Actual source code: itfunc.c

petsc-master 2019-12-09
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  2: /*
  3:       Interface KSP routines that the user calls.
  4: */

  6:  #include <petsc/private/kspimpl.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 Parameter:
 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 Parameter:
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:   PCGetFailedReason(pc,&pcreason);
216:   if (pcreason) {
217:     ksp->reason = KSP_DIVERGED_PC_FAILED;
218:   }
219:   return(0);
220: }

222: /*@
223:    KSPSetReusePreconditioner - reuse the current preconditioner, do not construct a new one even if the operator changes

225:    Collective on ksp

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

231:    Level: intermediate

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

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

247: /*@
248:    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

250:    Collective on ksp

252:    Input Parameters:
253: +  ksp   - iterative context obtained from KSPCreate()
254: -  flag - PETSC_TRUE to skip calling the PCSetFromOptions()

256:    Level: intermediate

258: .seealso: KSPCreate(), KSPSolve(), KSPDestroy(), PCSetReusePreconditioner(), KSP
259: @*/
260: PetscErrorCode  KSPSetSkipPCSetFromOptions(KSP ksp,PetscBool flag)
261: {
264:   ksp->skippcsetfromoptions = flag;
265:   return(0);
266: }

268: /*@
269:    KSPSetUp - Sets up the internal data structures for the
270:    later use of an iterative solver.

272:    Collective on ksp

274:    Input Parameter:
275: .  ksp   - iterative context obtained from KSPCreate()

277:    Level: developer

279: .seealso: KSPCreate(), KSPSolve(), KSPDestroy(), KSP
280: @*/
281: PetscErrorCode KSPSetUp(KSP ksp)
282: {
284:   Mat            A,B;
285:   Mat            mat,pmat;
286:   MatNullSpace   nullsp;
287:   PCFailedReason pcreason;
288: 

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

295:   if (!((PetscObject)ksp)->type_name) {
296:     KSPSetType(ksp,KSPGMRES);
297:   }
298:   KSPSetUpNorms_Private(ksp,PETSC_TRUE,&ksp->normtype,&ksp->pc_side);

300:   if (ksp->dmActive && !ksp->setupstage) {
301:     /* first time in so build matrix and vector data structures using DM */
302:     if (!ksp->vec_rhs) {DMCreateGlobalVector(ksp->dm,&ksp->vec_rhs);}
303:     if (!ksp->vec_sol) {DMCreateGlobalVector(ksp->dm,&ksp->vec_sol);}
304:     DMCreateMatrix(ksp->dm,&A);
305:     KSPSetOperators(ksp,A,A);
306:     PetscObjectDereference((PetscObject)A);
307:   }

309:   if (ksp->dmActive) {
310:     DMKSP kdm;
311:     DMGetDMKSP(ksp->dm,&kdm);

313:     if (kdm->ops->computeinitialguess && ksp->setupstage != KSP_SETUP_NEWRHS) {
314:       /* only computes initial guess the first time through */
315:       (*kdm->ops->computeinitialguess)(ksp,ksp->vec_sol,kdm->initialguessctx);
316:       KSPSetInitialGuessNonzero(ksp,PETSC_TRUE);
317:     }
318:     if (kdm->ops->computerhs) {
319:       (*kdm->ops->computerhs)(ksp,ksp->vec_rhs,kdm->rhsctx);
320:     }

322:     if (ksp->setupstage != KSP_SETUP_NEWRHS) {
323:       if (kdm->ops->computeoperators) {
324:         KSPGetOperators(ksp,&A,&B);
325:         (*kdm->ops->computeoperators)(ksp,A,B,kdm->operatorsctx);
326:       } else SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_WRONGSTATE,"You called KSPSetDM() but did not use DMKSPSetComputeOperators() or KSPSetDMActive(ksp,PETSC_FALSE);");
327:     }
328:   }

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

333:   switch (ksp->setupstage) {
334:   case KSP_SETUP_NEW:
335:     (*ksp->ops->setup)(ksp);
336:     break;
337:   case KSP_SETUP_NEWMATRIX: {   /* This should be replaced with a more general mechanism */
338:     if (ksp->setupnewmatrix) {
339:       (*ksp->ops->setup)(ksp);
340:     }
341:   } break;
342:   default: break;
343:   }

