Actual source code: itfunc.c

  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),PETSC_ERR_ARG_WRONGSTATE,"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),PETSC_ERR_ARG_WRONGSTATE,"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

146:    Input/Output Parameter:
147: .  nrit  - number of (harmonic) Ritz pairs to compute; on output,
148:            actual number of computed (harmonic) Ritz pairs

150:    Output Parameters:
151: +  S     - multidimensional vector with Ritz vectors
152: .  tetar - real part of the Ritz values
153: -  tetai - imaginary part of the Ritz values

155:    Notes:
156:    -For GMRES, the (harmonic) Ritz pairs are computed from the Hessenberg matrix obtained during
157:    the last complete cycle, or obtained at the end of the solution if the method is stopped before
158:    a restart. Then, the number of actual (harmonic) Ritz pairs computed is less or equal to the restart
159:    parameter for GMRES if a complete cycle has been performed or less or equal to the number of GMRES
160:    iterations.
161:    -Moreover, for real matrices, the (harmonic) Ritz pairs are possibly complex-valued. In such a case,
162:    the routine selects the complex (harmonic) Ritz value and its conjugate, and two successive columns of S
163:    are equal to the real and the imaginary parts of the associated vectors.
164:    -the (harmonic) Ritz pairs are given in order of increasing (harmonic) Ritz values in modulus
165:    -this is currently not implemented when PETSc is built with complex numbers

167:    One must call KSPSetComputeRitz() before calling KSPSetUp()
168:    in order for this routine to work correctly.

170:    Level: advanced

172: .seealso: KSPSetComputeRitz(), KSP
173: @*/
174: PetscErrorCode  KSPComputeRitz(KSP ksp,PetscBool ritz,PetscBool small,PetscInt *nrit,Vec S[],PetscReal tetar[],PetscReal tetai[])
175: {

180:   if (!ksp->calc_ritz) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_WRONGSTATE,"Ritz pairs not requested before KSPSetUp()");
181:   if (ksp->ops->computeritz) {(*ksp->ops->computeritz)(ksp,ritz,small,nrit,S,tetar,tetai);}
182:   return(0);
183: }
184: /*@
185:    KSPSetUpOnBlocks - Sets up the preconditioner for each block in
186:    the block Jacobi, block Gauss-Seidel, and overlapping Schwarz
187:    methods.

189:    Collective on ksp

191:    Input Parameter:
192: .  ksp - the KSP context

194:    Notes:
195:    KSPSetUpOnBlocks() is a routine that the user can optinally call for
196:    more precise profiling (via -log_view) of the setup phase for these
197:    block preconditioners.  If the user does not call KSPSetUpOnBlocks(),
198:    it will automatically be called from within KSPSolve().

200:    Calling KSPSetUpOnBlocks() is the same as calling PCSetUpOnBlocks()
201:    on the PC context within the KSP context.

203:    Level: advanced

205: .seealso: PCSetUpOnBlocks(), KSPSetUp(), PCSetUp(), KSP
206: @*/
207: PetscErrorCode  KSPSetUpOnBlocks(KSP ksp)
208: {
209:   PC             pc;
211:   PCFailedReason pcreason;

215:   KSPGetPC(ksp,&pc);
216:   PCSetUpOnBlocks(pc);
217:   PCGetFailedReasonRank(pc,&pcreason);
218:   /* TODO: this code was wrong and is still wrong, there is no way to propagate the failure to all processes; their is no code to handle a ksp->reason on only some ranks */
219:   if (pcreason) {
220:     ksp->reason = KSP_DIVERGED_PC_FAILED;
221:   }
222:   return(0);
223: }

225: /*@
226:    KSPSetReusePreconditioner - reuse the current preconditioner, do not construct a new one even if the operator changes

228:    Collective on ksp

230:    Input Parameters:
231: +  ksp   - iterative context obtained from KSPCreate()
232: -  flag - PETSC_TRUE to reuse the current preconditioner

234:    Level: intermediate

236: .seealso: KSPCreate(), KSPSolve(), KSPDestroy(), PCSetReusePreconditioner(), KSP
237: @*/
238: PetscErrorCode  KSPSetReusePreconditioner(KSP ksp,PetscBool flag)
239: {
240:   PC             pc;

245:   KSPGetPC(ksp,&pc);
246:   PCSetReusePreconditioner(pc,flag);
247:   return(0);
248: }

250: /*@
251:    KSPGetReusePreconditioner - Determines if the KSP reuses the current preconditioner even if the operator in the preconditioner has changed.

253:    Collective on ksp

255:    Input Parameters:
256: .  ksp   - iterative context obtained from KSPCreate()

258:    Output Parameters:
259: .  flag - the boolean flag

261:    Level: intermediate

263: .seealso: KSPCreate(), KSPSolve(), KSPDestroy(), KSPSetReusePreconditioner(), KSP
264: @*/
265: PetscErrorCode  KSPGetReusePreconditioner(KSP ksp,PetscBool *flag)
266: {

272:   *flag = PETSC_FALSE;
273:   if (ksp->pc) {
274:     PCGetReusePreconditioner(ksp->pc,flag);
275:   }
276:   return(0);
277: }

279: /*@
280:    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

282:    Collective on ksp

284:    Input Parameters:
285: +  ksp   - iterative context obtained from KSPCreate()
286: -  flag - PETSC_TRUE to skip calling the PCSetFromOptions()

288:    Level: intermediate

290: .seealso: KSPCreate(), KSPSolve(), KSPDestroy(), PCSetReusePreconditioner(), KSP
291: @*/
292: PetscErrorCode  KSPSetSkipPCSetFromOptions(KSP ksp,PetscBool flag)
293: {
296:   ksp->skippcsetfromoptions = flag;
297:   return(0);
298: }

300: /*@
301:    KSPSetUp - Sets up the internal data structures for the
302:    later use of an iterative solver.

304:    Collective on ksp

306:    Input Parameter:
307: .  ksp   - iterative context obtained from KSPCreate()

309:    Level: developer

311: .seealso: KSPCreate(), KSPSolve(), KSPDestroy(), KSP
312: @*/
313: PetscErrorCode KSPSetUp(KSP ksp)
314: {
316:   Mat            A,B;
317:   Mat            mat,pmat;
318:   MatNullSpace   nullsp;
319:   PCFailedReason pcreason;


324:   /* reset the convergence flag from the previous solves */
325:   ksp->reason = KSP_CONVERGED_ITERATING;

327:   if (!((PetscObject)ksp)->type_name) {
328:     KSPSetType(ksp,KSPGMRES);
329:   }
330:   KSPSetUpNorms_Private(ksp,PETSC_TRUE,&ksp->normtype,&ksp->pc_side);

332:   if (ksp->dmActive && !ksp->setupstage) {
333:     /* first time in so build matrix and vector data structures using DM */
334:     if (!ksp->vec_rhs) {DMCreateGlobalVector(ksp->dm,&ksp->vec_rhs);}
335:     if (!ksp->vec_sol) {DMCreateGlobalVector(ksp->dm,&ksp->vec_sol);}
336:     DMCreateMatrix(ksp->dm,&A);
337:     KSPSetOperators(ksp,A,A);
338:     PetscObjectDereference((PetscObject)A);
339:   }

341:   if (ksp->dmActive) {
342:     DMKSP kdm;
343:     DMGetDMKSP(ksp->dm,&kdm);

345:     if (kdm->ops->computeinitialguess && ksp->setupstage != KSP_SETUP_NEWRHS) {
346:       /* only computes initial guess the first time through */
347:       (*kdm->ops->computeinitialguess)(ksp,ksp->vec_sol,kdm->initialguessctx);
348:       KSPSetInitialGuessNonzero(ksp,PETSC_TRUE);
349:     }
350:     if (kdm->ops->computerhs) {
351:       (*kdm->ops->computerhs)(ksp,ksp->vec_rhs,kdm->rhsctx);
352:     }

354:     if (ksp->setupstage != KSP_SETUP_NEWRHS) {
355:       if (kdm->ops->computeoperators) {
356:         KSPGetOperators(ksp,&A,&B);
357:         (*kdm->ops->computeoperators)(ksp,A,B,kdm->operatorsctx);
358:       } else SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_WRONGSTATE,"You called KSPSetDM() but did not use DMKSPSetComputeOperators() or KSPSetDMActive(ksp,PETSC_FALSE);");
359:     }
360:   }

362:   if (ksp->setupstage == KSP_SETUP_NEWRHS) return(0);
363:   PetscLogEventBegin(KSP_SetUp,ksp,ksp->vec_rhs,ksp->vec_sol,0);

365:   switch (ksp->setupstage) {
366:   case KSP_SETUP_NEW:
367:     (*ksp->ops->setup)(ksp);
368:     break;
369:   case KSP_SETUP_NEWMATRIX: {   /* This should be replaced with a more general mechanism */
370:     if (ksp->setupnewmatrix) {
371:       (*ksp->ops->setup)(ksp);
372:     }
373:   } break;
374:   default: break;
375:   }

377:   if (!ksp->pc) {KSPGetPC(ksp,&ksp->pc);}
378:   PCGetOperators(ksp->pc,&mat,&pmat);
379:   /* scale the matrix if requested */
380:   if (ksp->dscale) {
381:     PetscScalar *xx;
382:     PetscInt    i,n;
383:     PetscBool   zeroflag = PETSC_FALSE;
384:     if (!ksp->pc) {KSPGetPC(ksp,&ksp->pc);}
385:     if (!ksp->diagonal) { /* allocate vector to hold diagonal */
386:       MatCreateVecs(pmat,&ksp->diagonal,NULL);
387:     }
388:     MatGetDiagonal(pmat,ksp->diagonal);
389:     VecGetLocalSize(ksp->diagonal,&n);
390:     VecGetArray(ksp->diagonal,&xx);
391:     for (i=0; i<n; i++) {
392:       if (xx[i] != 0.0) xx[i] = 1.0/PetscSqrtReal(PetscAbsScalar(xx[i]));
393:       else {
394:         xx[i]    = 1.0;
395:         zeroflag = PETSC_TRUE;
396:       }
397:     }
398:     VecRestoreArray(ksp->diagonal,&xx);
399:     if (zeroflag) {
400:       PetscInfo(ksp,"Zero detected in diagonal of matrix, using 1 at those locations\n");
401:     }
402:     MatDiagonalScale(pmat,ksp->diagonal,ksp->diagonal);
403:     if (mat != pmat) {MatDiagonalScale(mat,ksp->diagonal,ksp->diagonal);}
404:     ksp->dscalefix2 = PETSC_FALSE;
405:   }
406:   PetscLogEventEnd(KSP_SetUp,ksp,ksp->vec_rhs,ksp->vec_sol,0);
407:   PCSetErrorIfFailure(ksp->pc,ksp->errorifnotconverged);
408:   PCSetUp(ksp->pc);
409:   PCGetFailedReasonRank(ksp->pc,&pcreason);
410:   /* TODO: this code was wrong and is still wrong, there is no way to propagate the failure to all processes; their is no code to handle a ksp->reason on only some ranks */
411:   if (pcreason) {
412:     ksp->reason = KSP_DIVERGED_PC_FAILED;
413:   }

415:   MatGetNullSpace(mat,&nullsp);
416:   if (nullsp) {
417:     PetscBool test = PETSC_FALSE;
418:     PetscOptionsGetBool(((PetscObject)ksp)->options,((PetscObject)ksp)->prefix,"-ksp_test_null_space",&test,NULL);
419:     if (test) {
420:       MatNullSpaceTest(nullsp,mat,NULL);
421:     }
422:   }
423:   ksp->setupstage = KSP_SETUP_NEWRHS;
424:   return(0);
425: }

427: /*@C
428:    KSPConvergedReasonView - Displays the reason a KSP solve converged or diverged to a viewer

430:    Collective on ksp

432:    Parameter:
433: +  ksp - iterative context obtained from KSPCreate()
434: -  viewer - the viewer to display the reason

436:    Options Database Keys:
437: +  -ksp_converged_reason - print reason for converged or diverged, also prints number of iterations
438: -  -ksp_converged_reason ::failed - only print reason and number of iterations when diverged

440:    Notes:
441:      To change the format of the output call PetscViewerPushFormat(viewer,format) before this call. Use PETSC_VIEWER_DEFAULT for the default,
442:      use PETSC_VIEWER_FAILED to only display a reason if it fails.

