Actual source code: itfunc.c

petsc-master 2020-10-23
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  1: /*
  2:       Interface KSP routines that the user calls.
  3: */

  5: #include <petsc/private/kspimpl.h>
  6: #include <petsc/private/matimpl.h>
  7: #include <petscdm.h>

  9: PETSC_STATIC_INLINE PetscErrorCode ObjectView(PetscObject obj, PetscViewer viewer, PetscViewerFormat format)
 10: {

 13:   PetscViewerPushFormat(viewer, format);
 14:   PetscObjectView(obj, viewer);
 15:   PetscViewerPopFormat(viewer);
 16:   return(0);
 17: }

 19: /*@
 20:    KSPComputeExtremeSingularValues - Computes the extreme singular values
 21:    for the preconditioned operator. Called after or during KSPSolve().

 23:    Not Collective

 25:    Input Parameter:
 26: .  ksp - iterative context obtained from KSPCreate()

 28:    Output Parameters:
 29: .  emin, emax - extreme singular values

 31:    Options Database Keys:
 32: .  -ksp_view_singularvalues - compute extreme singular values and print when KSPSolve completes.

 34:    Notes:
 35:    One must call KSPSetComputeSingularValues() before calling KSPSetUp()
 36:    (or use the option -ksp_view_eigenvalues) in order for this routine to work correctly.

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

 42:    Estimates of the smallest singular value may be very inaccurate, especially if the Krylov method has not converged.
 43:    The largest singular value is usually accurate to within a few percent if the method has converged, but is still not
 44:    intended for eigenanalysis.

 46:    Disable restarts if using KSPGMRES, otherwise this estimate will only be using those iterations after the last
 47:    restart. See KSPGMRESSetRestart() for more details.

 49:    Level: advanced

 51: .seealso: KSPSetComputeSingularValues(), KSPMonitorSingularValue(), KSPComputeEigenvalues(), KSP
 52: @*/
 53: PetscErrorCode  KSPComputeExtremeSingularValues(KSP ksp,PetscReal *emax,PetscReal *emin)
 54: {

 61:   if (!ksp->calc_sings) SETERRQ(PetscObjectComm((PetscObject)ksp),4,"Singular values not requested before KSPSetUp()");

 63:   if (ksp->ops->computeextremesingularvalues) {
 64:     (*ksp->ops->computeextremesingularvalues)(ksp,emax,emin);
 65:   } else {
 66:     *emin = -1.0;
 67:     *emax = -1.0;
 68:   }
 69:   return(0);
 70: }

 72: /*@
 73:    KSPComputeEigenvalues - Computes the extreme eigenvalues for the
 74:    preconditioned operator. Called after or during KSPSolve().

 76:    Not Collective

 78:    Input Parameters:
 79: +  ksp - iterative context obtained from KSPCreate()
 80: -  n - size of arrays r and c. The number of eigenvalues computed (neig) will, in
 81:        general, be less than this.

 83:    Output Parameters:
 84: +  r - real part of computed eigenvalues, provided by user with a dimension of at least n
 85: .  c - complex part of computed eigenvalues, provided by user with a dimension of at least n
 86: -  neig - actual number of eigenvalues computed (will be less than or equal to n)

 88:    Options Database Keys:
 89: .  -ksp_view_eigenvalues - Prints eigenvalues to stdout

 91:    Notes:
 92:    The number of eigenvalues estimated depends on the size of the Krylov space
 93:    generated during the KSPSolve() ; for example, with
 94:    CG it corresponds to the number of CG iterations, for GMRES it is the number
 95:    of GMRES iterations SINCE the last restart. Any extra space in r[] and c[]
 96:    will be ignored.

 98:    KSPComputeEigenvalues() does not usually provide accurate estimates; it is
 99:    intended only for assistance in understanding the convergence of iterative
100:    methods, not for eigenanalysis. For accurate computation of eigenvalues we recommend using
101:    the excellent package SLEPc.

103:    One must call KSPSetComputeEigenvalues() before calling KSPSetUp()
104:    in order for this routine to work correctly.

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

110:    Level: advanced

112: .seealso: KSPSetComputeSingularValues(), KSPMonitorSingularValue(), KSPComputeExtremeSingularValues(), KSP
113: @*/
114: PetscErrorCode  KSPComputeEigenvalues(KSP ksp,PetscInt n,PetscReal r[],PetscReal c[],PetscInt *neig)
115: {

122:   if (n<0) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Requested < 0 Eigenvalues");
124:   if (!ksp->calc_sings) SETERRQ(PetscObjectComm((PetscObject)ksp),4,"Eigenvalues not requested before KSPSetUp()");

126:   if (n && ksp->ops->computeeigenvalues) {
127:     (*ksp->ops->computeeigenvalues)(ksp,n,r,c,neig);
128:   } else {
129:     *neig = 0;
130:   }
131:   return(0);
132: }

134: /*@
135:    KSPComputeRitz - Computes the Ritz or harmonic Ritz pairs associated to the
136:    smallest or largest in modulus, for the preconditioned operator.
137:    Called after KSPSolve().

139:    Not Collective

141:    Input Parameters:
142: +  ksp   - iterative context obtained from KSPCreate()
143: .  ritz  - PETSC_TRUE or PETSC_FALSE for ritz pairs or harmonic Ritz pairs, respectively
144: .  small - PETSC_TRUE or PETSC_FALSE for smallest or largest (harmonic) Ritz values, respectively
145: -  nrit  - number of (harmonic) Ritz pairs to compute

147:    Output Parameters:
148: +  nrit  - actual number of computed (harmonic) Ritz pairs
149: .  S     - multidimensional vector with Ritz vectors
150: .  tetar - real part of the Ritz values
151: -  tetai - imaginary part of the Ritz values

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

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

168:    Level: advanced

170: .seealso: KSPSetComputeRitz(), KSP
171: @*/
172: PetscErrorCode  KSPComputeRitz(KSP ksp,PetscBool ritz,PetscBool small,PetscInt *nrit,Vec S[],PetscReal tetar[],PetscReal tetai[])
173: {

178:   if (!ksp->calc_ritz) SETERRQ(PetscObjectComm((PetscObject)ksp),4,"Ritz pairs not requested before KSPSetUp()");
179:   if (ksp->ops->computeritz) {(*ksp->ops->computeritz)(ksp,ritz,small,nrit,S,tetar,tetai);}
180:   return(0);
181: }
182: /*@
183:    KSPSetUpOnBlocks - Sets up the preconditioner for each block in
184:    the block Jacobi, block Gauss-Seidel, and overlapping Schwarz
185:    methods.

187:    Collective on ksp

189:    Input Parameter:
190: .  ksp - the KSP context

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

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

201:    Level: advanced

203: .seealso: PCSetUpOnBlocks(), KSPSetUp(), PCSetUp(), KSP
204: @*/
205: PetscErrorCode  KSPSetUpOnBlocks(KSP ksp)
206: {
207:   PC             pc;
209:   PCFailedReason pcreason;

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

223: /*@
224:    KSPSetReusePreconditioner - reuse the current preconditioner, do not construct a new one even if the operator changes

226:    Collective on ksp

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

232:    Level: intermediate

234: .seealso: KSPCreate(), KSPSolve(), KSPDestroy(), PCSetReusePreconditioner(), KSP
235: @*/
236: PetscErrorCode  KSPSetReusePreconditioner(KSP ksp,PetscBool flag)
237: {
238:   PC             pc;

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

248: /*@
249:    KSPGetReusePreconditioner - Determines if the KSP reuses the current preconditioner even if the operator in the preconditioner has changed.

251:    Collective on ksp

253:    Input Parameters:
254: .  ksp   - iterative context obtained from KSPCreate()

256:    Output Parameters:
257: .  flag - the boolean flag

259:    Level: intermediate

261: .seealso: KSPCreate(), KSPSolve(), KSPDestroy(), KSPSetReusePreconditioner(), KSP
262: @*/
263: PetscErrorCode  KSPGetReusePreconditioner(KSP ksp,PetscBool *flag)
264: {

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

277: /*@
278:    KSPSetSkipPCSetFromOptions - prevents KSPSetFromOptions() from call PCSetFromOptions(). This is used if the same PC is shared by more than one KSP so its options are not resetable for each KSP

280:    Collective on ksp

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

286:    Level: intermediate

288: .seealso: KSPCreate(), KSPSolve(), KSPDestroy(), PCSetReusePreconditioner(), KSP
289: @*/
290: PetscErrorCode  KSPSetSkipPCSetFromOptions(KSP ksp,PetscBool flag)
291: {
294:   ksp->skippcsetfromoptions = flag;
295:   return(0);
296: }

298: /*@
299:    KSPSetUp - Sets up the internal data structures for the
300:    later use of an iterative solver.

302:    Collective on ksp

304:    Input Parameter:
305: .  ksp   - iterative context obtained from KSPCreate()

307:    Level: developer

309: .seealso: KSPCreate(), KSPSolve(), KSPDestroy(), KSP
310: @*/
311: PetscErrorCode KSPSetUp(KSP ksp)
312: {
314:   Mat            A,B;
315:   Mat            mat,pmat;
316:   MatNullSpace   nullsp;
317:   PCFailedReason pcreason;


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

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

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

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

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

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

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

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

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

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

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

428:    Collective on ksp

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

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

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

442:    Level: beginner

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

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

482: /*@
483:   KSPConvergedReasonViewFromOptions - Processes command line options to determine if/how a KSPReason is to be viewed.

485:   Collective on ksp

487:   Input Parameters:
488: . ksp   - the KSP object

490:   Level: intermediate

492: @*/
493: PetscErrorCode KSPConvergedReasonViewFromOptions(KSP ksp)
494: {
495:   PetscViewer       viewer;
496:   PetscBool         flg;
497:   PetscViewerFormat format;
498:   PetscErrorCode    ierr;

501:   PetscOptionsGetViewer(PetscObjectComm((PetscObject)ksp),((PetscObject)ksp)->options,((PetscObject)ksp)->prefix,"-ksp_converged_reason",&viewer,&format,&flg);
502:   if (flg) {
503:     PetscViewerPushFormat(viewer,format);
504:     KSPConvergedReasonView(ksp, viewer);
505:     PetscViewerPopFormat(viewer);
506:     PetscViewerDestroy(&viewer);
507:   }
508:   return(0);
509: }

511: #include <petscdraw.h>

513: static PetscErrorCode KSPViewEigenvalues_Internal(KSP ksp, PetscBool isExplicit, PetscViewer viewer, PetscViewerFormat format)
514: {
515:   PetscReal     *r, *c;
516:   PetscInt       n, i, neig;
517:   PetscBool      isascii, isdraw;
518:   PetscMPIInt    rank;

522:   MPI_Comm_rank(PetscObjectComm((PetscObject) ksp), &rank);
523:   PetscObjectTypeCompare((PetscObject) viewer, PETSCVIEWERASCII, &isascii);
524:   PetscObjectTypeCompare((PetscObject) viewer, PETSCVIEWERDRAW,  &isdraw);
525:   if (isExplicit) {
526:     VecGetSize(ksp->vec_sol,&n);
527:     PetscMalloc2(n, &r, n, &c);
528:     KSPComputeEigenvaluesExplicitly(ksp, n, r, c);
529:     neig = n;
530:   } else {
531:     PetscInt nits;

