,PetscErrorCode (**converge)(KSP,PetscInt,PetscReal,KSPConvergedReason*,void*),void **cctx,PetscErrorCode (**destroy)(void*))
2557: {
2560: if (converge) *converge = ksp->converged;
2561: if (destroy) *destroy = ksp->convergeddestroy;
2562: if (cctx) *cctx = ksp->cnvP;
2563: return(0);
2564: }
2566: /*@C
2567: KSPGetAndClearConvergenceTest - Gets the function to be used to determine convergence. Removes the current test without calling destroy on the test context
2569: Logically Collective on ksp
2571: Input Parameter:
2572: . ksp - iterative context obtained from KSPCreate()
2574: Output Parameter:
2575: + converge - pointer to convergence test function
2576: . cctx - context for private data for the convergence routine
2577: - destroy - a routine for destroying the context
2579: Calling sequence of converge:
2580: $ converge (KSP ksp, PetscInt it, PetscReal rnorm, KSPConvergedReason *reason,void *mctx)
2582: + ksp - iterative context obtained from KSPCreate()
2583: . it - iteration number
2584: . rnorm - (estimated) 2-norm of (preconditioned) residual
2585: . reason - the reason why it has converged or diverged
2586: - cctx - optional convergence context, as set by KSPSetConvergenceTest()
2588: Level: advanced
2590: Notes: This is intended to be used to allow transferring the convergence test (and its context) to another testing object (for example another KSP) and then calling
2591: KSPSetConvergenceTest() on this original KSP. If you just called KSPGetConvergenceTest() followed by KSPSetConvergenceTest() the original context information
2592: would be destroyed and hence the transferred context would be invalid and trigger a crash on use
2594: .seealso: KSPConvergedDefault(), KSPGetConvergenceContext(), KSPSetTolerances(), KSP, KSPSetConvergenceTest(), KSPGetConvergenceTest()
2595: @*/
2596: PetscErrorCode KSPGetAndClearConvergenceTest(KSP ksp,PetscErrorCode (**converge)(KSP,PetscInt,PetscReal,KSPConvergedReason*,void*),void **cctx,PetscErrorCode (**destroy)(void*))
2597: {
2600: *converge = ksp->converged;
2601: *destroy = ksp->convergeddestroy;
2602: *cctx = ksp->cnvP;
2603: ksp->converged = NULL;
2604: ksp->cnvP = NULL;
2605: ksp->convergeddestroy = NULL;
2606: return(0);
2607: }
2609: /*@C
2610: KSPGetConvergenceContext - Gets the convergence context set with
2611: KSPSetConvergenceTest().
2613: Not Collective
2615: Input Parameter:
2616: . ksp - iterative context obtained from KSPCreate()
2618: Output Parameter:
2619: . ctx - monitoring context
2621: Level: advanced
2623: .seealso: KSPConvergedDefault(), KSPSetConvergenceTest(), KSP
2624: @*/
2625: PetscErrorCode KSPGetConvergenceContext(KSP ksp,void **ctx)
2626: {
2629: *ctx = ksp->cnvP;
2630: return(0);
2631: }
2633: /*@C
2634: KSPBuildSolution - Builds the approximate solution in a vector provided.
2635: This routine is NOT commonly needed (see KSPSolve()).
2637: Collective on ksp
2639: Input Parameter:
2640: . ctx - iterative context obtained from KSPCreate()
2642: Output Parameter:
2643: Provide exactly one of
2644: + v - location to stash solution.
2645: - V - the solution is returned in this location. This vector is created
2646: internally. This vector should NOT be destroyed by the user with
2647: VecDestroy().
2649: Notes:
2650: This routine can be used in one of two ways
2651: .vb
2652: KSPBuildSolution(ksp,NULL,&V);
2653: or
2654: KSPBuildSolution(ksp,v,NULL); or KSPBuildSolution(ksp,v,&v);
2655: .ve
2656: In the first case an internal vector is allocated to store the solution
2657: (the user cannot destroy this vector). In the second case the solution
2658: is generated in the vector that the user provides. Note that for certain
2659: methods, such as KSPCG, the second case requires a copy of the solution,
2660: while in the first case the call is essentially free since it simply
2661: returns the vector where the solution already is stored. For some methods
2662: like GMRES this is a reasonably expensive operation and should only be
2663: used in truly needed.
2665: Level: advanced
2667: .seealso: KSPGetSolution(), KSPBuildResidual(), KSP
2668: @*/
2669: PetscErrorCode KSPBuildSolution(KSP ksp,Vec v,Vec *V)
2670: {
2675: if (!V && !v) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_WRONG,"Must provide either v or V");
2676: if (!V) V = &v;
2677: (*ksp->ops->buildsolution)(ksp,v,V);
2678: return(0);
2679: }
2681: /*@C
2682: KSPBuildResidual - Builds the residual in a vector provided.
2684: Collective on ksp
2686: Input Parameter:
2687: . ksp - iterative context obtained from KSPCreate()
2689: Output Parameters:
2690: + v - optional location to stash residual. If v is not provided,
2691: then a location is generated.