444:    Level: beginner

446: .seealso: KSPCreate(), KSPSetUp(), KSPDestroy(), KSPSetTolerances(), KSPConvergedDefault(),
447:           KSPSolveTranspose(), KSPGetIterationNumber(), KSP, KSPGetConvergedReason(), PetscViewerPushFormat(), PetscViewerPopFormat()
448: @*/
449: PetscErrorCode KSPConvergedReasonView(KSP ksp, PetscViewer viewer)
450: {
451:   PetscErrorCode    ierr;
452:   PetscBool         isAscii;
453:   PetscViewerFormat format;

456:   if (!viewer) viewer = PETSC_VIEWER_STDOUT_(PetscObjectComm((PetscObject)ksp));
457:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isAscii);
458:   if (isAscii) {
459:     PetscViewerGetFormat(viewer, &format);
460:     PetscViewerASCIIAddTab(viewer,((PetscObject)ksp)->tablevel);
461:     if (ksp->reason > 0 && format != PETSC_VIEWER_FAILED) {
462:       if (((PetscObject) ksp)->prefix) {
463:         PetscViewerASCIIPrintf(viewer,"Linear %s solve converged due to %s iterations %D\n",((PetscObject) ksp)->prefix,KSPConvergedReasons[ksp->reason],ksp->its);
464:       } else {
465:         PetscViewerASCIIPrintf(viewer,"Linear solve converged due to %s iterations %D\n",KSPConvergedReasons[ksp->reason],ksp->its);
466:       }
467:     } else if (ksp->reason <= 0) {
468:       if (((PetscObject) ksp)->prefix) {
469:         PetscViewerASCIIPrintf(viewer,"Linear %s solve did not converge due to %s iterations %D\n",((PetscObject) ksp)->prefix,KSPConvergedReasons[ksp->reason],ksp->its);
470:       } else {
471:         PetscViewerASCIIPrintf(viewer,"Linear solve did not converge due to %s iterations %D\n",KSPConvergedReasons[ksp->reason],ksp->its);
472:       }
473:       if (ksp->reason == KSP_DIVERGED_PC_FAILED) {
474:         PCFailedReason reason;
475:         PCGetFailedReason(ksp->pc,&reason);
476:         PetscViewerASCIIPrintf(viewer,"               PC failed due to %s \n",PCFailedReasons[reason]);
477:       }
478:     }
479:     PetscViewerASCIISubtractTab(viewer,((PetscObject)ksp)->tablevel);
480:   }
481:   return(0);
482: }

484: /*@C
485:    KSPConvergedReasonViewSet - Sets an ADDITIONAL function that is to be used at the
486:     end of the linear solver to display the convergence reason of the linear solver.

488:    Logically Collective on KSP

490:    Input Parameters:
491: +  ksp - the KSP context
492: .  f - the ksp converged reason view function
493: .  vctx - [optional] user-defined context for private data for the
494:           ksp converged reason view routine (use NULL if no context is desired)
495: -  reasonviewdestroy - [optional] routine that frees reasonview context
496:           (may be NULL)

498:    Options Database Keys:
499: +    -ksp_converged_reason        - sets a default KSPConvergedReasonView()
500: -    -ksp_converged_reason_view_cancel - cancels all converged reason viewers that have
501:                             been hardwired into a code by
502:                             calls to KSPConvergedReasonViewSet(), but
503:                             does not cancel those set via
504:                             the options database.

506:    Notes:
507:    Several different converged reason view routines may be set by calling
508:    KSPConvergedReasonViewSet() multiple times; all will be called in the
509:    order in which they were set.

511:    Level: intermediate

513: .seealso: KSPConvergedReasonView(), KSPConvergedReasonViewCancel()
514: @*/
515: PetscErrorCode  KSPConvergedReasonViewSet(KSP ksp,PetscErrorCode (*f)(KSP,void*),void *vctx,PetscErrorCode (*reasonviewdestroy)(void**))
516: {
517:   PetscInt       i;
519:   PetscBool      identical;

523:   for (i=0; i<ksp->numberreasonviews;i++) {
524:     PetscMonitorCompare((PetscErrorCode (*)(void))f,vctx,reasonviewdestroy,(PetscErrorCode (*)(void))ksp->reasonview[i],ksp->reasonviewcontext[i],ksp->reasonviewdestroy[i],&identical);
525:     if (identical) return(0);
526:   }
527:   if (ksp->numberreasonviews >= MAXKSPREASONVIEWS) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Too many KSP reasonview set");
528:   ksp->reasonview[ksp->numberreasonviews]          = f;
529:   ksp->reasonviewdestroy[ksp->numberreasonviews]   = reasonviewdestroy;
530:   ksp->reasonviewcontext[ksp->numberreasonviews++] = (void*)vctx;
531:   return(0);
532: }

534: /*@
535:    KSPConvergedReasonViewCancel - Clears all the reasonview functions for a KSP object.

537:    Collective on KSP

539:    Input Parameter:
540: .  ksp - iterative context obtained from KSPCreate()

542:    Level: intermediate

544: .seealso: KSPCreate(), KSPDestroy(), KSPReset()
545: @*/
546: PetscErrorCode  KSPConvergedReasonViewCancel(KSP ksp)
547: {
549:   PetscInt       i;

553:   for (i=0; i<ksp->numberreasonviews; i++) {
554:     if (ksp->reasonviewdestroy[i]) {
555:       (*ksp->reasonviewdestroy[i])(&ksp->reasonviewcontext[i]);
556:     }
557:   }
558:   ksp->numberreasonviews = 0;
559:   return(0);
560: }

562: /*@
563:   KSPConvergedReasonViewFromOptions - Processes command line options to determine if/how a KSPReason is to be viewed.

565:   Collective on ksp

567:   Input Parameters:
568: . ksp   - the KSP object

570:   Level: intermediate

572: .seealso: KSPConvergedReasonView()
573: @*/
574: PetscErrorCode KSPConvergedReasonViewFromOptions(KSP ksp)
575: {
576:   PetscViewer       viewer;
577:   PetscBool         flg;
578:   PetscViewerFormat format;
579:   PetscErrorCode    ierr;
580:   PetscInt          i;


584:   /* Call all user-provided reason review routines */
585:   for (i=0; i<ksp->numberreasonviews; i++) {
586:     (*ksp->reasonview[i])(ksp,ksp->reasonviewcontext[i]);
587:   }

589:   /* Call the default PETSc routine */
590:   PetscOptionsGetViewer(PetscObjectComm((PetscObject)ksp),((PetscObject)ksp)->options,((PetscObject)ksp)->prefix,"-ksp_converged_reason",&viewer,&format,&flg);
591:   if (flg) {
592:     PetscViewerPushFormat(viewer,format);
593:     KSPConvergedReasonView(ksp, viewer);
594:     PetscViewerPopFormat(viewer);
595:     PetscViewerDestroy(&viewer);
596:   }
597:   return(0);
598: }

600: /*@C
601:   KSPConvergedRateView - Displays the reason a KSP solve converged or diverged to a viewer

603:   Collective on ksp

605:   Input Parameters:
606: +  ksp    - iterative context obtained from KSPCreate()
607: -  viewer - the viewer to display the reason

609:   Options Database Keys:
610: . -ksp_converged_rate - print reason for convergence or divergence and the convergence rate (or 0.0 for divergence)

612:   Notes:
613:   To change the format of the output, call PetscViewerPushFormat(viewer,format) before this call.

615:   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,
616:   the slope is $\log c$. The coefficient of determination is given by $1 - \frac{\sum_i (y_i - f(x_i))^2}{\sum_i (y_i - \bar y)}$,
617:   see also https://en.wikipedia.org/wiki/Coefficient_of_determination

619:   Level: intermediate

621: .seealso: KSPConvergedReasonView(), KSPGetConvergedRate(), KSPSetTolerances(), KSPConvergedDefault()
622: @*/
623: PetscErrorCode KSPConvergedRateView(KSP ksp, PetscViewer viewer)
624: {
625:   PetscViewerFormat format;
626:   PetscBool         isAscii;
627:   PetscReal         rrate, rRsq, erate = 0.0, eRsq = 0.0;
628:   PetscInt          its;
629:   const char       *prefix, *reason = KSPConvergedReasons[ksp->reason];
630:   PetscErrorCode    ierr;

633:   KSPGetOptionsPrefix(ksp, &prefix);
634:   KSPGetIterationNumber(ksp, &its);
635:   KSPComputeConvergenceRate(ksp, &rrate, &rRsq, &erate, &eRsq);
636:   if (!viewer) viewer = PETSC_VIEWER_STDOUT_(PetscObjectComm((PetscObject)ksp));
637:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isAscii);
638:   if (isAscii) {
639:     PetscViewerGetFormat(viewer, &format);
640:     PetscViewerASCIIAddTab(viewer,((PetscObject)ksp)->tablevel);
641:     if (ksp->reason > 0) {
642:       if (prefix) {PetscViewerASCIIPrintf(viewer, "Linear %s solve converged due to %s iterations %D", prefix, reason, its);}
643:       else        {PetscViewerASCIIPrintf(viewer, "Linear solve converged due to %s iterations %D", reason, its);}
644:       PetscViewerASCIIUseTabs(viewer, PETSC_FALSE);
645:       if (rRsq >= 0.0) {PetscViewerASCIIPrintf(viewer, " res rate %g R^2 %g", rrate, rRsq);}
646:       if (eRsq >= 0.0) {PetscViewerASCIIPrintf(viewer, " error rate %g R^2 %g", erate, eRsq);}
647:       PetscViewerASCIIPrintf(viewer, "\n");
648:       PetscViewerASCIIUseTabs(viewer, PETSC_TRUE);
649:     } else if (ksp->reason <= 0) {
650:       if (prefix) {PetscViewerASCIIPrintf(viewer, "Linear %s solve did not converge due to %s iterations %D", prefix, reason, its);}
651:       else        {PetscViewerASCIIPrintf(viewer, "Linear solve did not converge due to %s iterations %D", reason, its);}
652:       PetscViewerASCIIUseTabs(viewer, PETSC_FALSE);
653:       if (rRsq >= 0.0) {PetscViewerASCIIPrintf(viewer, " res rate %g R^2 %g", rrate, rRsq);}
654:       if (eRsq >= 0.0) {PetscViewerASCIIPrintf(viewer, " error rate %g R^2 %g", erate, eRsq);}
655:       PetscViewerASCIIPrintf(viewer, "\n");
656:       PetscViewerASCIIUseTabs(viewer, PETSC_TRUE);
657:       if (ksp->reason == KSP_DIVERGED_PC_FAILED) {
658:         PCFailedReason reason;
659:         PCGetFailedReason(ksp->pc,&reason);
660:         PetscViewerASCIIPrintf(viewer,"               PC failed due to %s \n",PCFailedReasons[reason]);
661:       }
662:     }
663:     PetscViewerASCIISubtractTab(viewer,((PetscObject)ksp)->tablevel);
664:   }
665:   return(0);
666: }

668: #include <petscdraw.h>

670: static PetscErrorCode KSPViewEigenvalues_Internal(KSP ksp, PetscBool isExplicit, PetscViewer viewer, PetscViewerFormat format)
671: {
672:   PetscReal     *r, *c;
673:   PetscInt       n, i, neig;
674:   PetscBool      isascii, isdraw;
675:   PetscMPIInt    rank;

679:   MPI_Comm_rank(PetscObjectComm((PetscObject) ksp), &rank);
680:   PetscObjectTypeCompare((PetscObject) viewer, PETSCVIEWERASCII, &isascii);
681:   PetscObjectTypeCompare((PetscObject) viewer, PETSCVIEWERDRAW,  &isdraw);
682:   if (isExplicit) {
683:     VecGetSize(ksp->vec_sol,&n);
684:     PetscMalloc2(n, &r, n, &c);
685:     KSPComputeEigenvaluesExplicitly(ksp, n, r, c);
686:     neig = n;
687:   } else {
688:     PetscInt nits;

690:     KSPGetIterationNumber(ksp, &nits);
691:     n    = nits+2;
692:     if (!nits) {PetscViewerASCIIPrintf(viewer, "Zero iterations in solver, cannot approximate any eigenvalues\n");return(0);}
693:     PetscMalloc2(n, &r, n, &c);
694:     KSPComputeEigenvalues(ksp, n, r, c, &neig);
695:   }
696:   if (isascii) {
697:     PetscViewerASCIIPrintf(viewer, "%s computed eigenvalues\n", isExplicit ? "Explicitly" : "Iteratively");
698:     for (i = 0; i < neig; ++i) {
699:       if (c[i] >= 0.0) {PetscViewerASCIIPrintf(viewer, "%g + %gi\n", (double) r[i],  (double) c[i]);}
700:       else             {PetscViewerASCIIPrintf(viewer, "%g - %gi\n", (double) r[i], -(double) c[i]);}
701:     }
702:   } else if (isdraw && rank == 0) {
703:     PetscDraw   draw;
704:     PetscDrawSP drawsp;

706:     if (format == PETSC_VIEWER_DRAW_CONTOUR) {
707:       KSPPlotEigenContours_Private(ksp,neig,r,c);
708:     } else {
709:       if (!ksp->eigviewer) {PetscViewerDrawOpen(PETSC_COMM_SELF,NULL,isExplicit ? "Explicitly Computed Eigenvalues" : "Iteratively Computed Eigenvalues",PETSC_DECIDE,PETSC_DECIDE,400,400,&ksp->eigviewer);}
710:       PetscViewerDrawGetDraw(ksp->eigviewer,0,&draw);
711:       PetscDrawSPCreate(draw,1,&drawsp);
712:       PetscDrawSPReset(drawsp);
713:       for (i = 0; i < neig; ++i) {PetscDrawSPAddPoint(drawsp,r+i,c+i);}
714:       PetscDrawSPDraw(drawsp,PETSC_TRUE);
715:       PetscDrawSPSave(drawsp);
716:       PetscDrawSPDestroy(&drawsp);
717:     }
718:   }
719:   PetscFree2(r, c);
720:   return(0);
721: }

723: static PetscErrorCode KSPViewSingularvalues_Internal(KSP ksp, PetscViewer viewer, PetscViewerFormat format)
724: {
725:   PetscReal      smax, smin;
726:   PetscInt       nits;
727:   PetscBool      isascii;