533:     KSPGetIterationNumber(ksp, &nits);
534:     n    = nits+2;
535:     if (!nits) {PetscViewerASCIIPrintf(viewer, "Zero iterations in solver, cannot approximate any eigenvalues\n");return(0);}
536:     PetscMalloc2(n, &r, n, &c);
537:     KSPComputeEigenvalues(ksp, n, r, c, &neig);
538:   }
539:   if (isascii) {
540:     PetscViewerASCIIPrintf(viewer, "%s computed eigenvalues\n", isExplicit ? "Explicitly" : "Iteratively");
541:     for (i = 0; i < neig; ++i) {
542:       if (c[i] >= 0.0) {PetscViewerASCIIPrintf(viewer, "%g + %gi\n", (double) r[i],  (double) c[i]);}
543:       else             {PetscViewerASCIIPrintf(viewer, "%g - %gi\n", (double) r[i], -(double) c[i]);}
544:     }
545:   } else if (isdraw && !rank) {
546:     PetscDraw   draw;
547:     PetscDrawSP drawsp;

549:     if (format == PETSC_VIEWER_DRAW_CONTOUR) {
550:       KSPPlotEigenContours_Private(ksp,neig,r,c);
551:     } else {
552:       if (!ksp->eigviewer) {PetscViewerDrawOpen(PETSC_COMM_SELF,NULL,isExplicit ? "Explicitly Computed Eigenvalues" : "Iteratively Computed Eigenvalues",PETSC_DECIDE,PETSC_DECIDE,400,400,&ksp->eigviewer);}
553:       PetscViewerDrawGetDraw(ksp->eigviewer,0,&draw);
554:       PetscDrawSPCreate(draw,1,&drawsp);
555:       PetscDrawSPReset(drawsp);
556:       for (i = 0; i < neig; ++i) {PetscDrawSPAddPoint(drawsp,r+i,c+i);}
557:       PetscDrawSPDraw(drawsp,PETSC_TRUE);
558:       PetscDrawSPSave(drawsp);
559:       PetscDrawSPDestroy(&drawsp);
560:     }
561:   }
562:   PetscFree2(r, c);
563:   return(0);
564: }

566: static PetscErrorCode KSPViewSingularvalues_Internal(KSP ksp, PetscViewer viewer, PetscViewerFormat format)
567: {
568:   PetscReal      smax, smin;
569:   PetscInt       nits;
570:   PetscBool      isascii;

574:   PetscObjectTypeCompare((PetscObject) viewer, PETSCVIEWERASCII, &isascii);
575:   KSPGetIterationNumber(ksp, &nits);
576:   if (!nits) {PetscViewerASCIIPrintf(viewer, "Zero iterations in solver, cannot approximate any singular values\n");return(0);}
577:   KSPComputeExtremeSingularValues(ksp, &smax, &smin);
578:   if (isascii) {PetscViewerASCIIPrintf(viewer, "Iteratively computed extreme singular values: max %g min %g max/min %g\n",(double)smax,(double)smin,(double)(smax/smin));}
579:   return(0);
580: }

582: static PetscErrorCode KSPViewFinalResidual_Internal(KSP ksp, PetscViewer viewer, PetscViewerFormat format)
583: {
584:   PetscBool      isascii;

588:   PetscObjectTypeCompare((PetscObject) viewer, PETSCVIEWERASCII, &isascii);
589:   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");
590:   if (isascii) {
591:     Mat       A;
592:     Vec       t;
593:     PetscReal norm;

595:     PCGetOperators(ksp->pc, &A, NULL);
596:     VecDuplicate(ksp->vec_rhs, &t);
597:     KSP_MatMult(ksp, A, ksp->vec_sol, t);
598:     VecAYPX(t, -1.0, ksp->vec_rhs);
599:     VecNorm(t, NORM_2, &norm);
600:     VecDestroy(&t);
601:     PetscViewerASCIIPrintf(viewer, "KSP final norm of residual %g\n", (double) norm);
602:   }
603:   return(0);
604: }

606: static PetscErrorCode KSPSolve_Private(KSP ksp,Vec b,Vec x)
607: {
609:   PetscBool      flg = PETSC_FALSE,inXisinB=PETSC_FALSE,guess_zero;
610:   Mat            mat,pmat;
611:   MPI_Comm       comm;
612:   MatNullSpace   nullsp;
613:   Vec            btmp,vec_rhs=NULL;

616:   comm = PetscObjectComm((PetscObject)ksp);
617:   if (x && x == b) {
618:     if (!ksp->guess_zero) SETERRQ(comm,PETSC_ERR_ARG_INCOMP,"Cannot use x == b with nonzero initial guess");
619:     VecDuplicate(b,&x);
620:     inXisinB = PETSC_TRUE;
621:   }
622:   if (b) {
623:     PetscObjectReference((PetscObject)b);
624:     VecDestroy(&ksp->vec_rhs);
625:     ksp->vec_rhs = b;
626:   }
627:   if (x) {
628:     PetscObjectReference((PetscObject)x);
629:     VecDestroy(&ksp->vec_sol);
630:     ksp->vec_sol = x;
631:   }

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

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

637:   /* reset the residual history list if requested */
638:   if (ksp->res_hist_reset) ksp->res_hist_len = 0;

640:   PetscLogEventBegin(KSP_Solve,ksp,ksp->vec_rhs,ksp->vec_sol,0);

642:   if (ksp->guess) {
643:     PetscObjectState ostate,state;

645:     KSPGuessSetUp(ksp->guess);
646:     PetscObjectStateGet((PetscObject)ksp->vec_sol,&ostate);
647:     KSPGuessFormGuess(ksp->guess,ksp->vec_rhs,ksp->vec_sol);
648:     PetscObjectStateGet((PetscObject)ksp->vec_sol,&state);
649:     if (state != ostate) {
650:       ksp->guess_zero = PETSC_FALSE;
651:     } else {
652:       PetscInfo(ksp,"Using zero initial guess since the KSPGuess object did not change the vector\n");
653:       ksp->guess_zero = PETSC_TRUE;
654:     }
655:   }

657:   /* KSPSetUp() scales the matrix if needed */
658:   KSPSetUp(ksp);
659:   KSPSetUpOnBlocks(ksp);

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

663:   PCGetOperators(ksp->pc,&mat,&pmat);
664:   /* diagonal scale RHS if called for */
665:   if (ksp->dscale) {
666:     VecPointwiseMult(ksp->vec_rhs,ksp->vec_rhs,ksp->diagonal);
667:     /* second time in, but matrix was scaled back to original */
668:     if (ksp->dscalefix && ksp->dscalefix2) {
669:       Mat mat,pmat;

671:       PCGetOperators(ksp->pc,&mat,&pmat);
672:       MatDiagonalScale(pmat,ksp->diagonal,ksp->diagonal);
673:       if (mat != pmat) {MatDiagonalScale(mat,ksp->diagonal,ksp->diagonal);}
674:     }

676:     /* scale initial guess */
677:     if (!ksp->guess_zero) {
678:       if (!ksp->truediagonal) {
679:         VecDuplicate(ksp->diagonal,&ksp->truediagonal);
680:         VecCopy(ksp->diagonal,ksp->truediagonal);
681:         VecReciprocal(ksp->truediagonal);
682:       }
683:       VecPointwiseMult(ksp->vec_sol,ksp->vec_sol,ksp->truediagonal);
684:     }
685:   }
686:   PCPreSolve(ksp->pc,ksp);

688:   if (ksp->guess_zero) { VecSet(ksp->vec_sol,0.0);}
689:   if (ksp->guess_knoll) { /* The Knoll trick is independent on the KSPGuess specified */
690:     PCApply(ksp->pc,ksp->vec_rhs,ksp->vec_sol);
691:     KSP_RemoveNullSpace(ksp,ksp->vec_sol);
692:     ksp->guess_zero = PETSC_FALSE;
693:   }

695:   /* can we mark the initial guess as zero for this solve? */
696:   guess_zero = ksp->guess_zero;
697:   if (!ksp->guess_zero) {
698:     PetscReal norm;

700:     VecNormAvailable(ksp->vec_sol,NORM_2,&flg,&norm);
701:     if (flg && !norm) ksp->guess_zero = PETSC_TRUE;
702:   }
703:   if (ksp->transpose_solve) {
704:     MatGetNullSpace(pmat,&nullsp);
705:   } else {
706:     MatGetTransposeNullSpace(pmat,&nullsp);
707:   }
708:   if (nullsp) {
709:     VecDuplicate(ksp->vec_rhs,&btmp);
710:     VecCopy(ksp->vec_rhs,btmp);
711:     MatNullSpaceRemove(nullsp,btmp);
712:     vec_rhs      = ksp->vec_rhs;
713:     ksp->vec_rhs = btmp;
714:   }
715:   VecLockReadPush(ksp->vec_rhs);
716:   if (ksp->reason == KSP_DIVERGED_PC_FAILED) {
717:     VecSetInf(ksp->vec_sol);
718:   }
719:   (*ksp->ops->solve)(ksp);

721:   VecLockReadPop(ksp->vec_rhs);
722:   if (nullsp) {
723:     ksp->vec_rhs = vec_rhs;
724:     VecDestroy(&btmp);
725:   }

727:   ksp->guess_zero = guess_zero;

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

732:   if (ksp->viewReason) {
733:     PetscViewerPushFormat(ksp->viewerReason,ksp->formatReason);
734:     KSPConvergedReasonView(ksp, ksp->viewerReason);
735:     PetscViewerPopFormat(ksp->viewerReason);
736:   }
737:   PCPostSolve(ksp->pc,ksp);

739:   /* diagonal scale solution if called for */
740:   if (ksp->dscale) {
741:     VecPointwiseMult(ksp->vec_sol,ksp->vec_sol,ksp->diagonal);
742:     /* unscale right hand side and matrix */
743:     if (ksp->dscalefix) {
744:       Mat mat,pmat;

746:       VecReciprocal(ksp->diagonal);
747:       VecPointwiseMult(ksp->vec_rhs,ksp->vec_rhs,ksp->diagonal);
748:       PCGetOperators(ksp->pc,&mat,&pmat);
749:       MatDiagonalScale(pmat,ksp->diagonal,ksp->diagonal);
750:       if (mat != pmat) {MatDiagonalScale(mat,ksp->diagonal,ksp->diagonal);}
751:       VecReciprocal(ksp->diagonal);
752:       ksp->dscalefix2 = PETSC_TRUE;
753:     }
754:   }
755:   PetscLogEventEnd(KSP_Solve,ksp,ksp->vec_rhs,ksp->vec_sol,0);
756:   if (ksp->guess) {
757:     KSPGuessUpdate(ksp->guess,ksp->vec_rhs,ksp->vec_sol);
758:   }
759:   if (ksp->postsolve) {
760:     (*ksp->postsolve)(ksp,ksp->vec_rhs,ksp->vec_sol,ksp->postctx);
761:   }