345:   if (!ksp->pc) {KSPGetPC(ksp,&ksp->pc);}
346:   PCGetOperators(ksp->pc,&mat,&pmat);
347:   /* scale the matrix if requested */
348:   if (ksp->dscale) {
349:     PetscScalar *xx;
350:     PetscInt    i,n;
351:     PetscBool   zeroflag = PETSC_FALSE;
352:     if (!ksp->pc) {KSPGetPC(ksp,&ksp->pc);}
353:     if (!ksp->diagonal) { /* allocate vector to hold diagonal */
354:       MatCreateVecs(pmat,&ksp->diagonal,0);
355:     }
356:     MatGetDiagonal(pmat,ksp->diagonal);
357:     VecGetLocalSize(ksp->diagonal,&n);
358:     VecGetArray(ksp->diagonal,&xx);
359:     for (i=0; i<n; i++) {
360:       if (xx[i] != 0.0) xx[i] = 1.0/PetscSqrtReal(PetscAbsScalar(xx[i]));
361:       else {
362:         xx[i]    = 1.0;
363:         zeroflag = PETSC_TRUE;
364:       }
365:     }
366:     VecRestoreArray(ksp->diagonal,&xx);
367:     if (zeroflag) {
368:       PetscInfo(ksp,"Zero detected in diagonal of matrix, using 1 at those locations\n");
369:     }
370:     MatDiagonalScale(pmat,ksp->diagonal,ksp->diagonal);
371:     if (mat != pmat) {MatDiagonalScale(mat,ksp->diagonal,ksp->diagonal);}
372:     ksp->dscalefix2 = PETSC_FALSE;
373:   }
374:   PetscLogEventEnd(KSP_SetUp,ksp,ksp->vec_rhs,ksp->vec_sol,0);
375:   PCSetErrorIfFailure(ksp->pc,ksp->errorifnotconverged);
376:   PCSetUp(ksp->pc);
377:   PCGetFailedReason(ksp->pc,&pcreason);
378:   if (pcreason) {
379:     ksp->reason = KSP_DIVERGED_PC_FAILED;
380:   }

382:   MatGetNullSpace(mat,&nullsp);
383:   if (nullsp) {
384:     PetscBool test = PETSC_FALSE;
385:     PetscOptionsGetBool(((PetscObject)ksp)->options,((PetscObject)ksp)->prefix,"-ksp_test_null_space",&test,NULL);
386:     if (test) {
387:       MatNullSpaceTest(nullsp,mat,NULL);
388:     }
389:   }
390:   ksp->setupstage = KSP_SETUP_NEWRHS;
391:   return(0);
392: }

394: static PetscErrorCode KSPReasonView_Internal(KSP ksp, PetscViewer viewer, PetscViewerFormat format)
395: {
397:   PetscBool      isAscii;

400:   if (format != PETSC_VIEWER_DEFAULT) {PetscViewerPushFormat(viewer,format);}
401:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isAscii);
402:   if (isAscii) {
403:     PetscViewerASCIIAddTab(viewer,((PetscObject)ksp)->tablevel);
404:     if (ksp->reason > 0) {
405:       if (((PetscObject) ksp)->prefix) {
406:         PetscViewerASCIIPrintf(viewer,"Linear %s solve converged due to %s iterations %D\n",((PetscObject) ksp)->prefix,KSPConvergedReasons[ksp->reason],ksp->its);
407:       } else {
408:         PetscViewerASCIIPrintf(viewer,"Linear solve converged due to %s iterations %D\n",KSPConvergedReasons[ksp->reason],ksp->its);
409:       }
410:     } else {
411:       if (((PetscObject) ksp)->prefix) {
412:         PetscViewerASCIIPrintf(viewer,"Linear %s solve did not converge due to %s iterations %D\n",((PetscObject) ksp)->prefix,KSPConvergedReasons[ksp->reason],ksp->its);
413:       } else {
414:         PetscViewerASCIIPrintf(viewer,"Linear solve did not converge due to %s iterations %D\n",KSPConvergedReasons[ksp->reason],ksp->its);
415:       }
416:       if (ksp->reason == KSP_DIVERGED_PC_FAILED) {
417:         PCFailedReason reason;
418:         PCGetFailedReason(ksp->pc,&reason);
419:         PetscViewerASCIIPrintf(viewer,"               PC_FAILED due to %s \n",PCFailedReasons[reason]);
420:       }
421:     }
422:     PetscViewerASCIISubtractTab(viewer,((PetscObject)ksp)->tablevel);
423:   }
424:   if (format != PETSC_VIEWER_DEFAULT) {PetscViewerPopFormat(viewer);}
425:   return(0);
426: }