731:   PetscObjectTypeCompare((PetscObject) viewer, PETSCVIEWERASCII, &isascii);
732:   KSPGetIterationNumber(ksp, &nits);
733:   if (!nits) {PetscViewerASCIIPrintf(viewer, "Zero iterations in solver, cannot approximate any singular values\n");return(0);}
734:   KSPComputeExtremeSingularValues(ksp, &smax, &smin);
735:   if (isascii) {PetscViewerASCIIPrintf(viewer, "Iteratively computed extreme singular values: max %g min %g max/min %g\n",(double)smax,(double)smin,(double)(smax/smin));}
736:   return(0);
737: }

739: static PetscErrorCode KSPViewFinalResidual_Internal(KSP ksp, PetscViewer viewer, PetscViewerFormat format)
740: {
741:   PetscBool      isascii;

745:   PetscObjectTypeCompare((PetscObject) viewer, PETSCVIEWERASCII, &isascii);
746:   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");
747:   if (isascii) {
748:     Mat       A;
749:     Vec       t;
750:     PetscReal norm;

752:     PCGetOperators(ksp->pc, &A, NULL);
753:     VecDuplicate(ksp->vec_rhs, &t);
754:     KSP_MatMult(ksp, A, ksp->vec_sol, t);
755:     VecAYPX(t, -1.0, ksp->vec_rhs);
756:     VecNorm(t, NORM_2, &norm);
757:     VecDestroy(&t);
758:     PetscViewerASCIIPrintf(viewer, "KSP final norm of residual %g\n", (double) norm);
759:   }
760:   return(0);
761: }

763: static PetscErrorCode KSPMonitorPauseFinal_Internal(KSP ksp)
764: {
765:   PetscInt       i;

769:   if (!ksp->pauseFinal) return(0);
770:   for (i = 0; i < ksp->numbermonitors; ++i) {
771:     PetscViewerAndFormat *vf = (PetscViewerAndFormat *) ksp->monitorcontext[i];
772:     PetscDraw             draw;
773:     PetscReal             lpause;

775:     if (!vf) continue;
776:     if (vf->lg) {
778:       if (((PetscObject) vf->lg)->classid != PETSC_DRAWLG_CLASSID) continue;
779:       PetscDrawLGGetDraw(vf->lg, &draw);
780:       PetscDrawGetPause(draw, &lpause);
781:       PetscDrawSetPause(draw, -1.0);
782:       PetscDrawPause(draw);
783:       PetscDrawSetPause(draw, lpause);
784:     } else {
785:       PetscBool isdraw;

788:       if (((PetscObject) vf->viewer)->classid != PETSC_VIEWER_CLASSID) continue;
789:       PetscObjectTypeCompare((PetscObject) vf->viewer, PETSCVIEWERDRAW, &isdraw);
790:       if (!isdraw) continue;
791:       PetscViewerDrawGetDraw(vf->viewer, 0, &draw);
792:       PetscDrawGetPause(draw, &lpause);
793:       PetscDrawSetPause(draw, -1.0);
794:       PetscDrawPause(draw);
795:       PetscDrawSetPause(draw, lpause);
796:     }
797:   }
798:   return(0);
799: }

801: static PetscErrorCode KSPSolve_Private(KSP ksp,Vec b,Vec x)
802: {
804:   PetscBool      flg = PETSC_FALSE,inXisinB=PETSC_FALSE,guess_zero;
805:   Mat            mat,pmat;
806:   MPI_Comm       comm;
807:   MatNullSpace   nullsp;
808:   Vec            btmp,vec_rhs=NULL;

811:   comm = PetscObjectComm((PetscObject)ksp);
812:   if (x && x == b) {
813:     if (!ksp->guess_zero) SETERRQ(comm,PETSC_ERR_ARG_INCOMP,"Cannot use x == b with nonzero initial guess");
814:     VecDuplicate(b,&x);
815:     inXisinB = PETSC_TRUE;
816:   }
817:   if (b) {
818:     PetscObjectReference((PetscObject)b);
819:     VecDestroy(&ksp->vec_rhs);
820:     ksp->vec_rhs = b;
821:   }
822:   if (x) {
823:     PetscObjectReference((PetscObject)x);
824:     VecDestroy(&ksp->vec_sol);
825:     ksp->vec_sol = x;
826:   }

828:   if (ksp->viewPre) {ObjectView((PetscObject) ksp, ksp->viewerPre, ksp->formatPre);}

830:   if (ksp->presolve) {(*ksp->presolve)(ksp,ksp->vec_rhs,ksp->vec_sol,ksp->prectx);}

832:   /* reset the residual history list if requested */
833:   if (ksp->res_hist_reset) ksp->res_hist_len = 0;
834:   if (ksp->err_hist_reset) ksp->err_hist_len = 0;

836:   if (ksp->guess) {
837:     PetscObjectState ostate,state;

839:     KSPGuessSetUp(ksp->guess);
840:     PetscObjectStateGet((PetscObject)ksp->vec_sol,&ostate);
841:     KSPGuessFormGuess(ksp->guess,ksp->vec_rhs,ksp->vec_sol);
842:     PetscObjectStateGet((PetscObject)ksp->vec_sol,&state);
843:     if (state != ostate) {
844:       ksp->guess_zero = PETSC_FALSE;
845:     } else {
846:       PetscInfo(ksp,"Using zero initial guess since the KSPGuess object did not change the vector\n");
847:       ksp->guess_zero = PETSC_TRUE;
848:     }
849:   }

851:   /* KSPSetUp() scales the matrix if needed */
852:   KSPSetUp(ksp);
853:   KSPSetUpOnBlocks(ksp);

855:   VecSetErrorIfLocked(ksp->vec_sol,3);

857:   PetscLogEventBegin(KSP_Solve,ksp,ksp->vec_rhs,ksp->vec_sol,0);
858:   PCGetOperators(ksp->pc,&mat,&pmat);
859:   /* diagonal scale RHS if called for */
860:   if (ksp->dscale) {
861:     VecPointwiseMult(ksp->vec_rhs,ksp->vec_rhs,ksp->diagonal);
862:     /* second time in, but matrix was scaled back to original */
863:     if (ksp->dscalefix && ksp->dscalefix2) {
864:       Mat mat,pmat;

866:       PCGetOperators(ksp->pc,&mat,&pmat);
867:       MatDiagonalScale(pmat,ksp->diagonal,ksp->diagonal);
868:       if (mat != pmat) {MatDiagonalScale(mat,ksp->diagonal,ksp->diagonal);}
869:     }

871:     /* scale initial guess */
872:     if (!ksp->guess_zero) {
873:       if (!ksp->truediagonal) {
874:         VecDuplicate(ksp->diagonal,&ksp->truediagonal);
875:         VecCopy(ksp->diagonal,ksp->truediagonal);
876:         VecReciprocal(ksp->truediagonal);
877:       }
878:       VecPointwiseMult(ksp->vec_sol,ksp->vec_sol,ksp->truediagonal);
879:     }
880:   }
881:   PCPreSolve(ksp->pc,ksp);

883:   if (ksp->guess_zero) { VecSet(ksp->vec_sol,0.0);}
884:   if (ksp->guess_knoll) { /* The Knoll trick is independent on the KSPGuess specified */
885:     PCApply(ksp->pc,ksp->vec_rhs,ksp->vec_sol);
886:     KSP_RemoveNullSpace(ksp,ksp->vec_sol);
887:     ksp->guess_zero = PETSC_FALSE;
888:   }

890:   /* can we mark the initial guess as zero for this solve? */
891:   guess_zero = ksp->guess_zero;
892:   if (!ksp->guess_zero) {
893:     PetscReal norm;

895:     VecNormAvailable(ksp->vec_sol,NORM_2,&flg,&norm);
896:     if (flg && !norm) ksp->guess_zero = PETSC_TRUE;
897:   }
898:   if (ksp->transpose_solve) {
899:     MatGetNullSpace(pmat,&nullsp);
900:   } else {
901:     MatGetTransposeNullSpace(pmat,&nullsp);
902:   }
903:   if (nullsp) {
904:     VecDuplicate(ksp->vec_rhs,&btmp);
905:     VecCopy(ksp->vec_rhs,btmp);
906:     MatNullSpaceRemove(nullsp,btmp);
907:     vec_rhs      = ksp->vec_rhs;
908:     ksp->vec_rhs = btmp;
909:   }
910:   VecLockReadPush(ksp->vec_rhs);
911:   if (ksp->reason == KSP_DIVERGED_PC_FAILED) {
912:     VecSetInf(ksp->vec_sol);
913:   }
914:   (*ksp->ops->solve)(ksp);
915:   KSPMonitorPauseFinal_Internal(ksp);

917:   VecLockReadPop(ksp->vec_rhs);
918:   if (nullsp) {
919:     ksp->vec_rhs = vec_rhs;
920:     VecDestroy(&btmp);
921:   }

923:   ksp->guess_zero = guess_zero;

925:   if (!ksp->reason) SETERRQ(comm,PETSC_ERR_PLIB,"Internal error, solver returned without setting converged reason");
926:   ksp->totalits += ksp->its;

928:   KSPConvergedReasonViewFromOptions(ksp);

930:   if (ksp->viewRate) {
931:     PetscViewerPushFormat(ksp->viewerRate,ksp->formatRate);
932:     KSPConvergedRateView(ksp, ksp->viewerRate);
933:     PetscViewerPopFormat(ksp->viewerRate);
934:   }
935:   PCPostSolve(ksp->pc,ksp);

937:   /* diagonal scale solution if called for */
938:   if (ksp->dscale) {
939:     VecPointwiseMult(ksp->vec_sol,ksp->vec_sol,ksp->diagonal);
940:     /* unscale right hand side and matrix */
941:     if (ksp->dscalefix) {
942:       Mat mat,pmat;

944:       VecReciprocal(ksp->diagonal);
945:       VecPointwiseMult(ksp->vec_rhs,ksp->vec_rhs,ksp->diagonal);
946:       PCGetOperators(ksp->pc,&mat,&pmat);
947:       MatDiagonalScale(pmat,ksp->diagonal,ksp->diagonal);
948:       if (mat != pmat) {MatDiagonalScale(mat,ksp->diagonal,ksp->diagonal);}
949:       VecReciprocal(ksp->diagonal);
950:       ksp->dscalefix2 = PETSC_TRUE;
951:     }
952:   }
953:   PetscLogEventEnd(KSP_Solve,ksp,ksp->vec_rhs,ksp->vec_sol,0);
954:   if (ksp->guess) {
955:     KSPGuessUpdate(ksp->guess,ksp->vec_rhs,ksp->vec_sol);
956:   }
957:   if (ksp->postsolve) {
958:     (*ksp->postsolve)(ksp,ksp->vec_rhs,ksp->vec_sol,ksp->postctx);
959:   }

961:   PCGetOperators(ksp->pc,&mat,&pmat);
962:   if (ksp->viewEV)       {KSPViewEigenvalues_Internal(ksp, PETSC_FALSE, ksp->viewerEV,    ksp->formatEV);}
963:   if (ksp->viewEVExp)    {KSPViewEigenvalues_Internal(ksp, PETSC_TRUE,  ksp->viewerEVExp, ksp->formatEVExp);}
964:   if (ksp->viewSV)       {KSPViewSingularvalues_Internal(ksp, ksp->viewerSV, ksp->formatSV);}
965:   if (ksp->viewFinalRes) {KSPViewFinalResidual_Internal(ksp, ksp->viewerFinalRes, ksp->formatFinalRes);}
966:   if (ksp->viewMat)      {ObjectView((PetscObject) mat,           ksp->viewerMat,    ksp->formatMat);}
967:   if (ksp->viewPMat)     {ObjectView((PetscObject) pmat,          ksp->viewerPMat,   ksp->formatPMat);}
968:   if (ksp->viewRhs)      {ObjectView((PetscObject) ksp->vec_rhs,  ksp->viewerRhs,    ksp->formatRhs);}
969:   if (ksp->viewSol)      {ObjectView((PetscObject) ksp->vec_sol,  ksp->viewerSol,    ksp->formatSol);}
970:   if (ksp->view)         {ObjectView((PetscObject) ksp,           ksp->viewer,       ksp->format);}
971:   if (ksp->viewDScale)   {ObjectView((PetscObject) ksp->diagonal, ksp->viewerDScale, ksp->formatDScale);}
972:   if (ksp->viewMatExp)   {
973:     Mat A, B;

975:     PCGetOperators(ksp->pc, &A, NULL);
976:     if (ksp->transpose_solve) {
977:       Mat AT;

979:       MatCreateTranspose(A, &AT);
980:       MatComputeOperator(AT, MATAIJ, &B);
981:       MatDestroy(&AT);
982:     } else {
983:       MatComputeOperator(A, MATAIJ, &B);
984:     }
985:     ObjectView((PetscObject) B, ksp->viewerMatExp, ksp->formatMatExp);
986:     MatDestroy(&B);
987:   }
988:   if (ksp->viewPOpExp)   {
989:     Mat B;

991:     KSPComputeOperator(ksp, MATAIJ, &B);
992:     ObjectView((PetscObject) B, ksp->viewerPOpExp, ksp->formatPOpExp);
993:     MatDestroy(&B);
994:   }

996:   if (inXisinB) {
997:     VecCopy(x,b);
998:     VecDestroy(&x);
999:   }
1000:   PetscObjectSAWsBlock((PetscObject)ksp);
1001:   if (ksp->errorifnotconverged && ksp->reason < 0 && ksp->reason != KSP_DIVERGED_ITS) {
1002:     if (ksp->reason == KSP_DIVERGED_PC_FAILED) {
1003:       PCFailedReason reason;
1004:       PCGetFailedReason(ksp->pc,&reason);
1005:       SETERRQ2(comm,PETSC_ERR_NOT_CONVERGED,"KSPSolve has not converged, reason %s PC failed due to %s",KSPConvergedReasons[ksp->reason],PCFailedReasons[reason]);
1006:     } else SETERRQ1(comm,PETSC_ERR_NOT_CONVERGED,"KSPSolve has not converged, reason %s",KSPConvergedReasons[ksp->reason]);
1007:   }
1008:   return(0);
1009: }

1011: /*@
1012:    KSPSolve - Solves linear system.