2692: . t - work vector. If not provided then one is generated.
2693: - V - the residual
2695: Notes:
2696: Regardless of whether or not v is provided, the residual is
2697: returned in V.
2699: Level: advanced
2701: .seealso: KSPBuildSolution()
2702: @*/
2703: PetscErrorCode KSPBuildResidual(KSP ksp,Vec t,Vec v,Vec *V)
2704: {
2706: PetscBool flag = PETSC_FALSE;
2707: Vec w = v,tt = t;
2711: if (!w) {
2712: VecDuplicate(ksp->vec_rhs,&w);
2713: PetscLogObjectParent((PetscObject)ksp,(PetscObject)w);
2714: }
2715: if (!tt) {
2716: VecDuplicate(ksp->vec_sol,&tt); flag = PETSC_TRUE;
2717: PetscLogObjectParent((PetscObject)ksp,(PetscObject)tt);
2718: }
2719: (*ksp->ops->buildresidual)(ksp,tt,w,V);
2720: if (flag) {VecDestroy(&tt);}
2721: return(0);
2722: }
2724: /*@
2725: KSPSetDiagonalScale - Tells KSP to symmetrically diagonally scale the system
2726: before solving. This actually CHANGES the matrix (and right hand side).
2728: Logically Collective on ksp
2730: Input Parameter:
2731: + ksp - the KSP context
2732: - scale - PETSC_TRUE or PETSC_FALSE
2734: Options Database Key:
2735: + -ksp_diagonal_scale -
2736: - -ksp_diagonal_scale_fix - scale the matrix back AFTER the solve
2739: Notes:
2740: Scales the matrix by D^(-1/2) A D^(-1/2) [D^(1/2) x ] = D^(-1/2) b
2741: where D_{ii} is 1/abs(A_{ii}) unless A_{ii} is zero and then it is 1.
2743: BE CAREFUL with this routine: it actually scales the matrix and right
2744: hand side that define the system. After the system is solved the matrix
2745: and right hand side remain scaled unless you use KSPSetDiagonalScaleFix()
2747: This should NOT be used within the SNES solves if you are using a line
2748: search.
2750: If you use this with the PCType Eisenstat preconditioner than you can
2751: use the PCEisenstatSetNoDiagonalScaling() option, or -pc_eisenstat_no_diagonal_scaling
2752: to save some unneeded, redundant flops.
2754: Level: intermediate
2756: .seealso: KSPGetDiagonalScale(), KSPSetDiagonalScaleFix(), KSP
2757: @*/
2758: PetscErrorCode KSPSetDiagonalScale(KSP ksp,PetscBool scale)
2759: {
2763: ksp->dscale = scale;
2764: return(0);
2765: }
2767: /*@
2768: KSPGetDiagonalScale - Checks if KSP solver scales the matrix and
2769: right hand side
2771: Not Collective
2773: Input Parameter:
2774: . ksp - the KSP context
2776: Output Parameter:
2777: . scale - PETSC_TRUE or PETSC_FALSE
2779: Notes:
2780: BE CAREFUL with this routine: it actually scales the matrix and right
2781: hand side that define the system. After the system is solved the matrix
2782: and right hand side remain scaled unless you use KSPSetDiagonalScaleFix()
2784: Level: intermediate
2786: .seealso: KSPSetDiagonalScale(), KSPSetDiagonalScaleFix(), KSP
2787: @*/
2788: PetscErrorCode KSPGetDiagonalScale(KSP ksp,PetscBool *scale)
2789: {
2793: *scale = ksp->dscale;
2794: return(0);
2795: }
2797: /*@
2798: KSPSetDiagonalScaleFix - Tells KSP to diagonally scale the system
2799: back after solving.
2801: Logically Collective on ksp
2803: Input Parameter:
2804: + ksp - the KSP context
2805: - fix - PETSC_TRUE to scale back after the system solve, PETSC_FALSE to not
2806: rescale (default)
2808: Notes:
2809: Must be called after KSPSetDiagonalScale()
2811: Using this will slow things down, because it rescales the matrix before and
2812: after each linear solve. This is intended mainly for testing to allow one
2813: to easily get back the original system to make sure the solution computed is
2814: accurate enough.
2816: Level: intermediate
2818: .seealso: KSPGetDiagonalScale(), KSPSetDiagonalScale(), KSPGetDiagonalScaleFix(), KSP
2819: @*/
2820: PetscErrorCode KSPSetDiagonalScaleFix(KSP ksp,PetscBool fix)
2821: {
2825: ksp->dscalefix = fix;
2826: return(0);
2827: }
2829: /*@
2830: KSPGetDiagonalScaleFix - Determines if KSP diagonally scales the system
2831: back after solving.
2833: Not Collective
2835: Input Parameter:
2836: . ksp - the KSP context
2838: Output Parameter:
2839: . fix - PETSC_TRUE to scale back after the system solve, PETSC_FALSE to not
2840: rescale (default)
2842: Notes:
2843: Must be called after KSPSetDiagonalScale()
2845: If PETSC_TRUE will slow things down, because it rescales the matrix before and
2846: after each linear solve. This is intended mainly for testing to allow one
2847: to easily get back the original system to make sure the solution computed is
2848: accurate enough.