763:   PCGetOperators(ksp->pc,&mat,&pmat);
764:   if (ksp->viewEV)       {KSPViewEigenvalues_Internal(ksp, PETSC_FALSE, ksp->viewerEV,    ksp->formatEV);}
765:   if (ksp->viewEVExp)    {KSPViewEigenvalues_Internal(ksp, PETSC_TRUE,  ksp->viewerEVExp, ksp->formatEVExp);}
766:   if (ksp->viewSV)       {KSPViewSingularvalues_Internal(ksp, ksp->viewerSV, ksp->formatSV);}
767:   if (ksp->viewFinalRes) {KSPViewFinalResidual_Internal(ksp, ksp->viewerFinalRes, ksp->formatFinalRes);}
768:   if (ksp->viewMat)      {ObjectView((PetscObject) mat,           ksp->viewerMat,    ksp->formatMat);}
769:   if (ksp->viewPMat)     {ObjectView((PetscObject) pmat,          ksp->viewerPMat,   ksp->formatPMat);}
770:   if (ksp->viewRhs)      {ObjectView((PetscObject) ksp->vec_rhs,  ksp->viewerRhs,    ksp->formatRhs);}
771:   if (ksp->viewSol)      {ObjectView((PetscObject) ksp->vec_sol,  ksp->viewerSol,    ksp->formatSol);}
772:   if (ksp->view)         {ObjectView((PetscObject) ksp,           ksp->viewer,       ksp->format);}
773:   if (ksp->viewDScale)   {ObjectView((PetscObject) ksp->diagonal, ksp->viewerDScale, ksp->formatDScale);}
774:   if (ksp->viewMatExp)   {
775:     Mat A, B;

777:     PCGetOperators(ksp->pc, &A, NULL);
778:     if (ksp->transpose_solve) {
779:       Mat AT;

781:       MatCreateTranspose(A, &AT);
782:       MatComputeOperator(AT, MATAIJ, &B);
783:       MatDestroy(&AT);
784:     } else {
785:       MatComputeOperator(A, MATAIJ, &B);
786:     }
787:     ObjectView((PetscObject) B, ksp->viewerMatExp, ksp->formatMatExp);
788:     MatDestroy(&B);
789:   }
790:   if (ksp->viewPOpExp)   {
791:     Mat B;

793:     KSPComputeOperator(ksp, MATAIJ, &B);
794:     ObjectView((PetscObject) B, ksp->viewerPOpExp, ksp->formatPOpExp);
795:     MatDestroy(&B);
796:   }

798:   if (inXisinB) {
799:     VecCopy(x,b);
800:     VecDestroy(&x);
801:   }
802:   PetscObjectSAWsBlock((PetscObject)ksp);
803:   if (ksp->errorifnotconverged && ksp->reason < 0 && ksp->reason != KSP_DIVERGED_ITS) {
804:     if (ksp->reason == KSP_DIVERGED_PC_FAILED) {
805:       PCFailedReason reason;
806:       PCGetFailedReason(ksp->pc,&reason);
807:       SETERRQ2(comm,PETSC_ERR_NOT_CONVERGED,"KSPSolve has not converged, reason %s PC failed due to %s",KSPConvergedReasons[ksp->reason],PCFailedReasons[reason]);
808:     } else SETERRQ1(comm,PETSC_ERR_NOT_CONVERGED,"KSPSolve has not converged, reason %s",KSPConvergedReasons[ksp->reason]);
809:   }
810:   return(0);
811: }

813: /*@
814:    KSPSolve - Solves linear system.

816:    Collective on ksp

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

823:    Options Database Keys:
824: +  -ksp_view_eigenvalues - compute preconditioned operators eigenvalues
825: .  -ksp_view_eigenvalues_explicit - compute the eigenvalues by forming the dense operator and using LAPACK
826: .  -ksp_view_mat binary - save matrix to the default binary viewer
827: .  -ksp_view_pmat binary - save matrix used to build preconditioner to the default binary viewer
828: .  -ksp_view_rhs binary - save right hand side vector to the default binary viewer
829: .  -ksp_view_solution binary - save computed solution vector to the default binary viewer
830:            (can be read later with src/ksp/tutorials/ex10.c for testing solvers)
831: .  -ksp_view_mat_explicit - for matrix-free operators, computes the matrix entries and views them
832: .  -ksp_view_preconditioned_operator_explicit - computes the product of the preconditioner and matrix as an explicit matrix and views it
833: .  -ksp_converged_reason - print reason for converged or diverged, also prints number of iterations
834: .  -ksp_view_final_residual - print 2-norm of true linear system residual at the end of the solution process
835: -  -ksp_view - print the ksp data structure at the end of the system solution

837:    Notes:

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

841:    The operator is specified with KSPSetOperators().

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

846:    If you provide a matrix that has a MatSetNullSpace() and MatSetTransposeNullSpace() this will use that information to solve singular systems
847:    in the least squares sense with a norm minimizing solution.
848: $
849: $                   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()
850: $
851: $    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
852: $    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
853: $    direction thus the solution which is a linear combination of the search directions has no component in the nullspace(A).
854: $
855: $    We recommend always using GMRES for such singular systems.
856: $    If nullspace(A) = nullspace(A') (note symmetric matrices always satisfy this property) then both left and right preconditioning will work
857: $    If nullspace(A) != nullspace(A') then left preconditioning will work but right preconditioning may not work (or it may).

859:    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
860:        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
861:        such as diagonal scaling we cannot apply the inverse of the preconditioner to a vector and thus cannot compute the nullspace(AB).


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

869:    Understanding Convergence:
870:    The routines KSPMonitorSet(), KSPComputeEigenvalues(), and
871:    KSPComputeEigenvaluesExplicitly() provide information on additional
872:    options to monitor convergence and print eigenvalue information.

874:    Level: beginner

876: .seealso: KSPCreate(), KSPSetUp(), KSPDestroy(), KSPSetTolerances(), KSPConvergedDefault(),
877:           KSPSolveTranspose(), KSPGetIterationNumber(), MatNullSpaceCreate(), MatSetNullSpace(), MatSetTransposeNullSpace(), KSP,
878:           KSPConvergedReasonView()
879: @*/
880: PetscErrorCode KSPSolve(KSP ksp,Vec b,Vec x)
881: {

888:   ksp->transpose_solve = PETSC_FALSE;
889:   KSPSolve_Private(ksp,b,x);
890:   return(0);
891: }

893: /*@
894:    KSPSolveTranspose - Solves the transpose of a linear system.

896:    Collective on ksp

898:    Input Parameters:
899: +  ksp - iterative context obtained from KSPCreate()
900: .  b - right hand side vector
901: -  x - solution vector

903:    Notes:
904:     For complex numbers this solve the non-Hermitian transpose system.

906:    Developer Notes:
907:     We need to implement a KSPSolveHermitianTranspose()

909:    Level: developer

911: .seealso: KSPCreate(), KSPSetUp(), KSPDestroy(), KSPSetTolerances(), KSPConvergedDefault(),
912:           KSPSolve(), KSP
913: @*/
914: PetscErrorCode KSPSolveTranspose(KSP ksp,Vec b,Vec x)
915: {

922:   ksp->transpose_solve = PETSC_TRUE;
923:   KSPSolve_Private(ksp,b,x);
924:   return(0);
925: }

927: static PetscErrorCode KSPViewFinalMatResidual_Internal(KSP ksp, Mat B, Mat X, PetscViewer viewer, PetscViewerFormat format, PetscInt shift)
928: {
929:   Mat            A, R;
930:   PetscReal      *norms;
931:   PetscInt       i, N;
932:   PetscBool      flg;

936:   PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &flg);
937:   if (flg) {
938:     PCGetOperators(ksp->pc, &A, NULL);
939:     MatMatMult(A, X, MAT_INITIAL_MATRIX, PETSC_DEFAULT, &R);
940:     MatAYPX(R, -1.0, B, SAME_NONZERO_PATTERN);
941:     MatGetSize(R, NULL, &N);
942:     PetscMalloc1(N, &norms);
943:     MatGetColumnNorms(R, NORM_2, norms);
944:     MatDestroy(&R);
945:     for (i = 0; i < N; ++i) {
946:       PetscViewerASCIIPrintf(viewer, "%s #%D %g\n", i == 0 ? "KSP final norm of residual" : "                          ", shift + i, (double)norms[i]);
947:     }
948:     PetscFree(norms);
949:   }
950:   return(0);
951: }

953: /*@
954:      KSPMatSolve - Solves a linear system with multiple right-hand sides stored as a MATDENSE. Unlike KSPSolve(), B and X must be different matrices.

956:    Input Parameters:
957: +     ksp - iterative context
958: -     B - block of right-hand sides

960:    Output Parameter:
961: .     X - block of solutions

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

966:    Level: intermediate

968: .seealso:  KSPSolve(), MatMatSolve(), MATDENSE, KSPHPDDM, PCBJACOBI, PCASM
969: @*/
970: PetscErrorCode KSPMatSolve(KSP ksp, Mat B, Mat X)
971: {
972:   Mat            A, vB, vX;
973:   Vec            cb, cx;
974:   PetscInt       m1, M1, m2, M2, n1, N1, n2, N2, Bbn = PETSC_DECIDE;
975:   PetscBool      match;