1014:    Collective on ksp

1016:    Parameters:
1017: +  ksp - iterative context obtained from KSPCreate()
1018: .  b - the right hand side vector
1019: -  x - the solution (this may be the same vector as b, then b will be overwritten with answer)

1021:    Options Database Keys:
1022: +  -ksp_view_eigenvalues - compute preconditioned operators eigenvalues
1023: .  -ksp_view_eigenvalues_explicit - compute the eigenvalues by forming the dense operator and using LAPACK
1024: .  -ksp_view_mat binary - save matrix to the default binary viewer
1025: .  -ksp_view_pmat binary - save matrix used to build preconditioner to the default binary viewer
1026: .  -ksp_view_rhs binary - save right hand side vector to the default binary viewer
1027: .  -ksp_view_solution binary - save computed solution vector to the default binary viewer
1028:            (can be read later with src/ksp/tutorials/ex10.c for testing solvers)
1029: .  -ksp_view_mat_explicit - for matrix-free operators, computes the matrix entries and views them
1030: .  -ksp_view_preconditioned_operator_explicit - computes the product of the preconditioner and matrix as an explicit matrix and views it
1031: .  -ksp_converged_reason - print reason for converged or diverged, also prints number of iterations
1032: .  -ksp_view_final_residual - print 2-norm of true linear system residual at the end of the solution process
1033: -  -ksp_view - print the ksp data structure at the end of the system solution

1035:    Notes:

1037:    If one uses KSPSetDM() then x or b need not be passed. Use KSPGetSolution() to access the solution in this case.

1039:    The operator is specified with KSPSetOperators().

1041:    Call KSPGetConvergedReason() to determine if the solver converged or failed and
1042:    why. The number of iterations can be obtained from KSPGetIterationNumber().

1044:    If you provide a matrix that has a MatSetNullSpace() and MatSetTransposeNullSpace() this will use that information to solve singular systems
1045:    in the least squares sense with a norm minimizing solution.
1046: $
1047: $                   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()
1048: $
1049: $    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
1050: $    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
1051: $    direction thus the solution which is a linear combination of the search directions has no component in the nullspace(A).
1052: $
1053: $    We recommend always using GMRES for such singular systems.
1054: $    If nullspace(A) = nullspace(A') (note symmetric matrices always satisfy this property) then both left and right preconditioning will work
1055: $    If nullspace(A) != nullspace(A') then left preconditioning will work but right preconditioning may not work (or it may).

1057:    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
1058:        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
1059:        such as diagonal scaling we cannot apply the inverse of the preconditioner to a vector and thus cannot compute the nullspace(AB).

1061:    If using a direct method (e.g., via the KSP solver
1062:    KSPPREONLY and a preconditioner such as PCLU/PCILU),
1063:    then its=1.  See KSPSetTolerances() and KSPConvergedDefault()
1064:    for more details.

1066:    Understanding Convergence:
1067:    The routines KSPMonitorSet(), KSPComputeEigenvalues(), and
1068:    KSPComputeEigenvaluesExplicitly() provide information on additional
1069:    options to monitor convergence and print eigenvalue information.

1071:    Level: beginner

1073: .seealso: KSPCreate(), KSPSetUp(), KSPDestroy(), KSPSetTolerances(), KSPConvergedDefault(),
1074:           KSPSolveTranspose(), KSPGetIterationNumber(), MatNullSpaceCreate(), MatSetNullSpace(), MatSetTransposeNullSpace(), KSP,
1075:           KSPConvergedReasonView()
1076: @*/
1077: PetscErrorCode KSPSolve(KSP ksp,Vec b,Vec x)
1078: {

1085:   ksp->transpose_solve = PETSC_FALSE;
1086:   KSPSolve_Private(ksp,b,x);
1087:   return(0);
1088: }

1090: /*@
1091:    KSPSolveTranspose - Solves the transpose of a linear system.

1093:    Collective on ksp

1095:    Input Parameters:
1096: +  ksp - iterative context obtained from KSPCreate()
1097: .  b - right hand side vector
1098: -  x - solution vector

1100:    Notes:
1101:     For complex numbers this solve the non-Hermitian transpose system.

1103:    Developer Notes:
1104:     We need to implement a KSPSolveHermitianTranspose()

1106:    Level: developer

1108: .seealso: KSPCreate(), KSPSetUp(), KSPDestroy(), KSPSetTolerances(), KSPConvergedDefault(),
1109:           KSPSolve(), KSP
1110: @*/
1111: PetscErrorCode KSPSolveTranspose(KSP ksp,Vec b,Vec x)
1112: {

1119:   if (ksp->transpose.use_explicittranspose) {
1120:     Mat J,Jpre;
1121:     KSPGetOperators(ksp,&J,&Jpre);
1122:     if (!ksp->transpose.reuse_transpose) {
1123:       MatTranspose(J,MAT_INITIAL_MATRIX,&ksp->transpose.AT);
1124:       if (J != Jpre) {
1125:         MatTranspose(Jpre,MAT_INITIAL_MATRIX,&ksp->transpose.BT);
1126:       }
1127:       ksp->transpose.reuse_transpose = PETSC_TRUE;
1128:     } else {
1129:       MatTranspose(J,MAT_REUSE_MATRIX,&ksp->transpose.AT);
1130:       if (J != Jpre) {
1131:         MatTranspose(Jpre,MAT_REUSE_MATRIX,&ksp->transpose.BT);
1132:       }
1133:     }
1134:     if (J == Jpre && ksp->transpose.BT != ksp->transpose.AT) {
1135:       PetscObjectReference((PetscObject)ksp->transpose.AT);
1136:       ksp->transpose.BT = ksp->transpose.AT;
1137:     }
1138:     KSPSetOperators(ksp,ksp->transpose.AT,ksp->transpose.BT);
1139:   } else {
1140:     ksp->transpose_solve = PETSC_TRUE;
1141:   }
1142:   KSPSolve_Private(ksp,b,x);
1143:   return(0);
1144: }

1146: static PetscErrorCode KSPViewFinalMatResidual_Internal(KSP ksp, Mat B, Mat X, PetscViewer viewer, PetscViewerFormat format, PetscInt shift)
1147: {
1148:   Mat            A, R;
1149:   PetscReal      *norms;
1150:   PetscInt       i, N;
1151:   PetscBool      flg;

1155:   PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &flg);
1156:   if (flg) {
1157:     PCGetOperators(ksp->pc, &A, NULL);
1158:     MatMatMult(A, X, MAT_INITIAL_MATRIX, PETSC_DEFAULT, &R);
1159:     MatAYPX(R, -1.0, B, SAME_NONZERO_PATTERN);
1160:     MatGetSize(R, NULL, &N);
1161:     PetscMalloc1(N, &norms);
1162:     MatGetColumnNorms(R, NORM_2, norms);
1163:     MatDestroy(&R);
1164:     for (i = 0; i < N; ++i) {
1165:       PetscViewerASCIIPrintf(viewer, "%s #%D %g\n", i == 0 ? "KSP final norm of residual" : "                          ", shift + i, (double)norms[i]);
1166:     }
1167:     PetscFree(norms);
1168:   }
1169:   return(0);
1170: }

1172: /*@
1173:      KSPMatSolve - Solves a linear system with multiple right-hand sides stored as a MATDENSE. Unlike KSPSolve(), B and X must be different matrices.

1175:    Input Parameters:
1176: +     ksp - iterative context
1177: -     B - block of right-hand sides

1179:    Output Parameter:
1180: .     X - block of solutions

1182:    Notes:
1183:      This is a stripped-down version of KSPSolve(), which only handles -ksp_view, -ksp_converged_reason, and -ksp_view_final_residual.

1185:    Level: intermediate

1187: .seealso:  KSPSolve(), MatMatSolve(), MATDENSE, KSPHPDDM, PCBJACOBI, PCASM
1188: @*/
1189: PetscErrorCode KSPMatSolve(KSP ksp, Mat B, Mat X)
1190: {
1191:   Mat            A, P, vB, vX;
1192:   Vec            cb, cx;
1193:   PetscInt       n1, N1, n2, N2, Bbn = PETSC_DECIDE;
1194:   PetscBool      match;

1203:   if (!B->assembled) SETERRQ(PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Not for unassembled matrix");
1204:   MatCheckPreallocated(X, 3);
1205:   if (!X->assembled) {
1206:     MatSetOption(X, MAT_NO_OFF_PROC_ENTRIES, PETSC_TRUE);
1207:     MatAssemblyBegin(X, MAT_FINAL_ASSEMBLY);
1208:     MatAssemblyEnd(X, MAT_FINAL_ASSEMBLY);
1209:   }
1210:   if (B == X) SETERRQ(PetscObjectComm((PetscObject)ksp), PETSC_ERR_ARG_IDN, "B and X must be different matrices");
1211:   KSPGetOperators(ksp, &A, &P);
1212:   MatGetLocalSize(B, NULL, &n2);
1213:   MatGetLocalSize(X, NULL, &n1);
1214:   MatGetSize(B, NULL, &N2);
1215:   MatGetSize(X, NULL, &N1);
1216:   if (n1 != n2 || N1 != N2) SETERRQ4(PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Incompatible number of columns between block of right-hand sides (n,N) = (%D,%D) and block of solutions (n,N) = (%D,%D)", n2, N2, n1, N1);
1217:   PetscObjectBaseTypeCompareAny((PetscObject)B, &match, MATSEQDENSE, MATMPIDENSE, "");
1218:   if (!match) SETERRQ(PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Provided block of right-hand sides not stored in a dense Mat");
1219:   PetscObjectBaseTypeCompareAny((PetscObject)X, &match, MATSEQDENSE, MATMPIDENSE, "");
1220:   if (!match) SETERRQ(PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Provided block of solutions not stored in a dense Mat");
1221:   KSPSetUp(ksp);
1222:   KSPSetUpOnBlocks(ksp);
1223:   if (ksp->ops->matsolve) {
1224:     if (ksp->guess_zero) {
1225:       MatZeroEntries(X);
1226:     }
1227:     PetscLogEventBegin(KSP_MatSolve, ksp, B, X, 0);
1228:     KSPGetMatSolveBatchSize(ksp, &Bbn);
1229:     /* by default, do a single solve with all columns */
1230:     if (Bbn == PETSC_DECIDE) Bbn = N2;
1231:     else if (Bbn < 1) SETERRQ1(PetscObjectComm((PetscObject)ksp), PETSC_ERR_ARG_OUTOFRANGE, "KSPMatSolve() batch size %D must be positive", Bbn);
1232:     PetscInfo2(ksp, "KSP type %s solving using batches of width at most %D\n", ((PetscObject)ksp)->type_name, Bbn);
1233:     /* if -ksp_matsolve_batch_size is greater than the actual number of columns, do a single solve with all columns */
1234:     if (Bbn >= N2) {
1235:       (*ksp->ops->matsolve)(ksp, B, X);
1236:       if (ksp->viewFinalRes) {
1237:         KSPViewFinalMatResidual_Internal(ksp, B, X, ksp->viewerFinalRes, ksp->formatFinalRes, 0);
1238:       }

1240:       KSPConvergedReasonViewFromOptions(ksp);

1242:       if (ksp->viewRate) {
1243:         PetscViewerPushFormat(ksp->viewerRate,PETSC_VIEWER_DEFAULT);
1244:         KSPConvergedRateView(ksp, ksp->viewerRate);
1245:         PetscViewerPopFormat(ksp->viewerRate);
1246:       }
1247:     } else {
1248:       for (n2 = 0; n2 < N2; n2 += Bbn) {
1249:         MatDenseGetSubMatrix(B, n2, PetscMin(n2+Bbn, N2), &vB);
1250:         MatDenseGetSubMatrix(X, n2, PetscMin(n2+Bbn, N2), &vX);
1251:         (*ksp->ops->matsolve)(ksp, vB, vX);
1252:         if (ksp->viewFinalRes) {
1253:           KSPViewFinalMatResidual_Internal(ksp, vB, vX, ksp->viewerFinalRes, ksp->formatFinalRes, n2);
1254:         }

1256:         KSPConvergedReasonViewFromOptions(ksp);

1258:         if (ksp->viewRate) {
1259:           PetscViewerPushFormat(ksp->viewerRate,PETSC_VIEWER_DEFAULT);
1260:           KSPConvergedRateView(ksp, ksp->viewerRate);
1261:           PetscViewerPopFormat(ksp->viewerRate);
1262:         }
1263:         MatDenseRestoreSubMatrix(B, &vB);
1264:         MatDenseRestoreSubMatrix(X, &vX);
1265:       }
1266:     }
1267:     if (ksp->viewMat)  {ObjectView((PetscObject) A, ksp->viewerMat, ksp->formatMat);}
1268:     if (ksp->viewPMat) {ObjectView((PetscObject) P, ksp->viewerPMat,ksp->formatPMat);}
1269:     if (ksp->viewRhs)  {ObjectView((PetscObject) B, ksp->viewerRhs, ksp->formatRhs);}
1270:     if (ksp->viewSol)  {ObjectView((PetscObject) X, ksp->viewerSol, ksp->formatSol);}
1271:     if (ksp->view) {
1272:       KSPView(ksp, ksp->viewer);
1273:     }
1274:     PetscLogEventEnd(KSP_MatSolve, ksp, B, X, 0);
1275:   } else {
1276:     PetscInfo1(ksp, "KSP type %s solving column by column\n", ((PetscObject)ksp)->type_name);
1277:     for (n2 = 0; n2 < N2; ++n2) {
1278:       MatDenseGetColumnVecRead(B, n2, &cb);
1279:       MatDenseGetColumnVecWrite(X, n2, &cx);
1280:       KSPSolve(ksp, cb, cx);
1281:       MatDenseRestoreColumnVecWrite(X, n2, &cx);
1282:       MatDenseRestoreColumnVecRead(B, n2, &cb);
1283:     }
1284:   }
1285:   return(0);
1286: }

1288: /*@
1289:      KSPSetMatSolveBatchSize - Sets the maximum number of columns treated simultaneously in KSPMatSolve().