428: /*@
429:    KSPReasonView - Displays the reason a KSP solve converged or diverged to a viewer

431:    Collective on ksp

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


438:    Options Database Keys:
439: .  -ksp_converged_reason - print reason for converged or diverged, also prints number of iterations

441:    Level: beginner

443: .seealso: KSPCreate(), KSPSetUp(), KSPDestroy(), KSPSetTolerances(), KSPConvergedDefault(),
444:           KSPSolveTranspose(), KSPGetIterationNumber(), KSP
445: @*/
446: PetscErrorCode KSPReasonView(KSP ksp,PetscViewer viewer)
447: {

451:   KSPReasonView_Internal(ksp, viewer, PETSC_VIEWER_DEFAULT);
452:   return(0);
453: }

455: #if defined(PETSC_HAVE_THREADSAFETY)
456: #define KSPReasonViewFromOptions KSPReasonViewFromOptionsUnsafe
457: #else
458: #endif
459: /*@C
460:   KSPReasonViewFromOptions - Processes command line options to determine if/how a KSPReason is to be viewed.

462:   Collective on ksp

464:   Input Parameters:
465: . ksp   - the KSP object

467:   Level: intermediate

469: @*/
470: PetscErrorCode KSPReasonViewFromOptions(KSP ksp)
471: {
472:   PetscViewer       viewer;
473:   PetscBool         flg;
474:   PetscViewerFormat format;
475:   PetscErrorCode    ierr;

478:   PetscOptionsGetViewer(PetscObjectComm((PetscObject)ksp),((PetscObject)ksp)->options,((PetscObject)ksp)->prefix,"-ksp_converged_reason",&viewer,&format,&flg);
479:   if (flg) {
480:     KSPReasonView_Internal(ksp, viewer, format);
481:     PetscViewerDestroy(&viewer);
482:   }
483:   return(0);
484: }

486:  #include <petscdraw.h>

488: static PetscErrorCode KSPViewEigenvalues_Internal(KSP ksp, PetscBool isExplicit, PetscViewer viewer, PetscViewerFormat format)
489: {
490:   PetscReal     *r, *c;
491:   PetscInt       n, i, neig;
492:   PetscBool      isascii, isdraw;
493:   PetscMPIInt    rank;

497:   MPI_Comm_rank(PetscObjectComm((PetscObject) ksp), &rank);
498:   PetscObjectTypeCompare((PetscObject) viewer, PETSCVIEWERASCII, &isascii);
499:   PetscObjectTypeCompare((PetscObject) viewer, PETSCVIEWERDRAW,  &isdraw);
500:   if (isExplicit) {
501:     VecGetSize(ksp->vec_sol,&n);
502:     PetscMalloc2(n, &r, n, &c);
503:     KSPComputeEigenvaluesExplicitly(ksp, n, r, c);
504:     neig = n;
505:   } else {
506:     PetscInt nits;

508:     KSPGetIterationNumber(ksp, &nits);
509:     n    = nits+2;
510:     if (!nits) {PetscViewerASCIIPrintf(viewer, "Zero iterations in solver, cannot approximate any eigenvalues\n");return(0);}
511:     PetscMalloc2(n, &r, n, &c);
512:     KSPComputeEigenvalues(ksp, n, r, c, &neig);
513:   }
514:   if (isascii) {
515:     PetscViewerASCIIPrintf(viewer, "%s computed eigenvalues\n", isExplicit ? "Explicitly" : "Iteratively");
516:     for (i = 0; i < neig; ++i) {
517:       if (c[i] >= 0.0) {PetscViewerASCIIPrintf(viewer, "%g + %gi\n", (double) r[i],  (double) c[i]);}
518:       else             {PetscViewerASCIIPrintf(viewer, "%g - %gi\n", (double) r[i], -(double) c[i]);}
519:     }
520:   } else if (isdraw && !rank) {
521:     PetscDraw   draw;
522:     PetscDrawSP drawsp;