984:   if (!B->assembled) SETERRQ(PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Not for unassembled matrix");
985:   MatCheckPreallocated(X, 3);
986:   if (!X->assembled) {
987:     MatSetOption(X, MAT_NO_OFF_PROC_ENTRIES, PETSC_TRUE);
988:     MatAssemblyBegin(X, MAT_FINAL_ASSEMBLY);
989:     MatAssemblyEnd(X, MAT_FINAL_ASSEMBLY);
990:   }
991:   if (B == X) SETERRQ(PetscObjectComm((PetscObject)ksp), PETSC_ERR_ARG_IDN, "B and X must be different matrices");
992:   KSPGetOperators(ksp, &A, NULL);
993:   MatGetLocalSize(A, &m1, NULL);
994:   MatGetLocalSize(B, &m2, &n2);
995:   MatGetSize(A, &M1, NULL);
996:   MatGetSize(B, &M2, &N2);
997:   if (m1 != m2 || M1 != M2) SETERRQ4(PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Cannot use a block of right-hand sides with (m2,M2) = (%D,%D) for a linear system with (m1,M1) = (%D,%D)", m2, M2, m1, M1);
998:   MatGetLocalSize(X, &m1, &n1);
999:   MatGetSize(X, &M1, &N1);
1000:   if (m1 != m2 || M1 != M2 || n1 != n2 || N1 != N2) SETERRQ8(PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Incompatible block of right-hand sides (m2,M2)x(n2,N2) = (%D,%D)x(%D,%D) and solutions (m1,M1)x(n1,N1) = (%D,%D)x(%D,%D)", m2, M2, n2, N2, m1, M1, n1, N1);
1001:   PetscObjectBaseTypeCompareAny((PetscObject)B, &match, MATSEQDENSE, MATMPIDENSE, "");
1002:   if (!match) SETERRQ(PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Provided block of right-hand sides not stored in a dense Mat");
1003:   PetscObjectBaseTypeCompareAny((PetscObject)X, &match, MATSEQDENSE, MATMPIDENSE, "");
1004:   if (!match) SETERRQ(PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Provided block of solutions not stored in a dense Mat");
1005:   KSPSetUp(ksp);
1006:   KSPSetUpOnBlocks(ksp);
1007:   if (ksp->ops->matsolve) {
1008:     if (ksp->guess_zero) {
1009:       MatZeroEntries(X);
1010:     }
1011:     PetscLogEventBegin(KSP_MatSolve, ksp, B, X, 0);
1012:     KSPGetMatSolveBlockSize(ksp, &Bbn);
1013:     /* by default, do a single solve with all columns */
1014:     if (Bbn == PETSC_DECIDE) Bbn = N2;
1015:     else if (Bbn < 1)        SETERRQ1(PetscObjectComm((PetscObject)ksp), PETSC_ERR_ARG_OUTOFRANGE, "KSPMatSolve() block size %D must be positive", Bbn);
1016:     PetscInfo2(ksp, "KSP type %s solving using blocks of width at most %D\n", ((PetscObject)ksp)->type_name, Bbn);
1017:     /* if -ksp_matsolve_block_size is greater than the actual number of columns, do a single solve with all columns */
1018:     if (Bbn >= N2) {
1019:       (*ksp->ops->matsolve)(ksp, B, X);
1020:       if (ksp->viewFinalRes) {
1021:         KSPViewFinalMatResidual_Internal(ksp, B, X, ksp->viewerFinalRes, ksp->formatFinalRes, 0);
1022:       }
1023:       if (ksp->viewReason) {
1024:         PetscViewerPushFormat(ksp->viewerReason,PETSC_VIEWER_DEFAULT);
1025:         KSPConvergedReasonView(ksp, ksp->viewerReason);
1026:         PetscViewerPopFormat(ksp->viewerReason);
1027:       }
1028:     } else {
1029:       for (n2 = 0; n2 < N2; n2 += Bbn) {
1030:         MatDenseGetSubMatrix(B, n2, PetscMin(n2+Bbn, N2), &vB);
1031:         MatDenseGetSubMatrix(X, n2, PetscMin(n2+Bbn, N2), &vX);
1032:         (*ksp->ops->matsolve)(ksp, vB, vX);
1033:         if (ksp->viewFinalRes) {
1034:           KSPViewFinalMatResidual_Internal(ksp, vB, vX, ksp->viewerFinalRes, ksp->formatFinalRes, n2);
1035:         }
1036:         if (ksp->viewReason) {
1037:           PetscViewerPushFormat(ksp->viewerReason,PETSC_VIEWER_DEFAULT);
1038:           KSPConvergedReasonView(ksp, ksp->viewerReason);
1039:           PetscViewerPopFormat(ksp->viewerReason);
1040:         }
1041:         MatDenseRestoreSubMatrix(B, &vB);
1042:         MatDenseRestoreSubMatrix(X, &vX);
1043:       }
1044:     }
1045:     if (ksp->view) {
1046:       KSPView(ksp, ksp->viewer);
1047:     }
1048:     PetscLogEventEnd(KSP_MatSolve, ksp, B, X, 0);
1049:   } else {
1050:     PetscInfo1(ksp, "KSP type %s solving column by column\n", ((PetscObject)ksp)->type_name);
1051:     for (n2 = 0; n2 < N2; ++n2) {
1052:       MatDenseGetColumnVecRead(B, n2, &cb);
1053:       MatDenseGetColumnVecWrite(X, n2, &cx);
1054:       KSPSolve(ksp, cb, cx);
1055:       MatDenseRestoreColumnVecWrite(X, n2, &cx);
1056:       MatDenseRestoreColumnVecRead(B, n2, &cb);
1057:     }
1058:   }
1059:   return(0);
1060: }

1062: /*@
1063:      KSPSetMatSolveBlockSize - Sets the maximum number of columns treated simultaneously in KSPMatSolve().

1065:     Logically collective

1067:    Input Parameters:
1068: +     ksp - iterative context
1069: -     bs - block size

1071:    Level: advanced

1073: .seealso:  KSPMatSolve(), KSPGetMatSolveBlockSize(), -mat_mumps_icntl_27, -matmatmult_Bbn
1074: @*/
1075: PetscErrorCode KSPSetMatSolveBlockSize(KSP ksp, PetscInt bs)
1076: {

1082:   PetscTryMethod(ksp, "KSPSetMatSolveBlockSize_C", (KSP, PetscInt), (ksp, bs));
1083:   return(0);
1084: }

1086: /*@
1087:      KSPGetMatSolveBlockSize - Gets the maximum number of columns treated simultaneously in KSPMatSolve().

1089:    Input Parameter:
1090: .     ksp - iterative context

1092:    Output Parameter:
1093: .     bs - block size

1095:    Level: advanced

1097: .seealso:  KSPMatSolve(), KSPSetMatSolveBlockSize(), -mat_mumps_icntl_27, -matmatmult_Bbn
1098: @*/
1099: PetscErrorCode KSPGetMatSolveBlockSize(KSP ksp, PetscInt *bs)
1100: {

1105:   *bs = PETSC_DECIDE;
1106:   PetscTryMethod(ksp, "KSPGetMatSolveBlockSize_C", (KSP, PetscInt*), (ksp, bs));
1107:   return(0);
1108: }

1110: /*@
1111:    KSPResetViewers - Resets all the viewers set from the options database during KSPSetFromOptions()

1113:    Collective on ksp

1115:    Input Parameter:
1116: .  ksp - iterative context obtained from KSPCreate()

1118:    Level: beginner

1120: .seealso: KSPCreate(), KSPSetUp(), KSPSolve(), KSPSetFromOptions(), KSP
1121: @*/
1122: PetscErrorCode  KSPResetViewers(KSP ksp)
1123: {

1128:   if (!ksp) return(0);
1129:   PetscViewerDestroy(&ksp->viewer);
1130:   PetscViewerDestroy(&ksp->viewerPre);
1131:   PetscViewerDestroy(&ksp->viewerReason);
1132:   PetscViewerDestroy(&ksp->viewerMat);
1133:   PetscViewerDestroy(&ksp->viewerPMat);
1134:   PetscViewerDestroy(&ksp->viewerRhs);
1135:   PetscViewerDestroy(&ksp->viewerSol);
1136:   PetscViewerDestroy(&ksp->viewerMatExp);
1137:   PetscViewerDestroy(&ksp->viewerEV);
1138:   PetscViewerDestroy(&ksp->viewerSV);
1139:   PetscViewerDestroy(&ksp->viewerEVExp);
1140:   PetscViewerDestroy(&ksp->viewerFinalRes);
1141:   PetscViewerDestroy(&ksp->viewerPOpExp);
1142:   PetscViewerDestroy(&ksp->viewerDScale);
1143:   ksp->view         = PETSC_FALSE;
1144:   ksp->viewPre      = PETSC_FALSE;
1145:   ksp->viewReason   = PETSC_FALSE;
1146:   ksp->viewMat      = PETSC_FALSE;
1147:   ksp->viewPMat     = PETSC_FALSE;
1148:   ksp->viewRhs      = PETSC_FALSE;
1149:   ksp->viewSol      = PETSC_FALSE;
1150:   ksp->viewMatExp   = PETSC_FALSE;
1151:   ksp->viewEV       = PETSC_FALSE;
1152:   ksp->viewSV       = PETSC_FALSE;
1153:   ksp->viewEVExp    = PETSC_FALSE;
1154:   ksp->viewFinalRes = PETSC_FALSE;
1155:   ksp->viewPOpExp   = PETSC_FALSE;
1156:   ksp->viewDScale   = PETSC_FALSE;
1157:   return(0);
1158: }

1160: /*@
1161:    KSPReset - Resets a KSP context to the kspsetupcalled = 0 state and removes any allocated Vecs and Mats

1163:    Collective on ksp

1165:    Input Parameter:
1166: .  ksp - iterative context obtained from KSPCreate()

1168:    Level: beginner

1170: .seealso: KSPCreate(), KSPSetUp(), KSPSolve(), KSP
1171: @*/
1172: PetscErrorCode  KSPReset(KSP ksp)
1173: {

1178:   if (!ksp) return(0);
1179:   if (ksp->ops->reset) {
1180:     (*ksp->ops->reset)(ksp);
1181:   }
1182:   if (ksp->pc) {PCReset(ksp->pc);}
1183:   if (ksp->guess) {
1184:     KSPGuess guess = ksp->guess;
1185:     if (guess->ops->reset) { (*guess->ops->reset)(guess); }
1186:   }
1187:   VecDestroyVecs(ksp->nwork,&ksp->work);
1188:   VecDestroy(&ksp->vec_rhs);
1189:   VecDestroy(&ksp->vec_sol);
1190:   VecDestroy(&ksp->diagonal);
1191:   VecDestroy(&ksp->truediagonal);

1193:   KSPResetViewers(ksp);

1195:   ksp->setupstage = KSP_SETUP_NEW;
1196:   return(0);
1197: }

1199: /*@
1200:    KSPDestroy - Destroys KSP context.

1202:    Collective on ksp

1204:    Input Parameter:
1205: .  ksp - iterative context obtained from KSPCreate()

1207:    Level: beginner

1209: .seealso: KSPCreate(), KSPSetUp(), KSPSolve(), KSP
1210: @*/
1211: PetscErrorCode  KSPDestroy(KSP *ksp)
1212: {
1214:   PC             pc;

1217:   if (!*ksp) return(0);
1219:   if (--((PetscObject)(*ksp))->refct > 0) {*ksp = NULL; return(0);}

1221:   PetscObjectSAWsViewOff((PetscObject)*ksp);

1223:   /*
1224:    Avoid a cascading call to PCReset(ksp->pc) from the following call:
1225:    PCReset() shouldn't be called from KSPDestroy() as it is unprotected by pc's
1226:    refcount (and may be shared, e.g., by other ksps).
1227:    */
1228:   pc         = (*ksp)->pc;
1229:   (*ksp)->pc = NULL;
1230:   KSPReset((*ksp));
1231:   (*ksp)->pc = pc;
1232:   if ((*ksp)->ops->destroy) {(*(*ksp)->ops->destroy)(*ksp);}

1234:   KSPGuessDestroy(&(*ksp)->guess);
1235:   DMDestroy(&(*ksp)->dm);
1236:   PCDestroy(&(*ksp)->pc);
1237:   PetscFree((*ksp)->res_hist_alloc);
1238:   if ((*ksp)->convergeddestroy) {
1239:     (*(*ksp)->convergeddestroy)((*ksp)->cnvP);
1240:   }
1241:   KSPMonitorCancel((*ksp));
1242:   PetscViewerDestroy(&(*ksp)->eigviewer);
1243:   PetscHeaderDestroy(ksp);
1244:   return(0);
1245: }

1247: /*@
1248:     KSPSetPCSide - Sets the preconditioning side.

1250:     Logically Collective on ksp

1252:     Input Parameter:
1253: .   ksp - iterative context obtained from KSPCreate()

1255:     Output Parameter:
1256: .   side - the preconditioning side, where side is one of
1257: .vb
1258:       PC_LEFT - left preconditioning (default)
1259:       PC_RIGHT - right preconditioning
1260:       PC_SYMMETRIC - symmetric preconditioning
1261: .ve

1263:     Options Database Keys:
1264: .   -ksp_pc_side <right,left,symmetric>

1266:     Notes:
1267:     Left preconditioning is used by default for most Krylov methods except KSPFGMRES which only supports right preconditioning.

1269:     For methods changing the side of the preconditioner changes the norm type that is used, see KSPSetNormType().

1271:     Symmetric preconditioning is currently available only for the KSPQCG method. Note, however, that
1272:     symmetric preconditioning can be emulated by using either right or left
1273:     preconditioning and a pre or post processing step.

1275:     Setting the PC side often affects the default norm type.  See KSPSetNormType() for details.

1277:     Level: intermediate

1279: .seealso: KSPGetPCSide(), KSPSetNormType(), KSPGetNormType(), KSP
1280: @*/
1281: PetscErrorCode  KSPSetPCSide(KSP ksp,PCSide side)
1282: {
1286:   ksp->pc_side = ksp->pc_side_set = side;
1287:   return(0);
1288: }

1290: /*@
1291:     KSPGetPCSide - Gets the preconditioning side.