1291:     Logically collective

1293:    Input Parameters:
1294: +     ksp - iterative context
1295: -     bs - batch size

1297:    Level: advanced

1299: .seealso:  KSPMatSolve(), KSPGetMatSolveBatchSize(), -mat_mumps_icntl_27, -matmatmult_Bbn
1300: @*/
1301: PetscErrorCode KSPSetMatSolveBatchSize(KSP ksp, PetscInt bs)
1302: {
1306:   ksp->nmax = bs;
1307:   return(0);
1308: }

1310: /*@
1311:      KSPGetMatSolveBatchSize - Gets the maximum number of columns treated simultaneously in KSPMatSolve().

1313:    Input Parameter:
1314: .     ksp - iterative context

1316:    Output Parameter:
1317: .     bs - batch size

1319:    Level: advanced

1321: .seealso:  KSPMatSolve(), KSPSetMatSolveBatchSize(), -mat_mumps_icntl_27, -matmatmult_Bbn
1322: @*/
1323: PetscErrorCode KSPGetMatSolveBatchSize(KSP ksp, PetscInt *bs)
1324: {
1328:   *bs = ksp->nmax;
1329:   return(0);
1330: }

1332: /*@
1333:    KSPResetViewers - Resets all the viewers set from the options database during KSPSetFromOptions()

1335:    Collective on ksp

1337:    Input Parameter:
1338: .  ksp - iterative context obtained from KSPCreate()

1340:    Level: beginner

1342: .seealso: KSPCreate(), KSPSetUp(), KSPSolve(), KSPSetFromOptions(), KSP
1343: @*/
1344: PetscErrorCode  KSPResetViewers(KSP ksp)
1345: {

1350:   if (!ksp) return(0);
1351:   PetscViewerDestroy(&ksp->viewer);
1352:   PetscViewerDestroy(&ksp->viewerPre);
1353:   PetscViewerDestroy(&ksp->viewerRate);
1354:   PetscViewerDestroy(&ksp->viewerMat);
1355:   PetscViewerDestroy(&ksp->viewerPMat);
1356:   PetscViewerDestroy(&ksp->viewerRhs);
1357:   PetscViewerDestroy(&ksp->viewerSol);
1358:   PetscViewerDestroy(&ksp->viewerMatExp);
1359:   PetscViewerDestroy(&ksp->viewerEV);
1360:   PetscViewerDestroy(&ksp->viewerSV);
1361:   PetscViewerDestroy(&ksp->viewerEVExp);
1362:   PetscViewerDestroy(&ksp->viewerFinalRes);
1363:   PetscViewerDestroy(&ksp->viewerPOpExp);
1364:   PetscViewerDestroy(&ksp->viewerDScale);
1365:   ksp->view         = PETSC_FALSE;
1366:   ksp->viewPre      = PETSC_FALSE;
1367:   ksp->viewMat      = PETSC_FALSE;
1368:   ksp->viewPMat     = PETSC_FALSE;
1369:   ksp->viewRhs      = PETSC_FALSE;
1370:   ksp->viewSol      = PETSC_FALSE;
1371:   ksp->viewMatExp   = PETSC_FALSE;
1372:   ksp->viewEV       = PETSC_FALSE;
1373:   ksp->viewSV       = PETSC_FALSE;
1374:   ksp->viewEVExp    = PETSC_FALSE;
1375:   ksp->viewFinalRes = PETSC_FALSE;
1376:   ksp->viewPOpExp   = PETSC_FALSE;
1377:   ksp->viewDScale   = PETSC_FALSE;
1378:   return(0);
1379: }

1381: /*@
1382:    KSPReset - Resets a KSP context to the kspsetupcalled = 0 state and removes any allocated Vecs and Mats

1384:    Collective on ksp

1386:    Input Parameter:
1387: .  ksp - iterative context obtained from KSPCreate()

1389:    Level: beginner

1391: .seealso: KSPCreate(), KSPSetUp(), KSPSolve(), KSP
1392: @*/
1393: PetscErrorCode  KSPReset(KSP ksp)
1394: {

1399:   if (!ksp) return(0);
1400:   if (ksp->ops->reset) {
1401:     (*ksp->ops->reset)(ksp);
1402:   }
1403:   if (ksp->pc) {PCReset(ksp->pc);}
1404:   if (ksp->guess) {
1405:     KSPGuess guess = ksp->guess;
1406:     if (guess->ops->reset) { (*guess->ops->reset)(guess); }
1407:   }
1408:   VecDestroyVecs(ksp->nwork,&ksp->work);
1409:   VecDestroy(&ksp->vec_rhs);
1410:   VecDestroy(&ksp->vec_sol);
1411:   VecDestroy(&ksp->diagonal);
1412:   VecDestroy(&ksp->truediagonal);

1414:   KSPResetViewers(ksp);

1416:   ksp->setupstage = KSP_SETUP_NEW;
1417:   ksp->nmax = PETSC_DECIDE;
1418:   return(0);
1419: }

1421: /*@C
1422:    KSPDestroy - Destroys KSP context.

1424:    Collective on ksp

1426:    Input Parameter:
1427: .  ksp - iterative context obtained from KSPCreate()

1429:    Level: beginner

1431: .seealso: KSPCreate(), KSPSetUp(), KSPSolve(), KSP
1432: @*/
1433: PetscErrorCode  KSPDestroy(KSP *ksp)
1434: {
1436:   PC             pc;

1439:   if (!*ksp) return(0);
1441:   if (--((PetscObject)(*ksp))->refct > 0) {*ksp = NULL; return(0);}

1443:   PetscObjectSAWsViewOff((PetscObject)*ksp);

1445:   /*
1446:    Avoid a cascading call to PCReset(ksp->pc) from the following call:
1447:    PCReset() shouldn't be called from KSPDestroy() as it is unprotected by pc's
1448:    refcount (and may be shared, e.g., by other ksps).
1449:    */
1450:   pc         = (*ksp)->pc;
1451:   (*ksp)->pc = NULL;
1452:   KSPReset((*ksp));
1453:   (*ksp)->pc = pc;
1454:   if ((*ksp)->ops->destroy) {(*(*ksp)->ops->destroy)(*ksp);}

1456:   if ((*ksp)->transpose.use_explicittranspose) {
1457:     MatDestroy(&(*ksp)->transpose.AT);
1458:     MatDestroy(&(*ksp)->transpose.BT);
1459:     (*ksp)->transpose.reuse_transpose = PETSC_FALSE;
1460:   }

1462:   KSPGuessDestroy(&(*ksp)->guess);
1463:   DMDestroy(&(*ksp)->dm);
1464:   PCDestroy(&(*ksp)->pc);
1465:   PetscFree((*ksp)->res_hist_alloc);
1466:   PetscFree((*ksp)->err_hist_alloc);
1467:   if ((*ksp)->convergeddestroy) {
1468:     (*(*ksp)->convergeddestroy)((*ksp)->cnvP);
1469:   }
1470:   KSPMonitorCancel((*ksp));
1471:   KSPConvergedReasonViewCancel((*ksp));
1472:   PetscViewerDestroy(&(*ksp)->eigviewer);
1473:   PetscHeaderDestroy(ksp);
1474:   return(0);
1475: }

1477: /*@
1478:     KSPSetPCSide - Sets the preconditioning side.

1480:     Logically Collective on ksp

1482:     Input Parameter:
1483: .   ksp - iterative context obtained from KSPCreate()

1485:     Output Parameter:
1486: .   side - the preconditioning side, where side is one of
1487: .vb
1488:       PC_LEFT - left preconditioning (default)
1489:       PC_RIGHT - right preconditioning
1490:       PC_SYMMETRIC - symmetric preconditioning
1491: .ve

1493:     Options Database Keys:
1494: .   -ksp_pc_side <right,left,symmetric>

1496:     Notes:
1497:     Left preconditioning is used by default for most Krylov methods except KSPFGMRES which only supports right preconditioning.

1499:     For methods changing the side of the preconditioner changes the norm type that is used, see KSPSetNormType().

1501:     Symmetric preconditioning is currently available only for the KSPQCG method. Note, however, that
1502:     symmetric preconditioning can be emulated by using either right or left
1503:     preconditioning and a pre or post processing step.

1505:     Setting the PC side often affects the default norm type.  See KSPSetNormType() for details.

1507:     Level: intermediate

1509: .seealso: KSPGetPCSide(), KSPSetNormType(), KSPGetNormType(), KSP
1510: @*/
1511: PetscErrorCode  KSPSetPCSide(KSP ksp,PCSide side)
1512: {
1516:   ksp->pc_side = ksp->pc_side_set = side;
1517:   return(0);
1518: }

1520: /*@
1521:     KSPGetPCSide - Gets the preconditioning side.

1523:     Not Collective

1525:     Input Parameter:
1526: .   ksp - iterative context obtained from KSPCreate()

1528:     Output Parameter:
1529: .   side - the preconditioning side, where side is one of
1530: .vb
1531:       PC_LEFT - left preconditioning (default)
1532:       PC_RIGHT - right preconditioning
1533:       PC_SYMMETRIC - symmetric preconditioning
1534: .ve

1536:     Level: intermediate

1538: .seealso: KSPSetPCSide(), KSP
1539: @*/
1540: PetscErrorCode  KSPGetPCSide(KSP ksp,PCSide *side)
1541: {

1547:   KSPSetUpNorms_Private(ksp,PETSC_TRUE,&ksp->normtype,&ksp->pc_side);
1548:   *side = ksp->pc_side;
1549:   return(0);
1550: }

1552: /*@
1553:    KSPGetTolerances - Gets the relative, absolute, divergence, and maximum
1554:    iteration tolerances used by the default KSP convergence tests.

1556:    Not Collective

1558:    Input Parameter:
1559: .  ksp - the Krylov subspace context

1561:    Output Parameters:
1562: +  rtol - the relative convergence tolerance
1563: .  abstol - the absolute convergence tolerance
1564: .  dtol - the divergence tolerance
1565: -  maxits - maximum number of iterations

1567:    Notes:
1568:    The user can specify NULL for any parameter that is not needed.

1570:    Level: intermediate

1572:            maximum, iterations

1574: .seealso: KSPSetTolerances(), KSP
1575: @*/
1576: PetscErrorCode  KSPGetTolerances(KSP ksp,PetscReal *rtol,PetscReal *abstol,PetscReal *dtol,PetscInt *maxits)
1577: {
1580:   if (abstol) *abstol = ksp->abstol;
1581:   if (rtol) *rtol = ksp->rtol;
1582:   if (dtol) *dtol = ksp->divtol;
1583:   if (maxits) *maxits = ksp->max_it;
1584:   return(0);
1585: }

1587: /*@
1588:    KSPSetTolerances - Sets the relative, absolute, divergence, and maximum
1589:    iteration tolerances used by the default KSP convergence testers.

1591:    Logically Collective on ksp

1593:    Input Parameters:
1594: +  ksp - the Krylov subspace context
1595: .  rtol - the relative convergence tolerance, relative decrease in the (possibly preconditioned) residual norm
1596: .  abstol - the absolute convergence tolerance   absolute size of the (possibly preconditioned) residual norm
1597: .  dtol - the divergence tolerance,   amount (possibly preconditioned) residual norm can increase before KSPConvergedDefault() concludes that the method is diverging
1598: -  maxits - maximum number of iterations to use

1600:    Options Database Keys:
1601: +  -ksp_atol <abstol> - Sets abstol
1602: .  -ksp_rtol <rtol> - Sets rtol
1603: .  -ksp_divtol <dtol> - Sets dtol
1604: -  -ksp_max_it <maxits> - Sets maxits

1606:    Notes:
1607:    Use PETSC_DEFAULT to retain the default value of any of the tolerances.