2850: Level: intermediate
2852: .seealso: KSPGetDiagonalScale(), KSPSetDiagonalScale(), KSPSetDiagonalScaleFix(), KSP
2853: @*/
2854: PetscErrorCode KSPGetDiagonalScaleFix(KSP ksp,PetscBool *fix)
2855: {
2859: *fix = ksp->dscalefix;
2860: return(0);
2861: }
2863: /*@C
2864: KSPSetComputeOperators - set routine to compute the linear operators
2866: Logically Collective
2868: Input Arguments:
2869: + ksp - the KSP context
2870: . func - function to compute the operators
2871: - ctx - optional context
2873: Calling sequence of func:
2874: $ func(KSP ksp,Mat A,Mat B,void *ctx)
2876: + ksp - the KSP context
2877: . A - the linear operator
2878: . B - preconditioning matrix
2879: - ctx - optional user-provided context
2881: Notes:
2882: The user provided func() will be called automatically at the very next call to KSPSolve(). It will not be called at future KSPSolve() calls
2883: unless either KSPSetComputeOperators() or KSPSetOperators() is called before that KSPSolve() is called.
2885: To reuse the same preconditioner for the next KSPSolve() and not compute a new one based on the most recently computed matrix call KSPSetReusePreconditioner()
2887: Level: beginner
2889: .seealso: KSPSetOperators(), KSPSetComputeRHS(), DMKSPSetComputeOperators(), KSPSetComputeInitialGuess()
2890: @*/
2891: PetscErrorCode KSPSetComputeOperators(KSP ksp,PetscErrorCode (*func)(KSP,Mat,Mat,void*),void *ctx)
2892: {
2894: DM dm;
2898: KSPGetDM(ksp,&dm);
2899: DMKSPSetComputeOperators(dm,func,ctx);
2900: if (ksp->setupstage == KSP_SETUP_NEWRHS) ksp->setupstage = KSP_SETUP_NEWMATRIX;
2901: return(0);
2902: }
2904: /*@C
2905: KSPSetComputeRHS - set routine to compute the right hand side of the linear system
2907: Logically Collective
2909: Input Arguments:
2910: + ksp - the KSP context
2911: . func - function to compute the right hand side
2912: - ctx - optional context
2914: Calling sequence of func:
2915: $ func(KSP ksp,Vec b,void *ctx)
2917: + ksp - the KSP context
2918: . b - right hand side of linear system
2919: - ctx - optional user-provided context
2921: Notes:
2922: The routine you provide will be called EACH you call KSPSolve() to prepare the new right hand side for that solve
2924: Level: beginner
2926: .seealso: KSPSolve(), DMKSPSetComputeRHS(), KSPSetComputeOperators()
2927: @*/
2928: PetscErrorCode KSPSetComputeRHS(KSP ksp,PetscErrorCode (*func)(KSP,Vec,void*),void *ctx)
2929: {
2931: DM dm;
2935: KSPGetDM(ksp,&dm);
2936: DMKSPSetComputeRHS(dm,func,ctx);
2937: return(0);
2938: }
2940: /*@C
2941: KSPSetComputeInitialGuess - set routine to compute the initial guess of the linear system
2943: Logically Collective
2945: Input Arguments:
2946: + ksp - the KSP context
2947: . func - function to compute the initial guess
2948: - ctx - optional context
2950: Calling sequence of func:
2951: $ func(KSP ksp,Vec x,void *ctx)
2953: + ksp - the KSP context
2954: . x - solution vector
2955: - ctx - optional user-provided context
2957: Notes: This should only be used in conjunction with KSPSetComputeRHS(), KSPSetComputeOperators(), otherwise
2958: call KSPSetInitialGuessNonzero() and set the initial guess values in the solution vector passed to KSPSolve().
2960: Level: beginner
2962: .seealso: KSPSolve(), KSPSetComputeRHS(), KSPSetComputeOperators(), DMKSPSetComputeInitialGuess()
2963: @*/
2964: PetscErrorCode KSPSetComputeInitialGuess(KSP ksp,PetscErrorCode (*func)(KSP,Vec,void*),void *ctx)
2965: {
2967: DM dm;
2971: KSPGetDM(ksp,&dm);
2972: DMKSPSetComputeInitialGuess(dm,func,ctx);
2973: return(0);
2974: }
2976: /*@
2977: KSPSetUseExplicitTranspose - Determines if transpose the system explicitly
2978: in KSPSolveTranspose.
2980: Logically Collective on ksp
2982: Input Parameter:
2983: . ksp - the KSP context
2985: Output Parameter:
2986: . flg - PETSC_TRUE to transpose the system in KSPSolveTranspose, PETSC_FALSE to not
2987: transpose (default)
2989: Level: advanced
2991: .seealso: KSPSolveTranspose(), KSP
2992: @*/
2993: PetscErrorCode KSPSetUseExplicitTranspose(KSP ksp,PetscBool flg)
2994: {
2997: ksp->transpose.use_explicittranspose = flg;
2998: return(0);
2999: }