1293:     Not Collective

1295:     Input Parameter:
1296: .   ksp - iterative context obtained from KSPCreate()

1298:     Output Parameter:
1299: .   side - the preconditioning side, where side is one of
1300: .vb
1301:       PC_LEFT - left preconditioning (default)
1302:       PC_RIGHT - right preconditioning
1303:       PC_SYMMETRIC - symmetric preconditioning
1304: .ve

1306:     Level: intermediate

1308: .seealso: KSPSetPCSide(), KSP
1309: @*/
1310: PetscErrorCode  KSPGetPCSide(KSP ksp,PCSide *side)
1311: {

1317:   KSPSetUpNorms_Private(ksp,PETSC_TRUE,&ksp->normtype,&ksp->pc_side);
1318:   *side = ksp->pc_side;
1319:   return(0);
1320: }

1322: /*@
1323:    KSPGetTolerances - Gets the relative, absolute, divergence, and maximum
1324:    iteration tolerances used by the default KSP convergence tests.

1326:    Not Collective

1328:    Input Parameter:
1329: .  ksp - the Krylov subspace context

1331:    Output Parameters:
1332: +  rtol - the relative convergence tolerance
1333: .  abstol - the absolute convergence tolerance
1334: .  dtol - the divergence tolerance
1335: -  maxits - maximum number of iterations

1337:    Notes:
1338:    The user can specify NULL for any parameter that is not needed.

1340:    Level: intermediate

1342:            maximum, iterations

1344: .seealso: KSPSetTolerances(), KSP
1345: @*/
1346: PetscErrorCode  KSPGetTolerances(KSP ksp,PetscReal *rtol,PetscReal *abstol,PetscReal *dtol,PetscInt *maxits)
1347: {
1350:   if (abstol) *abstol = ksp->abstol;
1351:   if (rtol) *rtol = ksp->rtol;
1352:   if (dtol) *dtol = ksp->divtol;
1353:   if (maxits) *maxits = ksp->max_it;
1354:   return(0);
1355: }

1357: /*@
1358:    KSPSetTolerances - Sets the relative, absolute, divergence, and maximum
1359:    iteration tolerances used by the default KSP convergence testers.

1361:    Logically Collective on ksp

1363:    Input Parameters:
1364: +  ksp - the Krylov subspace context
1365: .  rtol - the relative convergence tolerance, relative decrease in the (possibly preconditioned) residual norm
1366: .  abstol - the absolute convergence tolerance   absolute size of the (possibly preconditioned) residual norm
1367: .  dtol - the divergence tolerance,   amount (possibly preconditioned) residual norm can increase before KSPConvergedDefault() concludes that the method is diverging
1368: -  maxits - maximum number of iterations to use

1370:    Options Database Keys:
1371: +  -ksp_atol <abstol> - Sets abstol
1372: .  -ksp_rtol <rtol> - Sets rtol
1373: .  -ksp_divtol <dtol> - Sets dtol
1374: -  -ksp_max_it <maxits> - Sets maxits

1376:    Notes:
1377:    Use PETSC_DEFAULT to retain the default value of any of the tolerances.

1379:    See KSPConvergedDefault() for details how these parameters are used in the default convergence test.  See also KSPSetConvergenceTest()
1380:    for setting user-defined stopping criteria.

1382:    Level: intermediate

1384:            convergence, maximum, iterations

1386: .seealso: KSPGetTolerances(), KSPConvergedDefault(), KSPSetConvergenceTest(), KSP
1387: @*/
1388: PetscErrorCode  KSPSetTolerances(KSP ksp,PetscReal rtol,PetscReal abstol,PetscReal dtol,PetscInt maxits)
1389: {

1397:   if (rtol != PETSC_DEFAULT) {
1398:     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);
1399:     ksp->rtol = rtol;
1400:   }
1401:   if (abstol != PETSC_DEFAULT) {
1402:     if (abstol < 0.0) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Absolute tolerance %g must be non-negative",(double)abstol);
1403:     ksp->abstol = abstol;
1404:   }
1405:   if (dtol != PETSC_DEFAULT) {
1406:     if (dtol < 0.0) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Divergence tolerance %g must be larger than 1.0",(double)dtol);
1407:     ksp->divtol = dtol;
1408:   }
1409:   if (maxits != PETSC_DEFAULT) {
1410:     if (maxits < 0) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Maximum number of iterations %D must be non-negative",maxits);
1411:     ksp->max_it = maxits;
1412:   }
1413:   return(0);
1414: }

1416: /*@
1417:    KSPSetInitialGuessNonzero - Tells the iterative solver that the
1418:    initial guess is nonzero; otherwise KSP assumes the initial guess
1419:    is to be zero (and thus zeros it out before solving).

1421:    Logically Collective on ksp

1423:    Input Parameters:
1424: +  ksp - iterative context obtained from KSPCreate()
1425: -  flg - PETSC_TRUE indicates the guess is non-zero, PETSC_FALSE indicates the guess is zero

1427:    Options database keys:
1428: .  -ksp_initial_guess_nonzero : use nonzero initial guess; this takes an optional truth value (0/1/no/yes/true/false)

1430:    Level: beginner

1432:    Notes:
1433:     If this is not called the X vector is zeroed in the call to KSPSolve().

1435: .seealso: KSPGetInitialGuessNonzero(), KSPSetGuessType(), KSPGuessType, KSP
1436: @*/
1437: PetscErrorCode  KSPSetInitialGuessNonzero(KSP ksp,PetscBool flg)
1438: {
1442:   ksp->guess_zero = (PetscBool) !(int)flg;
1443:   return(0);
1444: }

1446: /*@
1447:    KSPGetInitialGuessNonzero - Determines whether the KSP solver is using
1448:    a zero initial guess.

1450:    Not Collective

1452:    Input Parameter:
1453: .  ksp - iterative context obtained from KSPCreate()

1455:    Output Parameter:
1456: .  flag - PETSC_TRUE if guess is nonzero, else PETSC_FALSE

1458:    Level: intermediate

1460: .seealso: KSPSetInitialGuessNonzero(), KSP
1461: @*/
1462: PetscErrorCode  KSPGetInitialGuessNonzero(KSP ksp,PetscBool  *flag)
1463: {
1467:   if (ksp->guess_zero) *flag = PETSC_FALSE;
1468:   else *flag = PETSC_TRUE;
1469:   return(0);
1470: }

1472: /*@
1473:    KSPSetErrorIfNotConverged - Causes KSPSolve() to generate an error if the solver has not converged.

1475:    Logically Collective on ksp

1477:    Input Parameters:
1478: +  ksp - iterative context obtained from KSPCreate()
1479: -  flg - PETSC_TRUE indicates you want the error generated

1481:    Options database keys:
1482: .  -ksp_error_if_not_converged : this takes an optional truth value (0/1/no/yes/true/false)

1484:    Level: intermediate

1486:    Notes:
1487:     Normally PETSc continues if a linear solver fails to converge, you can call KSPGetConvergedReason() after a KSPSolve()
1488:     to determine if it has converged.


1491: .seealso: KSPGetErrorIfNotConverged(), KSP
1492: @*/
1493: PetscErrorCode  KSPSetErrorIfNotConverged(KSP ksp,PetscBool flg)
1494: {
1498:   ksp->errorifnotconverged = flg;
1499:   return(0);
1500: }

1502: /*@
1503:    KSPGetErrorIfNotConverged - Will KSPSolve() generate an error if the solver does not converge?

1505:    Not Collective

1507:    Input Parameter:
1508: .  ksp - iterative context obtained from KSPCreate()

1510:    Output Parameter:
1511: .  flag - PETSC_TRUE if it will generate an error, else PETSC_FALSE

1513:    Level: intermediate

1515: .seealso: KSPSetErrorIfNotConverged(), KSP
1516: @*/
1517: PetscErrorCode  KSPGetErrorIfNotConverged(KSP ksp,PetscBool  *flag)
1518: {
1522:   *flag = ksp->errorifnotconverged;
1523:   return(0);
1524: }

1526: /*@
1527:    KSPSetInitialGuessKnoll - Tells the iterative solver to use PCApply(pc,b,..) to compute the initial guess (The Knoll trick)

1529:    Logically Collective on ksp

1531:    Input Parameters:
1532: +  ksp - iterative context obtained from KSPCreate()
1533: -  flg - PETSC_TRUE or PETSC_FALSE

1535:    Level: advanced

1537:    Developer Note: the Knoll trick is not currently implemented using the KSPGuess class

1539: .seealso: KSPGetInitialGuessKnoll(), KSPSetInitialGuessNonzero(), KSPGetInitialGuessNonzero(), KSP
1540: @*/
1541: PetscErrorCode  KSPSetInitialGuessKnoll(KSP ksp,PetscBool flg)
1542: {
1546:   ksp->guess_knoll = flg;
1547:   return(0);
1548: }

1550: /*@
1551:    KSPGetInitialGuessKnoll - Determines whether the KSP solver is using the Knoll trick (using PCApply(pc,b,...) to compute
1552:      the initial guess

1554:    Not Collective

1556:    Input Parameter:
1557: .  ksp - iterative context obtained from KSPCreate()

1559:    Output Parameter:
1560: .  flag - PETSC_TRUE if using Knoll trick, else PETSC_FALSE

1562:    Level: advanced

1564: .seealso: KSPSetInitialGuessKnoll(), KSPSetInitialGuessNonzero(), KSPGetInitialGuessNonzero(), KSP
1565: @*/
1566: PetscErrorCode  KSPGetInitialGuessKnoll(KSP ksp,PetscBool  *flag)
1567: {
1571:   *flag = ksp->guess_knoll;
1572:   return(0);
1573: }

1575: /*@
1576:    KSPGetComputeSingularValues - Gets the flag indicating whether the extreme singular
1577:    values will be calculated via a Lanczos or Arnoldi process as the linear
1578:    system is solved.

1580:    Not Collective

1582:    Input Parameter:
1583: .  ksp - iterative context obtained from KSPCreate()

1585:    Output Parameter:
1586: .  flg - PETSC_TRUE or PETSC_FALSE

1588:    Options Database Key:
1589: .  -ksp_monitor_singular_value - Activates KSPSetComputeSingularValues()

1591:    Notes:
1592:    Currently this option is not valid for all iterative methods.

1594:    Many users may just want to use the monitoring routine
1595:    KSPMonitorSingularValue() (which can be set with option -ksp_monitor_singular_value)
1596:    to print the singular values at each iteration of the linear solve.

1598:    Level: advanced

1600: .seealso: KSPComputeExtremeSingularValues(), KSPMonitorSingularValue(), KSP
1601: @*/
1602: PetscErrorCode  KSPGetComputeSingularValues(KSP ksp,PetscBool  *flg)
1603: {
1607:   *flg = ksp->calc_sings;
1608:   return(0);
1609: }

1611: /*@
1612:    KSPSetComputeSingularValues - Sets a flag so that the extreme singular
1613:    values will be calculated via a Lanczos or Arnoldi process as the linear
1614:    system is solved.