1609:    See KSPConvergedDefault() for details how these parameters are used in the default convergence test.  See also KSPSetConvergenceTest()
1610:    for setting user-defined stopping criteria.

1612:    Level: intermediate

1614:            convergence, maximum, iterations

1616: .seealso: KSPGetTolerances(), KSPConvergedDefault(), KSPSetConvergenceTest(), KSP
1617: @*/
1618: PetscErrorCode  KSPSetTolerances(KSP ksp,PetscReal rtol,PetscReal abstol,PetscReal dtol,PetscInt maxits)
1619: {

1627:   if (rtol != PETSC_DEFAULT) {
1628:     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);
1629:     ksp->rtol = rtol;
1630:   }
1631:   if (abstol != PETSC_DEFAULT) {
1632:     if (abstol < 0.0) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Absolute tolerance %g must be non-negative",(double)abstol);
1633:     ksp->abstol = abstol;
1634:   }
1635:   if (dtol != PETSC_DEFAULT) {
1636:     if (dtol < 0.0) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Divergence tolerance %g must be larger than 1.0",(double)dtol);
1637:     ksp->divtol = dtol;
1638:   }
1639:   if (maxits != PETSC_DEFAULT) {
1640:     if (maxits < 0) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Maximum number of iterations %D must be non-negative",maxits);
1641:     ksp->max_it = maxits;
1642:   }
1643:   return(0);
1644: }

1646: /*@
1647:    KSPSetInitialGuessNonzero - Tells the iterative solver that the
1648:    initial guess is nonzero; otherwise KSP assumes the initial guess
1649:    is to be zero (and thus zeros it out before solving).

1651:    Logically Collective on ksp

1653:    Input Parameters:
1654: +  ksp - iterative context obtained from KSPCreate()
1655: -  flg - PETSC_TRUE indicates the guess is non-zero, PETSC_FALSE indicates the guess is zero

1657:    Options database keys:
1658: .  -ksp_initial_guess_nonzero : use nonzero initial guess; this takes an optional truth value (0/1/no/yes/true/false)

1660:    Level: beginner

1662:    Notes:
1663:     If this is not called the X vector is zeroed in the call to KSPSolve().

1665: .seealso: KSPGetInitialGuessNonzero(), KSPSetGuessType(), KSPGuessType, KSP
1666: @*/
1667: PetscErrorCode  KSPSetInitialGuessNonzero(KSP ksp,PetscBool flg)
1668: {
1672:   ksp->guess_zero = (PetscBool) !(int)flg;
1673:   return(0);
1674: }

1676: /*@
1677:    KSPGetInitialGuessNonzero - Determines whether the KSP solver is using
1678:    a zero initial guess.

1680:    Not Collective

1682:    Input Parameter:
1683: .  ksp - iterative context obtained from KSPCreate()

1685:    Output Parameter:
1686: .  flag - PETSC_TRUE if guess is nonzero, else PETSC_FALSE

1688:    Level: intermediate

1690: .seealso: KSPSetInitialGuessNonzero(), KSP
1691: @*/
1692: PetscErrorCode  KSPGetInitialGuessNonzero(KSP ksp,PetscBool  *flag)
1693: {
1697:   if (ksp->guess_zero) *flag = PETSC_FALSE;
1698:   else *flag = PETSC_TRUE;
1699:   return(0);
1700: }

1702: /*@
1703:    KSPSetErrorIfNotConverged - Causes KSPSolve() to generate an error if the solver has not converged.

1705:    Logically Collective on ksp

1707:    Input Parameters:
1708: +  ksp - iterative context obtained from KSPCreate()
1709: -  flg - PETSC_TRUE indicates you want the error generated

1711:    Options database keys:
1712: .  -ksp_error_if_not_converged : this takes an optional truth value (0/1/no/yes/true/false)

1714:    Level: intermediate

1716:    Notes:
1717:     Normally PETSc continues if a linear solver fails to converge, you can call KSPGetConvergedReason() after a KSPSolve()
1718:     to determine if it has converged.

1720: .seealso: KSPGetErrorIfNotConverged(), KSP
1721: @*/
1722: PetscErrorCode  KSPSetErrorIfNotConverged(KSP ksp,PetscBool flg)
1723: {
1727:   ksp->errorifnotconverged = flg;
1728:   return(0);
1729: }

1731: /*@
1732:    KSPGetErrorIfNotConverged - Will KSPSolve() generate an error if the solver does not converge?

1734:    Not Collective

1736:    Input Parameter:
1737: .  ksp - iterative context obtained from KSPCreate()

1739:    Output Parameter:
1740: .  flag - PETSC_TRUE if it will generate an error, else PETSC_FALSE

1742:    Level: intermediate

1744: .seealso: KSPSetErrorIfNotConverged(), KSP
1745: @*/
1746: PetscErrorCode  KSPGetErrorIfNotConverged(KSP ksp,PetscBool  *flag)
1747: {
1751:   *flag = ksp->errorifnotconverged;
1752:   return(0);
1753: }

1755: /*@
1756:    KSPSetInitialGuessKnoll - Tells the iterative solver to use PCApply(pc,b,..) to compute the initial guess (The Knoll trick)

1758:    Logically Collective on ksp

1760:    Input Parameters:
1761: +  ksp - iterative context obtained from KSPCreate()
1762: -  flg - PETSC_TRUE or PETSC_FALSE

1764:    Level: advanced

1766:    Developer Note: the Knoll trick is not currently implemented using the KSPGuess class

1768: .seealso: KSPGetInitialGuessKnoll(), KSPSetInitialGuessNonzero(), KSPGetInitialGuessNonzero(), KSP
1769: @*/
1770: PetscErrorCode  KSPSetInitialGuessKnoll(KSP ksp,PetscBool flg)
1771: {
1775:   ksp->guess_knoll = flg;
1776:   return(0);
1777: }

1779: /*@
1780:    KSPGetInitialGuessKnoll - Determines whether the KSP solver is using the Knoll trick (using PCApply(pc,b,...) to compute
1781:      the initial guess

1783:    Not Collective

1785:    Input Parameter:
1786: .  ksp - iterative context obtained from KSPCreate()

1788:    Output Parameter:
1789: .  flag - PETSC_TRUE if using Knoll trick, else PETSC_FALSE

1791:    Level: advanced

1793: .seealso: KSPSetInitialGuessKnoll(), KSPSetInitialGuessNonzero(), KSPGetInitialGuessNonzero(), KSP
1794: @*/
1795: PetscErrorCode  KSPGetInitialGuessKnoll(KSP ksp,PetscBool  *flag)
1796: {
1800:   *flag = ksp->guess_knoll;
1801:   return(0);
1802: }

1804: /*@
1805:    KSPGetComputeSingularValues - Gets the flag indicating whether the extreme singular
1806:    values will be calculated via a Lanczos or Arnoldi process as the linear
1807:    system is solved.

1809:    Not Collective

1811:    Input Parameter:
1812: .  ksp - iterative context obtained from KSPCreate()

1814:    Output Parameter:
1815: .  flg - PETSC_TRUE or PETSC_FALSE

1817:    Options Database Key:
1818: .  -ksp_monitor_singular_value - Activates KSPSetComputeSingularValues()

1820:    Notes:
1821:    Currently this option is not valid for all iterative methods.

1823:    Many users may just want to use the monitoring routine
1824:    KSPMonitorSingularValue() (which can be set with option -ksp_monitor_singular_value)
1825:    to print the singular values at each iteration of the linear solve.

1827:    Level: advanced

1829: .seealso: KSPComputeExtremeSingularValues(), KSPMonitorSingularValue(), KSP
1830: @*/
1831: PetscErrorCode  KSPGetComputeSingularValues(KSP ksp,PetscBool  *flg)
1832: {
1836:   *flg = ksp->calc_sings;
1837:   return(0);
1838: }

1840: /*@
1841:    KSPSetComputeSingularValues - Sets a flag so that the extreme singular
1842:    values will be calculated via a Lanczos or Arnoldi process as the linear
1843:    system is solved.

1845:    Logically Collective on ksp

1847:    Input Parameters:
1848: +  ksp - iterative context obtained from KSPCreate()
1849: -  flg - PETSC_TRUE or PETSC_FALSE

1851:    Options Database Key:
1852: .  -ksp_monitor_singular_value - Activates KSPSetComputeSingularValues()

1854:    Notes:
1855:    Currently this option is not valid for all iterative methods.

1857:    Many users may just want to use the monitoring routine
1858:    KSPMonitorSingularValue() (which can be set with option -ksp_monitor_singular_value)
1859:    to print the singular values at each iteration of the linear solve.

1861:    Level: advanced

1863: .seealso: KSPComputeExtremeSingularValues(), KSPMonitorSingularValue(), KSP
1864: @*/
1865: PetscErrorCode  KSPSetComputeSingularValues(KSP ksp,PetscBool flg)
1866: {
1870:   ksp->calc_sings = flg;
1871:   return(0);
1872: }

1874: /*@
1875:    KSPGetComputeEigenvalues - Gets the flag indicating that the extreme eigenvalues
1876:    values will be calculated via a Lanczos or Arnoldi process as the linear
1877:    system is solved.

1879:    Not Collective

1881:    Input Parameter:
1882: .  ksp - iterative context obtained from KSPCreate()

1884:    Output Parameter:
1885: .  flg - PETSC_TRUE or PETSC_FALSE

1887:    Notes:
1888:    Currently this option is not valid for all iterative methods.

1890:    Level: advanced

1892: .seealso: KSPComputeEigenvalues(), KSPComputeEigenvaluesExplicitly(), KSP
1893: @*/
1894: PetscErrorCode  KSPGetComputeEigenvalues(KSP ksp,PetscBool  *flg)
1895: {
1899:   *flg = ksp->calc_sings;
1900:   return(0);
1901: }

1903: /*@
1904:    KSPSetComputeEigenvalues - Sets a flag so that the extreme eigenvalues
1905:    values will be calculated via a Lanczos or Arnoldi process as the linear
1906:    system is solved.

1908:    Logically Collective on ksp

1910:    Input Parameters:
1911: +  ksp - iterative context obtained from KSPCreate()
1912: -  flg - PETSC_TRUE or PETSC_FALSE

1914:    Notes:
1915:    Currently this option is not valid for all iterative methods.

1917:    Level: advanced

1919: .seealso: KSPComputeEigenvalues(), KSPComputeEigenvaluesExplicitly(), KSP
1920: @*/
1921: PetscErrorCode  KSPSetComputeEigenvalues(KSP ksp,PetscBool flg)
1922: {
1926:   ksp->calc_sings = flg;
1927:   return(0);
1928: }

1930: /*@
1931:    KSPSetComputeRitz - Sets a flag so that the Ritz or harmonic Ritz pairs
1932:    will be calculated via a Lanczos or Arnoldi process as the linear
1933:    system is solved.

1935:    Logically Collective on ksp

1937:    Input Parameters:
1938: +  ksp - iterative context obtained from KSPCreate()
1939: -  flg - PETSC_TRUE or PETSC_FALSE

1941:    Notes:
1942:    Currently this option is only valid for the GMRES method.

1944:    Level: advanced

1946: .seealso: KSPComputeRitz(), KSP
1947: @*/
1948: PetscErrorCode  KSPSetComputeRitz(KSP ksp, PetscBool flg)
1949: {
1953:   ksp->calc_ritz = flg;
1954:   return(0);
1955: }

1957: /*@
1958:    KSPGetRhs - Gets the right-hand-side vector for the linear system to
1959:    be solved.

1961:    Not Collective

1963:    Input Parameter:
1964: .  ksp - iterative context obtained from KSPCreate()

1966:    Output Parameter:
1967: .  r - right-hand-side vector

1969:    Level: developer

1971: .seealso: KSPGetSolution(), KSPSolve(), KSP
1972: @*/
1973: PetscErrorCode  KSPGetRhs(KSP ksp,Vec *r)
1974: {
1978:   *r = ksp->vec_rhs;
1979:   return(0);
1980: }

1982: /*@
1983:    KSPGetSolution - Gets the location of the solution for the
1984:    linear system to be solved.  Note that this may not be where the solution
1985:    is stored during the iterative process; see KSPBuildSolution().

1987:    Not Collective

1989:    Input Parameters:
1990: .  ksp - iterative context obtained from KSPCreate()

1992:    Output Parameters:
1993: .  v - solution vector

1995:    Level: developer

1997: .seealso: KSPGetRhs(),  KSPBuildSolution(), KSPSolve(), KSP
1998: @*/
1999: PetscErrorCode  KSPGetSolution(KSP ksp,Vec *v)
2000: {
2004:   *v = ksp->vec_sol;
2005:   return(0);
2006: }

2008: /*@
2009:    KSPSetPC - Sets the preconditioner to be used to calculate the
2010:    application of the preconditioner on a vector.

2012:    Collective on ksp

2014:    Input Parameters:
2015: +  ksp - iterative context obtained from KSPCreate()
2016: -  pc   - the preconditioner object (can be NULL)

2018:    Notes:
2019:    Use KSPGetPC() to retrieve the preconditioner context.