1616:    Logically Collective on ksp

1618:    Input Parameters:
1619: +  ksp - iterative context obtained from KSPCreate()
1620: -  flg - PETSC_TRUE or PETSC_FALSE

1622:    Options Database Key:
1623: .  -ksp_monitor_singular_value - Activates KSPSetComputeSingularValues()

1625:    Notes:
1626:    Currently this option is not valid for all iterative methods.

1628:    Many users may just want to use the monitoring routine
1629:    KSPMonitorSingularValue() (which can be set with option -ksp_monitor_singular_value)
1630:    to print the singular values at each iteration of the linear solve.

1632:    Level: advanced

1634: .seealso: KSPComputeExtremeSingularValues(), KSPMonitorSingularValue(), KSP
1635: @*/
1636: PetscErrorCode  KSPSetComputeSingularValues(KSP ksp,PetscBool flg)
1637: {
1641:   ksp->calc_sings = flg;
1642:   return(0);
1643: }

1645: /*@
1646:    KSPGetComputeEigenvalues - Gets the flag indicating that the extreme eigenvalues
1647:    values will be calculated via a Lanczos or Arnoldi process as the linear
1648:    system is solved.

1650:    Not Collective

1652:    Input Parameter:
1653: .  ksp - iterative context obtained from KSPCreate()

1655:    Output Parameter:
1656: .  flg - PETSC_TRUE or PETSC_FALSE

1658:    Notes:
1659:    Currently this option is not valid for all iterative methods.

1661:    Level: advanced

1663: .seealso: KSPComputeEigenvalues(), KSPComputeEigenvaluesExplicitly(), KSP
1664: @*/
1665: PetscErrorCode  KSPGetComputeEigenvalues(KSP ksp,PetscBool  *flg)
1666: {
1670:   *flg = ksp->calc_sings;
1671:   return(0);
1672: }

1674: /*@
1675:    KSPSetComputeEigenvalues - Sets a flag so that the extreme eigenvalues
1676:    values will be calculated via a Lanczos or Arnoldi process as the linear
1677:    system is solved.

1679:    Logically Collective on ksp

1681:    Input Parameters:
1682: +  ksp - iterative context obtained from KSPCreate()
1683: -  flg - PETSC_TRUE or PETSC_FALSE

1685:    Notes:
1686:    Currently this option is not valid for all iterative methods.

1688:    Level: advanced

1690: .seealso: KSPComputeEigenvalues(), KSPComputeEigenvaluesExplicitly(), KSP
1691: @*/
1692: PetscErrorCode  KSPSetComputeEigenvalues(KSP ksp,PetscBool flg)
1693: {
1697:   ksp->calc_sings = flg;
1698:   return(0);
1699: }

1701: /*@
1702:    KSPSetComputeRitz - Sets a flag so that the Ritz or harmonic Ritz pairs
1703:    will be calculated via a Lanczos or Arnoldi process as the linear
1704:    system is solved.

1706:    Logically Collective on ksp

1708:    Input Parameters:
1709: +  ksp - iterative context obtained from KSPCreate()
1710: -  flg - PETSC_TRUE or PETSC_FALSE

1712:    Notes:
1713:    Currently this option is only valid for the GMRES method.

1715:    Level: advanced

1717: .seealso: KSPComputeRitz(), KSP
1718: @*/
1719: PetscErrorCode  KSPSetComputeRitz(KSP ksp, PetscBool flg)
1720: {
1724:   ksp->calc_ritz = flg;
1725:   return(0);
1726: }

1728: /*@
1729:    KSPGetRhs - Gets the right-hand-side vector for the linear system to
1730:    be solved.

1732:    Not Collective

1734:    Input Parameter:
1735: .  ksp - iterative context obtained from KSPCreate()

1737:    Output Parameter:
1738: .  r - right-hand-side vector

1740:    Level: developer

1742: .seealso: KSPGetSolution(), KSPSolve(), KSP
1743: @*/
1744: PetscErrorCode  KSPGetRhs(KSP ksp,Vec *r)
1745: {
1749:   *r = ksp->vec_rhs;
1750:   return(0);
1751: }

1753: /*@
1754:    KSPGetSolution - Gets the location of the solution for the
1755:    linear system to be solved.  Note that this may not be where the solution
1756:    is stored during the iterative process; see KSPBuildSolution().

1758:    Not Collective

1760:    Input Parameters:
1761: .  ksp - iterative context obtained from KSPCreate()

1763:    Output Parameters:
1764: .  v - solution vector

1766:    Level: developer

1768: .seealso: KSPGetRhs(),  KSPBuildSolution(), KSPSolve(), KSP
1769: @*/
1770: PetscErrorCode  KSPGetSolution(KSP ksp,Vec *v)
1771: {
1775:   *v = ksp->vec_sol;
1776:   return(0);
1777: }

1779: /*@
1780:    KSPSetPC - Sets the preconditioner to be used to calculate the
1781:    application of the preconditioner on a vector.

1783:    Collective on ksp

1785:    Input Parameters:
1786: +  ksp - iterative context obtained from KSPCreate()
1787: -  pc   - the preconditioner object (can be NULL)

1789:    Notes:
1790:    Use KSPGetPC() to retrieve the preconditioner context.

1792:    Level: developer

1794: .seealso: KSPGetPC(), KSP
1795: @*/
1796: PetscErrorCode  KSPSetPC(KSP ksp,PC pc)
1797: {

1802:   if (pc) {
1805:   }
1806:   PetscObjectReference((PetscObject)pc);
1807:   PCDestroy(&ksp->pc);
1808:   ksp->pc = pc;
1809:   PetscLogObjectParent((PetscObject)ksp,(PetscObject)ksp->pc);
1810:   return(0);
1811: }

1813: /*@
1814:    KSPGetPC - Returns a pointer to the preconditioner context
1815:    set with KSPSetPC().

1817:    Not Collective

1819:    Input Parameters:
1820: .  ksp - iterative context obtained from KSPCreate()

1822:    Output Parameter:
1823: .  pc - preconditioner context

1825:    Level: developer

1827: .seealso: KSPSetPC(), KSP
1828: @*/
1829: PetscErrorCode  KSPGetPC(KSP ksp,PC *pc)
1830: {

1836:   if (!ksp->pc) {
1837:     PCCreate(PetscObjectComm((PetscObject)ksp),&ksp->pc);
1838:     PetscObjectIncrementTabLevel((PetscObject)ksp->pc,(PetscObject)ksp,0);
1839:     PetscLogObjectParent((PetscObject)ksp,(PetscObject)ksp->pc);
1840:     PetscObjectSetOptions((PetscObject)ksp->pc,((PetscObject)ksp)->options);
1841:   }
1842:   *pc = ksp->pc;
1843:   return(0);
1844: }

1846: /*@
1847:    KSPMonitor - runs the user provided monitor routines, if they exist

1849:    Collective on ksp

1851:    Input Parameters:
1852: +  ksp - iterative context obtained from KSPCreate()
1853: .  it - iteration number
1854: -  rnorm - relative norm of the residual

1856:    Notes:
1857:    This routine is called by the KSP implementations.
1858:    It does not typically need to be called by the user.

1860:    Level: developer

1862: .seealso: KSPMonitorSet()
1863: @*/
1864: PetscErrorCode KSPMonitor(KSP ksp,PetscInt it,PetscReal rnorm)
1865: {
1866:   PetscInt       i, n = ksp->numbermonitors;

1870:   for (i=0; i<n; i++) {
1871:     (*ksp->monitor[i])(ksp,it,rnorm,ksp->monitorcontext[i]);
1872:   }
1873:   return(0);
1874: }

1876: /*@C
1877:    KSPMonitorSet - Sets an ADDITIONAL function to be called at every iteration to monitor
1878:    the residual/error etc.

1880:    Logically Collective on ksp

1882:    Input Parameters:
1883: +  ksp - iterative context obtained from KSPCreate()
1884: .  monitor - pointer to function (if this is NULL, it turns off monitoring
1885: .  mctx    - [optional] context for private data for the
1886:              monitor routine (use NULL if no context is desired)
1887: -  monitordestroy - [optional] routine that frees monitor context
1888:           (may be NULL)

1890:    Calling Sequence of monitor:
1891: $     monitor (KSP ksp, PetscInt it, PetscReal rnorm, void *mctx)

1893: +  ksp - iterative context obtained from KSPCreate()
1894: .  it - iteration number
1895: .  rnorm - (estimated) 2-norm of (preconditioned) residual
1896: -  mctx  - optional monitoring context, as set by KSPMonitorSet()

1898:    Options Database Keys:
1899: +    -ksp_monitor        - sets KSPMonitorDefault()
1900: .    -ksp_monitor_true_residual    - sets KSPMonitorTrueResidualNorm()
1901: .    -ksp_monitor_max    - sets KSPMonitorTrueResidualMaxNorm()
1902: .    -ksp_monitor_lg_residualnorm    - sets line graph monitor,
1903:                            uses KSPMonitorLGResidualNormCreate()
1904: .    -ksp_monitor_lg_true_residualnorm   - sets line graph monitor,
1905:                            uses KSPMonitorLGResidualNormCreate()
1906: .    -ksp_monitor_singular_value    - sets KSPMonitorSingularValue()
1907: -    -ksp_monitor_cancel - cancels all monitors that have
1908:                           been hardwired into a code by
1909:                           calls to KSPMonitorSet(), but
1910:                           does not cancel those set via
1911:                           the options database.

1913:    Notes:
1914:    The default is to do nothing.  To print the residual, or preconditioned
1915:    residual if KSPSetNormType(ksp,KSP_NORM_PRECONDITIONED) was called, use
1916:    KSPMonitorDefault() as the monitoring routine, with a ASCII viewer as the
1917:    context.

1919:    Several different monitoring routines may be set by calling
1920:    KSPMonitorSet() multiple times; all will be called in the
1921:    order in which they were set.

1923:    Fortran Notes:
1924:     Only a single monitor function can be set for each KSP object

1926:    Level: beginner

1928: .seealso: KSPMonitorDefault(), KSPMonitorLGResidualNormCreate(), KSPMonitorCancel(), KSP
1929: @*/
1930: PetscErrorCode  KSPMonitorSet(KSP ksp,PetscErrorCode (*monitor)(KSP,PetscInt,PetscReal,void*),void *mctx,PetscErrorCode (*monitordestroy)(void**))
1931: {
1932:   PetscInt       i;
1934:   PetscBool      identical;

1938:   for (i=0; i<ksp->numbermonitors;i++) {
1939:     PetscMonitorCompare((PetscErrorCode (*)(void))monitor,mctx,monitordestroy,(PetscErrorCode (*)(void))ksp->monitor[i],ksp->monitorcontext[i],ksp->monitordestroy[i],&identical);
1940:     if (identical) return(0);
1941:   }
1942:   if (ksp->numbermonitors >= MAXKSPMONITORS) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Too many KSP monitors set");
1943:   ksp->monitor[ksp->numbermonitors]          = monitor;
1944:   ksp->monitordestroy[ksp->numbermonitors]   = monitordestroy;
1945:   ksp->monitorcontext[ksp->numbermonitors++] = (void*)mctx;
1946:   return(0);
1947: }

1949: /*@
1950:    KSPMonitorCancel - Clears all monitors for a KSP object.

1952:    Logically Collective on ksp

1954:    Input Parameters:
1955: .  ksp - iterative context obtained from KSPCreate()

1957:    Options Database Key:
1958: .  -ksp_monitor_cancel - Cancels all monitors that have
1959:     been hardwired into a code by calls to KSPMonitorSet(),
1960:     but does not cancel those set via the options database.

1962:    Level: intermediate

1964: .seealso: KSPMonitorDefault(), KSPMonitorLGResidualNormCreate(), KSPMonitorSet(), KSP
1965: @*/
1966: PetscErrorCode  KSPMonitorCancel(KSP ksp)
1967: {
1969:   PetscInt       i;

1973:   for (i=0; i<ksp->numbermonitors; i++) {
1974:     if (ksp->monitordestroy[i]) {
1975:       (*ksp->monitordestroy[i])(&ksp->monitorcontext[i]);
1976:     }
1977:   }
1978:   ksp->numbermonitors = 0;
1979:   return(0);
1980: }

1982: /*@C
1983:    KSPGetMonitorContext - Gets the monitoring context, as set by
1984:    KSPMonitorSet() for the FIRST monitor only.

1986:    Not Collective

1988:    Input Parameter:
1989: .  ksp - iterative context obtained from KSPCreate()

1991:    Output Parameter:
1992: .  ctx - monitoring context

1994:    Level: intermediate

1996: .seealso: KSPMonitorDefault(), KSPMonitorLGResidualNormCreate(), KSP
1997: @*/
1998: PetscErrorCode  KSPGetMonitorContext(KSP ksp,void **ctx)
1999: {
2002:   *ctx =      (ksp->monitorcontext[0]);
2003:   return(0);
2004: }

2006: /*@
2007:    KSPSetResidualHistory - Sets the array used to hold the residual history.
2008:    If set, this array will contain the residual norms computed at each
2009:    iteration of the solver.

2011:    Not Collective

2013:    Input Parameters:
2014: +  ksp - iterative context obtained from KSPCreate()
2015: .  a   - array to hold history
2016: .  na  - size of a
2017: -  reset - PETSC_TRUE indicates the history counter is reset to zero
2018:            for each new linear solve

2020:    Level: advanced

2022:    Notes:
2023:     The array is NOT freed by PETSc so the user needs to keep track of
2024:            it and destroy once the KSP object is destroyed.

2026:    If 'a' is NULL then space is allocated for the history. If 'na' PETSC_DECIDE or PETSC_DEFAULT then a
2027:    default array of length 10000 is allocated.

2029: .seealso: KSPGetResidualHistory(), KSP

2031: @*/
2032: PetscErrorCode  KSPSetResidualHistory(KSP ksp,PetscReal a[],PetscInt na,PetscBool reset)
2033: {


2039:   PetscFree(ksp->res_hist_alloc);
2040:   if (na != PETSC_DECIDE && na != PETSC_DEFAULT && a) {
2041:     ksp->res_hist     = a;
2042:     ksp->res_hist_max = na;
2043:   } else {
2044:     if (na != PETSC_DECIDE && na != PETSC_DEFAULT) ksp->res_hist_max = na;
2045:     else                                           ksp->res_hist_max = 10000; /* like default ksp->max_it */
2046:     PetscCalloc1(ksp->res_hist_max,&ksp->res_hist_alloc);

2048:     ksp->res_hist = ksp->res_hist_alloc;
2049:   }
2050:   ksp->res_hist_len   = 0;
2051:   ksp->res_hist_reset = reset;
2052:   return(0);
2053: }

2055: /*@C
2056:    KSPGetResidualHistory - Gets the array used to hold the residual history
2057:    and the number of residuals it contains.

2059:    Not Collective

2061:    Input Parameter:
2062: .  ksp - iterative context obtained from KSPCreate()

2064:    Output Parameters:
2065: +  a   - pointer to array to hold history (or NULL)
2066: -  na  - number of used entries in a (or NULL)

2068:    Level: advanced

2070:    Notes:
2071:      Can only be called after a KSPSetResidualHistory() otherwise a and na are set to zero

2073:      The Fortran version of this routine has a calling sequence
2074: $   call KSPGetResidualHistory(KSP ksp, integer na, integer ierr)
2075:     note that you have passed a Fortran array into KSPSetResidualHistory() and you need
2076:     to access the residual values from this Fortran array you provided. Only the na (number of
2077:     residual norms currently held) is set.

2079: .seealso: KSPGetResidualHistory(), KSP

2081: @*/
2082: PetscErrorCode  KSPGetResidualHistory(KSP ksp,PetscReal *a[],PetscInt *na)
2083: {
2086:   if (a) *a = ksp->res_hist;
2087:   if (na) *na = ksp->res_hist_len;
2088:   return(0);
2089: }

2091: /*@C
2092:    KSPSetConvergenceTest - Sets the function to be used to determine
2093:    convergence.

2095:    Logically Collective on ksp

2097:    Input Parameters:
2098: +  ksp - iterative context obtained from KSPCreate()
2099: .  converge - pointer to the function
2100: .  cctx    - context for private data for the convergence routine (may be null)
2101: -  destroy - a routine for destroying the context (may be null)

2103:    Calling sequence of converge:
2104: $     converge (KSP ksp, PetscInt it, PetscReal rnorm, KSPConvergedReason *reason,void *mctx)

2106: +  ksp - iterative context obtained from KSPCreate()
2107: .  it - iteration number
2108: .  rnorm - (estimated) 2-norm of (preconditioned) residual
2109: .  reason - the reason why it has converged or diverged
2110: -  cctx  - optional convergence context, as set by KSPSetConvergenceTest()


2113:    Notes:
2114:    Must be called after the KSP type has been set so put this after
2115:    a call to KSPSetType(), or KSPSetFromOptions().

2117:    The default convergence test, KSPConvergedDefault(), aborts if the
2118:    residual grows to more than 10000 times the initial residual.

2120:    The default is a combination of relative and absolute tolerances.
2121:    The residual value that is tested may be an approximation; routines
2122:    that need exact values should compute them.

2124:    In the default PETSc convergence test, the precise values of reason
2125:    are macros such as KSP_CONVERGED_RTOL, which are defined in petscksp.h.

2127:    Level: advanced

2129: .seealso: KSPConvergedDefault(), KSPGetConvergenceContext(), KSPSetTolerances(), KSP, KSPGetConvergenceTest(), KSPGetAndClearConvergenceTest()
2130: @*/
2131: PetscErrorCode  KSPSetConvergenceTest(KSP ksp,PetscErrorCode (*converge)(KSP,PetscInt,PetscReal,KSPConvergedReason*,void*),void *cctx,PetscErrorCode (*destroy)(void*))
2132: {

2137:   if (ksp->convergeddestroy) {
2138:     (*ksp->convergeddestroy)(ksp->cnvP);
2139:   }
2140:   ksp->converged        = converge;
2141:   ksp->convergeddestroy = destroy;
2142:   ksp->cnvP             = (void*)cctx;
2143:   return(0);
2144: }

2146: /*@C
2147:    KSPGetConvergenceTest - Gets the function to be used to determine
2148:    convergence.

2150:    Logically Collective on ksp

2152:    Input Parameter:
2153: .   ksp - iterative context obtained from KSPCreate()

2155:    Output Parameter:
2156: +  converge - pointer to convergence test function
2157: .  cctx    - context for private data for the convergence routine (may be null)
2158: -  destroy - a routine for destroying the context (may be null)

2160:    Calling sequence of converge:
2161: $     converge (KSP ksp, PetscInt it, PetscReal rnorm, KSPConvergedReason *reason,void *mctx)

2163: +  ksp - iterative context obtained from KSPCreate()
2164: .  it - iteration number
2165: .  rnorm - (estimated) 2-norm of (preconditioned) residual
2166: .  reason - the reason why it has converged or diverged
2167: -  cctx  - optional convergence context, as set by KSPSetConvergenceTest()

2169:    Level: advanced

2171: .seealso: KSPConvergedDefault(), KSPGetConvergenceContext(), KSPSetTolerances(), KSP, KSPSetConvergenceTest(), KSPGetAndClearConvergenceTest()
2172: @*/
2173: PetscErrorCode  KSPGetConvergenceTest(KSP ksp,PetscErrorCode (**converge)(KSP,PetscInt,PetscReal,KSPConvergedReason*,void*),void **cctx,PetscErrorCode (**destroy)(void*))
2174: {
2177:   if (converge) *converge = ksp->converged;
2178:   if (destroy)  *destroy  = ksp->convergeddestroy;
2179:   if (cctx)     *cctx     = ksp->cnvP;
2180:   return(0);
2181: }

2183: /*@C
2184:    KSPGetAndClearConvergenceTest - Gets the function to be used to determine convergence. Removes the current test without calling destroy on the test context

2186:    Logically Collective on ksp

2188:    Input Parameter:
2189: .   ksp - iterative context obtained from KSPCreate()

2191:    Output Parameter:
2192: +  converge - pointer to convergence test function
2193: .  cctx    - context for private data for the convergence routine
2194: -  destroy - a routine for destroying the context

2196:    Calling sequence of converge:
2197: $     converge (KSP ksp, PetscInt it, PetscReal rnorm, KSPConvergedReason *reason,void *mctx)

2199: +  ksp - iterative context obtained from KSPCreate()
2200: .  it - iteration number
2201: .  rnorm - (estimated) 2-norm of (preconditioned) residual
2202: .  reason - the reason why it has converged or diverged
2203: -  cctx  - optional convergence context, as set by KSPSetConvergenceTest()

2205:    Level: advanced

2207:    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
2208:           KSPSetConvergenceTest() on this original KSP. If you just called KSPGetConvergenceTest() followed by KSPSetConvergenceTest() the original context information
2209:           would be destroyed and hence the transferred context would be invalid and trigger a crash on use

2211: .seealso: KSPConvergedDefault(), KSPGetConvergenceContext(), KSPSetTolerances(), KSP, KSPSetConvergenceTest(), KSPGetConvergenceTest()
2212: @*/
2213: PetscErrorCode  KSPGetAndClearConvergenceTest(KSP ksp,PetscErrorCode (**converge)(KSP,PetscInt,PetscReal,KSPConvergedReason*,void*),void **cctx,PetscErrorCode (**destroy)(void*))
2214: {
2217:   *converge             = ksp->converged;
2218:   *destroy              = ksp->convergeddestroy;
2219:   *cctx                 = ksp->cnvP;
2220:   ksp->converged        = NULL;
2221:   ksp->cnvP             = NULL;
2222:   ksp->convergeddestroy = NULL;
2223:   return(0);
2224: }

2226: /*@C
2227:    KSPGetConvergenceContext - Gets the convergence context set with
2228:    KSPSetConvergenceTest().

2230:    Not Collective

2232:    Input Parameter:
2233: .  ksp - iterative context obtained from KSPCreate()

2235:    Output Parameter:
2236: .  ctx - monitoring context

2238:    Level: advanced

2240: .seealso: KSPConvergedDefault(), KSPSetConvergenceTest(), KSP
2241: @*/
2242: PetscErrorCode  KSPGetConvergenceContext(KSP ksp,void **ctx)
2243: {
2246:   *ctx = ksp->cnvP;
2247:   return(0);
2248: }

2250: /*@C
2251:    KSPBuildSolution - Builds the approximate solution in a vector provided.
2252:    This routine is NOT commonly needed (see KSPSolve()).

2254:    Collective on ksp

2256:    Input Parameter:
2257: .  ctx - iterative context obtained from KSPCreate()

2259:    Output Parameter:
2260:    Provide exactly one of
2261: +  v - location to stash solution.
2262: -  V - the solution is returned in this location. This vector is created
2263:        internally. This vector should NOT be destroyed by the user with
2264:        VecDestroy().