2021:    Level: developer

2023: .seealso: KSPGetPC(), KSP
2024: @*/
2025: PetscErrorCode  KSPSetPC(KSP ksp,PC pc)
2026: {

2031:   if (pc) {
2034:   }
2035:   PetscObjectReference((PetscObject)pc);
2036:   PCDestroy(&ksp->pc);
2037:   ksp->pc = pc;
2038:   PetscLogObjectParent((PetscObject)ksp,(PetscObject)ksp->pc);
2039:   return(0);
2040: }

2042: /*@
2043:    KSPGetPC - Returns a pointer to the preconditioner context
2044:    set with KSPSetPC().

2046:    Not Collective

2048:    Input Parameters:
2049: .  ksp - iterative context obtained from KSPCreate()

2051:    Output Parameter:
2052: .  pc - preconditioner context

2054:    Level: developer

2056: .seealso: KSPSetPC(), KSP
2057: @*/
2058: PetscErrorCode  KSPGetPC(KSP ksp,PC *pc)
2059: {

2065:   if (!ksp->pc) {
2066:     PCCreate(PetscObjectComm((PetscObject)ksp),&ksp->pc);
2067:     PetscObjectIncrementTabLevel((PetscObject)ksp->pc,(PetscObject)ksp,0);
2068:     PetscLogObjectParent((PetscObject)ksp,(PetscObject)ksp->pc);
2069:     PetscObjectSetOptions((PetscObject)ksp->pc,((PetscObject)ksp)->options);
2070:   }
2071:   *pc = ksp->pc;
2072:   return(0);
2073: }

2075: /*@
2076:    KSPMonitor - runs the user provided monitor routines, if they exist

2078:    Collective on ksp

2080:    Input Parameters:
2081: +  ksp - iterative context obtained from KSPCreate()
2082: .  it - iteration number
2083: -  rnorm - relative norm of the residual

2085:    Notes:
2086:    This routine is called by the KSP implementations.
2087:    It does not typically need to be called by the user.

2089:    Level: developer

2091: .seealso: KSPMonitorSet()
2092: @*/
2093: PetscErrorCode KSPMonitor(KSP ksp,PetscInt it,PetscReal rnorm)
2094: {
2095:   PetscInt       i, n = ksp->numbermonitors;

2099:   for (i=0; i<n; i++) {
2100:     (*ksp->monitor[i])(ksp,it,rnorm,ksp->monitorcontext[i]);
2101:   }
2102:   return(0);
2103: }

2105: /*@C
2106:    KSPMonitorSet - Sets an ADDITIONAL function to be called at every iteration to monitor
2107:    the residual/error etc.

2109:    Logically Collective on ksp

2111:    Input Parameters:
2112: +  ksp - iterative context obtained from KSPCreate()
2113: .  monitor - pointer to function (if this is NULL, it turns off monitoring
2114: .  mctx    - [optional] context for private data for the
2115:              monitor routine (use NULL if no context is desired)
2116: -  monitordestroy - [optional] routine that frees monitor context
2117:           (may be NULL)

2119:    Calling Sequence of monitor:
2120: $     monitor (KSP ksp, PetscInt it, PetscReal rnorm, void *mctx)

2122: +  ksp - iterative context obtained from KSPCreate()
2123: .  it - iteration number
2124: .  rnorm - (estimated) 2-norm of (preconditioned) residual
2125: -  mctx  - optional monitoring context, as set by KSPMonitorSet()

2127:    Options Database Keys:
2128: +    -ksp_monitor               - sets KSPMonitorResidual()
2129: .    -ksp_monitor draw          - sets KSPMonitorResidualDraw() and plots residual
2130: .    -ksp_monitor draw::draw_lg - sets KSPMonitorResidualDrawLG() and plots residual
2131: .    -ksp_monitor_pause_final   - Pauses any graphics when the solve finishes (only works for internal monitors)
2132: .    -ksp_monitor_true_residual - sets KSPMonitorTrueResidual()
2133: .    -ksp_monitor_true_residual draw::draw_lg - sets KSPMonitorTrueResidualDrawLG() and plots residual
2134: .    -ksp_monitor_max           - sets KSPMonitorTrueResidualMax()
2135: .    -ksp_monitor_singular_value - sets KSPMonitorSingularValue()
2136: -    -ksp_monitor_cancel - cancels all monitors that have
2137:                           been hardwired into a code by
2138:                           calls to KSPMonitorSet(), but
2139:                           does not cancel those set via
2140:                           the options database.

2142:    Notes:
2143:    The default is to do nothing.  To print the residual, or preconditioned
2144:    residual if KSPSetNormType(ksp,KSP_NORM_PRECONDITIONED) was called, use
2145:    KSPMonitorResidual() as the monitoring routine, with a ASCII viewer as the
2146:    context.

2148:    Several different monitoring routines may be set by calling
2149:    KSPMonitorSet() multiple times; all will be called in the
2150:    order in which they were set.

2152:    Fortran Notes:
2153:     Only a single monitor function can be set for each KSP object

2155:    Level: beginner

2157: .seealso: KSPMonitorResidual(), KSPMonitorCancel(), KSP
2158: @*/
2159: PetscErrorCode  KSPMonitorSet(KSP ksp,PetscErrorCode (*monitor)(KSP,PetscInt,PetscReal,void*),void *mctx,PetscErrorCode (*monitordestroy)(void**))
2160: {
2161:   PetscInt       i;
2163:   PetscBool      identical;

2167:   for (i=0; i<ksp->numbermonitors;i++) {
2168:     PetscMonitorCompare((PetscErrorCode (*)(void))monitor,mctx,monitordestroy,(PetscErrorCode (*)(void))ksp->monitor[i],ksp->monitorcontext[i],ksp->monitordestroy[i],&identical);
2169:     if (identical) return(0);
2170:   }
2171:   if (ksp->numbermonitors >= MAXKSPMONITORS) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Too many KSP monitors set");
2172:   ksp->monitor[ksp->numbermonitors]          = monitor;
2173:   ksp->monitordestroy[ksp->numbermonitors]   = monitordestroy;
2174:   ksp->monitorcontext[ksp->numbermonitors++] = (void*)mctx;
2175:   return(0);
2176: }

2178: /*@
2179:    KSPMonitorCancel - Clears all monitors for a KSP object.

2181:    Logically Collective on ksp

2183:    Input Parameters:
2184: .  ksp - iterative context obtained from KSPCreate()

2186:    Options Database Key:
2187: .  -ksp_monitor_cancel - Cancels all monitors that have
2188:     been hardwired into a code by calls to KSPMonitorSet(),
2189:     but does not cancel those set via the options database.

2191:    Level: intermediate

2193: .seealso: KSPMonitorResidual(), KSPMonitorSet(), KSP
2194: @*/
2195: PetscErrorCode  KSPMonitorCancel(KSP ksp)
2196: {
2198:   PetscInt       i;

2202:   for (i=0; i<ksp->numbermonitors; i++) {
2203:     if (ksp->monitordestroy[i]) {
2204:       (*ksp->monitordestroy[i])(&ksp->monitorcontext[i]);
2205:     }
2206:   }
2207:   ksp->numbermonitors = 0;
2208:   return(0);
2209: }

2211: /*@C
2212:    KSPGetMonitorContext - Gets the monitoring context, as set by
2213:    KSPMonitorSet() for the FIRST monitor only.

2215:    Not Collective

2217:    Input Parameter:
2218: .  ksp - iterative context obtained from KSPCreate()

2220:    Output Parameter:
2221: .  ctx - monitoring context

2223:    Level: intermediate

2225: .seealso: KSPMonitorResidual(), KSP
2226: @*/
2227: PetscErrorCode  KSPGetMonitorContext(KSP ksp,void *ctx)
2228: {
2231:   *(void**)ctx = ksp->monitorcontext[0];
2232:   return(0);
2233: }

2235: /*@
2236:    KSPSetResidualHistory - Sets the array used to hold the residual history.
2237:    If set, this array will contain the residual norms computed at each
2238:    iteration of the solver.

2240:    Not Collective

2242:    Input Parameters:
2243: +  ksp - iterative context obtained from KSPCreate()
2244: .  a   - array to hold history
2245: .  na  - size of a
2246: -  reset - PETSC_TRUE indicates the history counter is reset to zero
2247:            for each new linear solve

2249:    Level: advanced

2251:    Notes:
2252:    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.
2253:    If 'a' is NULL then space is allocated for the history. If 'na' PETSC_DECIDE or PETSC_DEFAULT then a
2254:    default array of length 10000 is allocated.

2256: .seealso: KSPGetResidualHistory(), KSP

2258: @*/
2259: PetscErrorCode KSPSetResidualHistory(KSP ksp,PetscReal a[],PetscInt na,PetscBool reset)
2260: {


2266:   PetscFree(ksp->res_hist_alloc);
2267:   if (na != PETSC_DECIDE && na != PETSC_DEFAULT && a) {
2268:     ksp->res_hist     = a;
2269:     ksp->res_hist_max = na;
2270:   } else {
2271:     if (na != PETSC_DECIDE && na != PETSC_DEFAULT) ksp->res_hist_max = na;
2272:     else                                           ksp->res_hist_max = 10000; /* like default ksp->max_it */
2273:     PetscCalloc1(ksp->res_hist_max,&ksp->res_hist_alloc);

2275:     ksp->res_hist = ksp->res_hist_alloc;
2276:   }
2277:   ksp->res_hist_len   = 0;
2278:   ksp->res_hist_reset = reset;
2279:   return(0);
2280: }

2282: /*@C
2283:    KSPGetResidualHistory - Gets the array used to hold the residual history
2284:    and the number of residuals it contains.

2286:    Not Collective

2288:    Input Parameter:
2289: .  ksp - iterative context obtained from KSPCreate()

2291:    Output Parameters:
2292: +  a   - pointer to array to hold history (or NULL)
2293: -  na  - number of used entries in a (or NULL)

2295:    Level: advanced

2297:    Notes:
2298:      This array is borrowed and should not be freed by the caller.
2299:      Can only be called after a KSPSetResidualHistory() otherwise a and na are set to zero

2301:      The Fortran version of this routine has a calling sequence
2302: $   call KSPGetResidualHistory(KSP ksp, integer na, integer ierr)
2303:     note that you have passed a Fortran array into KSPSetResidualHistory() and you need
2304:     to access the residual values from this Fortran array you provided. Only the na (number of
2305:     residual norms currently held) is set.

2307: .seealso: KSPSetResidualHistory(), KSP

2309: @*/
2310: PetscErrorCode KSPGetResidualHistory(KSP ksp, const PetscReal *a[],PetscInt *na)
2311: {
2314:   if (a) *a = ksp->res_hist;
2315:   if (na) *na = ksp->res_hist_len;
2316:   return(0);
2317: }

2319: /*@
2320:   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.

2322:   Not Collective

2324:   Input Parameters:
2325: + ksp   - iterative context obtained from KSPCreate()
2326: . a     - array to hold history
2327: . na    - size of a
2328: - reset - PETSC_TRUE indicates the history counter is reset to zero for each new linear solve

2330:   Level: advanced

2332:   Notes:
2333:   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.
2334:   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.

2336: .seealso: KSPGetErrorHistory(), KSPSetResidualHistory(), KSP
2337: @*/
2338: PetscErrorCode KSPSetErrorHistory(KSP ksp, PetscReal a[], PetscInt na, PetscBool reset)
2339: {


2345:   PetscFree(ksp->err_hist_alloc);
2346:   if (na != PETSC_DECIDE && na != PETSC_DEFAULT && a) {
2347:     ksp->err_hist     = a;
2348:     ksp->err_hist_max = na;
2349:   } else {
2350:     if (na != PETSC_DECIDE && na != PETSC_DEFAULT) ksp->err_hist_max = na;
2351:     else                                           ksp->err_hist_max = 10000; /* like default ksp->max_it */
2352:     PetscCalloc1(ksp->err_hist_max, &ksp->err_hist_alloc);

2354:     ksp->err_hist = ksp->err_hist_alloc;
2355:   }
2356:   ksp->err_hist_len   = 0;
2357:   ksp->err_hist_reset = reset;
2358:   return(0);
2359: }

2361: /*@C
2362:   KSPGetErrorHistory - Gets the array used to hold the error history and the number of residuals it contains.

2364:   Not Collective

2366:   Input Parameter:
2367: . ksp - iterative context obtained from KSPCreate()

2369:   Output Parameters:
2370: + a  - pointer to array to hold history (or NULL)
2371: - na - number of used entries in a (or NULL)

2373:   Level: advanced

2375:   Notes:
2376:   This array is borrowed and should not be freed by the caller.
2377:   Can only be called after a KSPSetErrorHistory() otherwise a and na are set to zero
2378:   The Fortran version of this routine has a calling sequence
2379: $   call KSPGetErrorHistory(KSP ksp, integer na, integer ierr)
2380:   note that you have passed a Fortran array into KSPSetErrorHistory() and you need
2381:   to access the residual values from this Fortran array you provided. Only the na (number of
2382:   residual norms currently held) is set.