2266:    Notes:
2267:    This routine can be used in one of two ways
2268: .vb
2269:       KSPBuildSolution(ksp,NULL,&V);
2270:    or
2271:       KSPBuildSolution(ksp,v,NULL); or KSPBuildSolution(ksp,v,&v);
2272: .ve
2273:    In the first case an internal vector is allocated to store the solution
2274:    (the user cannot destroy this vector). In the second case the solution
2275:    is generated in the vector that the user provides. Note that for certain
2276:    methods, such as KSPCG, the second case requires a copy of the solution,
2277:    while in the first case the call is essentially free since it simply
2278:    returns the vector where the solution already is stored. For some methods
2279:    like GMRES this is a reasonably expensive operation and should only be
2280:    used in truly needed.

2282:    Level: advanced

2284: .seealso: KSPGetSolution(), KSPBuildResidual(), KSP
2285: @*/
2286: PetscErrorCode  KSPBuildSolution(KSP ksp,Vec v,Vec *V)
2287: {

2292:   if (!V && !v) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_WRONG,"Must provide either v or V");
2293:   if (!V) V = &v;
2294:   (*ksp->ops->buildsolution)(ksp,v,V);
2295:   return(0);
2296: }

2298: /*@C
2299:    KSPBuildResidual - Builds the residual in a vector provided.

2301:    Collective on ksp

2303:    Input Parameter:
2304: .  ksp - iterative context obtained from KSPCreate()

2306:    Output Parameters:
2307: +  v - optional location to stash residual.  If v is not provided,
2308:        then a location is generated.
2309: .  t - work vector.  If not provided then one is generated.
2310: -  V - the residual

2312:    Notes:
2313:    Regardless of whether or not v is provided, the residual is
2314:    returned in V.

2316:    Level: advanced

2318: .seealso: KSPBuildSolution()
2319: @*/
2320: PetscErrorCode  KSPBuildResidual(KSP ksp,Vec t,Vec v,Vec *V)
2321: {
2323:   PetscBool      flag = PETSC_FALSE;
2324:   Vec            w    = v,tt = t;

2328:   if (!w) {
2329:     VecDuplicate(ksp->vec_rhs,&w);
2330:     PetscLogObjectParent((PetscObject)ksp,(PetscObject)w);
2331:   }
2332:   if (!tt) {
2333:     VecDuplicate(ksp->vec_sol,&tt); flag = PETSC_TRUE;
2334:     PetscLogObjectParent((PetscObject)ksp,(PetscObject)tt);
2335:   }
2336:   (*ksp->ops->buildresidual)(ksp,tt,w,V);
2337:   if (flag) {VecDestroy(&tt);}
2338:   return(0);
2339: }

2341: /*@
2342:    KSPSetDiagonalScale - Tells KSP to symmetrically diagonally scale the system
2343:      before solving. This actually CHANGES the matrix (and right hand side).

2345:    Logically Collective on ksp

2347:    Input Parameter:
2348: +  ksp - the KSP context
2349: -  scale - PETSC_TRUE or PETSC_FALSE

2351:    Options Database Key:
2352: +   -ksp_diagonal_scale -
2353: -   -ksp_diagonal_scale_fix - scale the matrix back AFTER the solve


2356:     Notes:
2357:     Scales the matrix by  D^(-1/2)  A  D^(-1/2)  [D^(1/2) x ] = D^(-1/2) b
2358:        where D_{ii} is 1/abs(A_{ii}) unless A_{ii} is zero and then it is 1.

2360:     BE CAREFUL with this routine: it actually scales the matrix and right
2361:     hand side that define the system. After the system is solved the matrix
2362:     and right hand side remain scaled unless you use KSPSetDiagonalScaleFix()

2364:     This should NOT be used within the SNES solves if you are using a line
2365:     search.

2367:     If you use this with the PCType Eisenstat preconditioner than you can
2368:     use the PCEisenstatSetNoDiagonalScaling() option, or -pc_eisenstat_no_diagonal_scaling
2369:     to save some unneeded, redundant flops.

2371:    Level: intermediate

2373: .seealso: KSPGetDiagonalScale(), KSPSetDiagonalScaleFix(), KSP
2374: @*/
2375: PetscErrorCode  KSPSetDiagonalScale(KSP ksp,PetscBool scale)
2376: {
2380:   ksp->dscale = scale;
2381:   return(0);
2382: }

2384: /*@
2385:    KSPGetDiagonalScale - Checks if KSP solver scales the matrix and
2386:                           right hand side

2388:    Not Collective

2390:    Input Parameter:
2391: .  ksp - the KSP context

2393:    Output Parameter:
2394: .  scale - PETSC_TRUE or PETSC_FALSE

2396:    Notes:
2397:     BE CAREFUL with this routine: it actually scales the matrix and right
2398:     hand side that define the system. After the system is solved the matrix
2399:     and right hand side remain scaled  unless you use KSPSetDiagonalScaleFix()

2401:    Level: intermediate

2403: .seealso: KSPSetDiagonalScale(), KSPSetDiagonalScaleFix(), KSP
2404: @*/
2405: PetscErrorCode  KSPGetDiagonalScale(KSP ksp,PetscBool  *scale)
2406: {
2410:   *scale = ksp->dscale;
2411:   return(0);
2412: }

2414: /*@
2415:    KSPSetDiagonalScaleFix - Tells KSP to diagonally scale the system
2416:      back after solving.

2418:    Logically Collective on ksp

2420:    Input Parameter:
2421: +  ksp - the KSP context
2422: -  fix - PETSC_TRUE to scale back after the system solve, PETSC_FALSE to not
2423:          rescale (default)

2425:    Notes:
2426:      Must be called after KSPSetDiagonalScale()

2428:      Using this will slow things down, because it rescales the matrix before and
2429:      after each linear solve. This is intended mainly for testing to allow one
2430:      to easily get back the original system to make sure the solution computed is
2431:      accurate enough.

2433:    Level: intermediate

2435: .seealso: KSPGetDiagonalScale(), KSPSetDiagonalScale(), KSPGetDiagonalScaleFix(), KSP
2436: @*/
2437: PetscErrorCode  KSPSetDiagonalScaleFix(KSP ksp,PetscBool fix)
2438: {
2442:   ksp->dscalefix = fix;
2443:   return(0);
2444: }

2446: /*@
2447:    KSPGetDiagonalScaleFix - Determines if KSP diagonally scales the system
2448:      back after solving.

2450:    Not Collective

2452:    Input Parameter:
2453: .  ksp - the KSP context

2455:    Output Parameter:
2456: .  fix - PETSC_TRUE to scale back after the system solve, PETSC_FALSE to not
2457:          rescale (default)

2459:    Notes:
2460:      Must be called after KSPSetDiagonalScale()

2462:      If PETSC_TRUE will slow things down, because it rescales the matrix before and
2463:      after each linear solve. This is intended mainly for testing to allow one
2464:      to easily get back the original system to make sure the solution computed is
2465:      accurate enough.

2467:    Level: intermediate

2469: .seealso: KSPGetDiagonalScale(), KSPSetDiagonalScale(), KSPSetDiagonalScaleFix(), KSP
2470: @*/
2471: PetscErrorCode  KSPGetDiagonalScaleFix(KSP ksp,PetscBool  *fix)
2472: {
2476:   *fix = ksp->dscalefix;
2477:   return(0);
2478: }

2480: /*@C
2481:    KSPSetComputeOperators - set routine to compute the linear operators

2483:    Logically Collective

2485:    Input Arguments:
2486: +  ksp - the KSP context
2487: .  func - function to compute the operators
2488: -  ctx - optional context

2490:    Calling sequence of func:
2491: $  func(KSP ksp,Mat A,Mat B,void *ctx)

2493: +  ksp - the KSP context
2494: .  A - the linear operator
2495: .  B - preconditioning matrix
2496: -  ctx - optional user-provided context

2498:    Notes:
2499:     The user provided func() will be called automatically at the very next call to KSPSolve(). It will not be called at future KSPSolve() calls
2500:           unless either KSPSetComputeOperators() or KSPSetOperators() is called before that KSPSolve() is called.

2502:           To reuse the same preconditioner for the next KSPSolve() and not compute a new one based on the most recently computed matrix call KSPSetReusePreconditioner()

2504:    Level: beginner

2506: .seealso: KSPSetOperators(), KSPSetComputeRHS(), DMKSPSetComputeOperators(), KSPSetComputeInitialGuess()
2507: @*/
2508: PetscErrorCode KSPSetComputeOperators(KSP ksp,PetscErrorCode (*func)(KSP,Mat,Mat,void*),void *ctx)
2509: {
2511:   DM             dm;

2515:   KSPGetDM(ksp,&dm);
2516:   DMKSPSetComputeOperators(dm,func,ctx);
2517:   if (ksp->setupstage == KSP_SETUP_NEWRHS) ksp->setupstage = KSP_SETUP_NEWMATRIX;
2518:   return(0);
2519: }

2521: /*@C
2522:    KSPSetComputeRHS - set routine to compute the right hand side of the linear system

2524:    Logically Collective

2526:    Input Arguments:
2527: +  ksp - the KSP context
2528: .  func - function to compute the right hand side
2529: -  ctx - optional context

2531:    Calling sequence of func:
2532: $  func(KSP ksp,Vec b,void *ctx)

2534: +  ksp - the KSP context
2535: .  b - right hand side of linear system
2536: -  ctx - optional user-provided context

2538:    Notes:
2539:     The routine you provide will be called EACH you call KSPSolve() to prepare the new right hand side for that solve

2541:    Level: beginner

2543: .seealso: KSPSolve(), DMKSPSetComputeRHS(), KSPSetComputeOperators()
2544: @*/
2545: PetscErrorCode KSPSetComputeRHS(KSP ksp,PetscErrorCode (*func)(KSP,Vec,void*),void *ctx)
2546: {
2548:   DM             dm;

2552:   KSPGetDM(ksp,&dm);
2553:   DMKSPSetComputeRHS(dm,func,ctx);
2554:   return(0);
2555: }

2557: /*@C
2558:    KSPSetComputeInitialGuess - set routine to compute the initial guess of the linear system

2560:    Logically Collective

2562:    Input Arguments:
2563: +  ksp - the KSP context
2564: .  func - function to compute the initial guess
2565: -  ctx - optional context

2567:    Calling sequence of func:
2568: $  func(KSP ksp,Vec x,void *ctx)

2570: +  ksp - the KSP context
2571: .  x - solution vector
2572: -  ctx - optional user-provided context

2574:    Notes: This should only be used in conjunction with KSPSetComputeRHS(), KSPSetComputeOperators(), otherwise
2575:    call KSPSetInitialGuessNonzero() and set the initial guess values in the solution vector passed to KSPSolve().

2577:    Level: beginner

2579: .seealso: KSPSolve(), KSPSetComputeRHS(), KSPSetComputeOperators(), DMKSPSetComputeInitialGuess()
2580: @*/
2581: PetscErrorCode KSPSetComputeInitialGuess(KSP ksp,PetscErrorCode (*func)(KSP,Vec,void*),void *ctx)
2582: {
2584:   DM             dm;

2588:   KSPGetDM(ksp,&dm);
2589:   DMKSPSetComputeInitialGuess(dm,func,ctx);
2590:   return(0);
2591: }