2384: .seealso: KSPSetErrorHistory(), KSPGetResidualHistory(), KSP
2385: @*/
2386: PetscErrorCode KSPGetErrorHistory(KSP ksp, const PetscReal *a[], PetscInt *na)
2387: {
2390:   if (a)  *a  = ksp->err_hist;
2391:   if (na) *na = ksp->err_hist_len;
2392:   return(0);
2393: }

2395: /*
2396:   KSPComputeConvergenceRate - Compute the convergence rate for the iteration

2398:   Not collective

2400:   Input Parameter:
2401: . ksp - The KSP

2403:   Output Parameters:
2404: + cr   - The residual contraction rate
2405: . rRsq - The coefficient of determination, R^2, indicating the linearity of the data
2406: . ce   - The error contraction rate
2407: - eRsq - The coefficient of determination, R^2, indicating the linearity of the data

2409:   Note:
2410:   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,
2411:   the slope is $\log c$. The coefficient of determination is given by $1 - \frac{\sum_i (y_i - f(x_i))^2}{\sum_i (y_i - \bar y)}$,
2412:   see also https://en.wikipedia.org/wiki/Coefficient_of_determination

2414:   Level: advanced

2416: .seealso: KSPConvergedRateView()
2417: */
2418: PetscErrorCode KSPComputeConvergenceRate(KSP ksp, PetscReal *cr, PetscReal *rRsq, PetscReal *ce, PetscReal *eRsq)
2419: {
2420:   PetscReal      const *hist;
2421:   PetscReal      *x, *y, slope, intercept, mean = 0.0, var = 0.0, res = 0.0;
2422:   PetscInt       n, k;

2426:   if (cr || rRsq) {
2427:     KSPGetResidualHistory(ksp, &hist, &n);
2428:     if (!n) {
2429:       if (cr)   *cr   =  0.0;
2430:       if (rRsq) *rRsq = -1.0;
2431:     } else {
2432:       PetscMalloc2(n, &x, n, &y);
2433:       for (k = 0; k < n; ++k) {
2434:         x[k] = k;
2435:         y[k] = PetscLogReal(hist[k]);
2436:         mean += y[k];
2437:       }
2438:       mean /= n;
2439:       PetscLinearRegression(n, x, y, &slope, &intercept);
2440:       for (k = 0; k < n; ++k) {
2441:         res += PetscSqr(y[k] - (slope*x[k] + intercept));
2442:         var += PetscSqr(y[k] - mean);
2443:       }
2444:       PetscFree2(x, y);
2445:       if (cr)   *cr   = PetscExpReal(slope);
2446:       if (rRsq) *rRsq = var < PETSC_MACHINE_EPSILON ? 0.0 : 1.0 - (res / var);
2447:     }
2448:   }
2449:   if (ce || eRsq) {
2450:     KSPGetErrorHistory(ksp, &hist, &n);
2451:     if (!n) {
2452:       if (ce)   *ce   =  0.0;
2453:       if (eRsq) *eRsq = -1.0;
2454:     } else {
2455:       PetscMalloc2(n, &x, n, &y);
2456:       for (k = 0; k < n; ++k) {
2457:         x[k] = k;
2458:         y[k] = PetscLogReal(hist[k]);
2459:         mean += y[k];
2460:       }
2461:       mean /= n;
2462:       PetscLinearRegression(n, x, y, &slope, &intercept);
2463:       for (k = 0; k < n; ++k) {
2464:         res += PetscSqr(y[k] - (slope*x[k] + intercept));
2465:         var += PetscSqr(y[k] - mean);
2466:       }
2467:       PetscFree2(x, y);
2468:       if (ce)   *ce   = PetscExpReal(slope);
2469:       if (eRsq) *eRsq = var < PETSC_MACHINE_EPSILON ? 0.0 : 1.0 - (res / var);
2470:     }
2471:   }
2472:   return(0);
2473: }

2475: /*@C
2476:    KSPSetConvergenceTest - Sets the function to be used to determine
2477:    convergence.

2479:    Logically Collective on ksp

2481:    Input Parameters:
2482: +  ksp - iterative context obtained from KSPCreate()
2483: .  converge - pointer to the function
2484: .  cctx    - context for private data for the convergence routine (may be null)
2485: -  destroy - a routine for destroying the context (may be null)

2487:    Calling sequence of converge:
2488: $     converge (KSP ksp, PetscInt it, PetscReal rnorm, KSPConvergedReason *reason,void *mctx)

2490: +  ksp - iterative context obtained from KSPCreate()
2491: .  it - iteration number
2492: .  rnorm - (estimated) 2-norm of (preconditioned) residual
2493: .  reason - the reason why it has converged or diverged
2494: -  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 Parameters:
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 Parameters:
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:   *(void**)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 Parameters:
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

2738:     Notes:
2739:     Scales the matrix by  D^(-1/2)  A  D^(-1/2)  [D^(1/2) x ] = D^(-1/2) b
2740:        where D_{ii} is 1/abs(A_{ii}) unless A_{ii} is zero and then it is 1.

2742:     BE CAREFUL with this routine: it actually scales the matrix and right
2743:     hand side that define the system. After the system is solved the matrix
2744:     and right hand side remain scaled unless you use KSPSetDiagonalScaleFix()

2746:     This should NOT be used within the SNES solves if you are using a line
2747:     search.

2749:     If you use this with the PCType Eisenstat preconditioner than you can
2750:     use the PCEisenstatSetNoDiagonalScaling() option, or -pc_eisenstat_no_diagonal_scaling
2751:     to save some unneeded, redundant flops.

2753:    Level: intermediate

2755: .seealso: KSPGetDiagonalScale(), KSPSetDiagonalScaleFix(), KSP
2756: @*/
2757: PetscErrorCode  KSPSetDiagonalScale(KSP ksp,PetscBool scale)
2758: {
2762:   ksp->dscale = scale;
2763:   return(0);
2764: }

2766: /*@
2767:    KSPGetDiagonalScale - Checks if KSP solver scales the matrix and
2768:                           right hand side

2770:    Not Collective

2772:    Input Parameter:
2773: .  ksp - the KSP context

2775:    Output Parameter:
2776: .  scale - PETSC_TRUE or PETSC_FALSE

2778:    Notes:
2779:     BE CAREFUL with this routine: it actually scales the matrix and right
2780:     hand side that define the system. After the system is solved the matrix
2781:     and right hand side remain scaled  unless you use KSPSetDiagonalScaleFix()

2783:    Level: intermediate

2785: .seealso: KSPSetDiagonalScale(), KSPSetDiagonalScaleFix(), KSP
2786: @*/
2787: PetscErrorCode  KSPGetDiagonalScale(KSP ksp,PetscBool  *scale)
2788: {
2792:   *scale = ksp->dscale;
2793:   return(0);
2794: }

2796: /*@
2797:    KSPSetDiagonalScaleFix - Tells KSP to diagonally scale the system
2798:      back after solving.

2800:    Logically Collective on ksp

2802:    Input Parameters:
2803: +  ksp - the KSP context
2804: -  fix - PETSC_TRUE to scale back after the system solve, PETSC_FALSE to not
2805:          rescale (default)

2807:    Notes:
2808:      Must be called after KSPSetDiagonalScale()

2810:      Using this will slow things down, because it rescales the matrix before and
2811:      after each linear solve. This is intended mainly for testing to allow one
2812:      to easily get back the original system to make sure the solution computed is
2813:      accurate enough.

2815:    Level: intermediate

2817: .seealso: KSPGetDiagonalScale(), KSPSetDiagonalScale(), KSPGetDiagonalScaleFix(), KSP
2818: @*/
2819: PetscErrorCode  KSPSetDiagonalScaleFix(KSP ksp,PetscBool fix)
2820: {
2824:   ksp->dscalefix = fix;
2825:   return(0);
2826: }

2828: /*@
2829:    KSPGetDiagonalScaleFix - Determines if KSP diagonally scales the system
2830:      back after solving.

2832:    Not Collective

2834:    Input Parameter:
2835: .  ksp - the KSP context

2837:    Output Parameter:
2838: .  fix - PETSC_TRUE to scale back after the system solve, PETSC_FALSE to not
2839:          rescale (default)

2841:    Notes:
2842:      Must be called after KSPSetDiagonalScale()

2844:      If PETSC_TRUE will slow things down, because it rescales the matrix before and
2845:      after each linear solve. This is intended mainly for testing to allow one
2846:      to easily get back the original system to make sure the solution computed is
2847:      accurate enough.

2849:    Level: intermediate

2851: .seealso: KSPGetDiagonalScale(), KSPSetDiagonalScale(), KSPSetDiagonalScaleFix(), KSP
2852: @*/
2853: PetscErrorCode  KSPGetDiagonalScaleFix(KSP ksp,PetscBool  *fix)
2854: {
2858:   *fix = ksp->dscalefix;
2859:   return(0);
2860: }

2862: /*@C
2863:    KSPSetComputeOperators - set routine to compute the linear operators

2865:    Logically Collective

2867:    Input Parameters:
2868: +  ksp - the KSP context
2869: .  func - function to compute the operators
2870: -  ctx - optional context

2872:    Calling sequence of func:
2873: $  func(KSP ksp,Mat A,Mat B,void *ctx)

2875: +  ksp - the KSP context
2876: .  A - the linear operator
2877: .  B - preconditioning matrix
2878: -  ctx - optional user-provided context

2880:    Notes:
2881:     The user provided func() will be called automatically at the very next call to KSPSolve(). It will not be called at future KSPSolve() calls
2882:           unless either KSPSetComputeOperators() or KSPSetOperators() is called before that KSPSolve() is called.

2884:           To reuse the same preconditioner for the next KSPSolve() and not compute a new one based on the most recently computed matrix call KSPSetReusePreconditioner()

2886:    Level: beginner

2888: .seealso: KSPSetOperators(), KSPSetComputeRHS(), DMKSPSetComputeOperators(), KSPSetComputeInitialGuess()
2889: @*/
2890: PetscErrorCode KSPSetComputeOperators(KSP ksp,PetscErrorCode (*func)(KSP,Mat,Mat,void*),void *ctx)
2891: {
2893:   DM             dm;

2897:   KSPGetDM(ksp,&dm);
2898:   DMKSPSetComputeOperators(dm,func,ctx);
2899:   if (ksp->setupstage == KSP_SETUP_NEWRHS) ksp->setupstage = KSP_SETUP_NEWMATRIX;
2900:   return(0);
2901: }

2903: /*@C
2904:    KSPSetComputeRHS - set routine to compute the right hand side of the linear system

2906:    Logically Collective

2908:    Input Parameters:
2909: +  ksp - the KSP context
2910: .  func - function to compute the right hand side
2911: -  ctx - optional context

2913:    Calling sequence of func:
2914: $  func(KSP ksp,Vec b,void *ctx)

2916: +  ksp - the KSP context
2917: .  b - right hand side of linear system
2918: -  ctx - optional user-provided context

2920:    Notes:
2921:     The routine you provide will be called EACH you call KSPSolve() to prepare the new right hand side for that solve

2923:    Level: beginner

2925: .seealso: KSPSolve(), DMKSPSetComputeRHS(), KSPSetComputeOperators()
2926: @*/
2927: PetscErrorCode KSPSetComputeRHS(KSP ksp,PetscErrorCode (*func)(KSP,Vec,void*),void *ctx)
2928: {
2930:   DM             dm;

2934:   KSPGetDM(ksp,&dm);
2935:   DMKSPSetComputeRHS(dm,func,ctx);
2936:   return(0);
2937: }

2939: /*@C
2940:    KSPSetComputeInitialGuess - set routine to compute the initial guess of the linear system

2942:    Logically Collective

2944:    Input Parameters:
2945: +  ksp - the KSP context
2946: .  func - function to compute the initial guess
2947: -  ctx - optional context

2949:    Calling sequence of func:
2950: $  func(KSP ksp,Vec x,void *ctx)

2952: +  ksp - the KSP context
2953: .  x - solution vector
2954: -  ctx - optional user-provided context

2956:    Notes: This should only be used in conjunction with KSPSetComputeRHS(), KSPSetComputeOperators(), otherwise
2957:    call KSPSetInitialGuessNonzero() and set the initial guess values in the solution vector passed to KSPSolve().

2959:    Level: beginner

2961: .seealso: KSPSolve(), KSPSetComputeRHS(), KSPSetComputeOperators(), DMKSPSetComputeInitialGuess()
2962: @*/
2963: PetscErrorCode KSPSetComputeInitialGuess(KSP ksp,PetscErrorCode (*func)(KSP,Vec,void*),void *ctx)
2964: {
2966:   DM             dm;

2970:   KSPGetDM(ksp,&dm);
2971:   DMKSPSetComputeInitialGuess(dm,func,ctx);
2972:   return(0);
2973: }

2975: /*@
2976:    KSPSetUseExplicitTranspose - Determines if transpose the system explicitly
2977:    in KSPSolveTranspose.

2979:    Logically Collective on ksp

2981:    Input Parameter:
2982: .  ksp - the KSP context

2984:    Output Parameter:
2985: .  flg - PETSC_TRUE to transpose the system in KSPSolveTranspose, PETSC_FALSE to not
2986:          transpose (default)

2988:    Level: advanced

2990: .seealso: KSPSolveTranspose(), KSP
2991: @*/
2992: PetscErrorCode KSPSetUseExplicitTranspose(KSP ksp,PetscBool flg)
2993: {
2997:   ksp->transpose.use_explicittranspose = flg;
2998:   return(0);
2999: }