524:     if (format == PETSC_VIEWER_DRAW_CONTOUR) {
525:       KSPPlotEigenContours_Private(ksp,neig,r,c);
526:     } else {
527:       if (!ksp->eigviewer) {PetscViewerDrawOpen(PETSC_COMM_SELF,0,isExplicit ? "Explicitly Computed Eigenvalues" : "Iteratively Computed Eigenvalues",PETSC_DECIDE,PETSC_DECIDE,400,400,&ksp->eigviewer);}
528:       PetscViewerDrawGetDraw(ksp->eigviewer,0,&draw);
529:       PetscDrawSPCreate(draw,1,&drawsp);
530:       PetscDrawSPReset(drawsp);
531:       for (i = 0; i < neig; ++i) {PetscDrawSPAddPoint(drawsp,r+i,c+i);}
532:       PetscDrawSPDraw(drawsp,PETSC_TRUE);
533:       PetscDrawSPSave(drawsp);
534:       PetscDrawSPDestroy(&drawsp);
535:     }
536:   }
537:   PetscFree2(r, c);
538:   return(0);
539: }

541: static PetscErrorCode KSPViewSingularvalues_Internal(KSP ksp, PetscViewer viewer, PetscViewerFormat format)
542: {
543:   PetscReal      smax, smin;
544:   PetscInt       nits;
545:   PetscBool      isascii;

549:   PetscObjectTypeCompare((PetscObject) viewer, PETSCVIEWERASCII, &isascii);
550:   KSPGetIterationNumber(ksp, &nits);
551:   if (!nits) {PetscViewerASCIIPrintf(viewer, "Zero iterations in solver, cannot approximate any singular values\n");return(0);}
552:   KSPComputeExtremeSingularValues(ksp, &smax, &smin);
553:   if (isascii) {PetscViewerASCIIPrintf(viewer, "Iteratively computed extreme singular values: max %g min %g max/min %g\n",(double)smax,(double)smin,(double)(smax/smin));}
554:   return(0);
555: }

557: static PetscErrorCode KSPViewFinalResidual_Internal(KSP ksp, PetscViewer viewer, PetscViewerFormat format)
558: {
559:   PetscBool      isascii;

563:   PetscObjectTypeCompare((PetscObject) viewer, PETSCVIEWERASCII, &isascii);
564:   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");
565:   if (isascii) {
566:     Mat       A;
567:     Vec       t;
568:     PetscReal norm;

570:     PCGetOperators(ksp->pc, &A, NULL);
571:     VecDuplicate(ksp->vec_rhs, &t);
572:     KSP_MatMult(ksp, A, ksp->vec_sol, t);
573:     VecAYPX(t, -1.0, ksp->vec_rhs);
574:     VecNorm(t, NORM_2, &norm);
575:     VecDestroy(&t);
576:     PetscViewerASCIIPrintf(viewer, "KSP final norm of residual %g\n", (double) norm);
577:   }
578:   return(0);
579: }

581: /*@
582:    KSPSolve - Solves linear system.

584:    Collective on ksp

586:    Parameter:
587: +  ksp - iterative context obtained from KSPCreate()
588: .  b - the right hand side vector
589: -  x - the solution  (this may be the same vector as b, then b will be overwritten with answer)

591:    Options Database Keys:
592: +  -ksp_view_eigenvalues - compute preconditioned operators eigenvalues
593: .  -ksp_view_eigenvalues_explicitly - compute the eigenvalues by forming the dense operator and using LAPACK
594: .  -ksp_view_mat binary - save matrix to the default binary viewer
595: .  -ksp_view_pmat binary - save matrix used to build preconditioner to the default binary viewer
596: .  -ksp_view_rhs binary - save right hand side vector to the default binary viewer
597: .  -ksp_view_solution binary - save computed solution vector to the default binary viewer
598:            (can be read later with src/ksp/examples/tutorials/ex10.c for testing solvers)
599: .  -ksp_view_mat_explicit - for matrix-free operators, computes the matrix entries and views them
600: .  -ksp_view_preconditioned_operator_explicit - computes the product of the preconditioner and matrix as an explicit matrix and views it
601: .  -ksp_converged_reason - print reason for converged or diverged, also prints number of iterations
602: .  -ksp_view_final_residual - print 2-norm of true linear system residual at the end of the solution process
603: -  -ksp_view - print the ksp data structure at the end of the system solution

605:    Notes:

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

609:    The operator is specified with KSPSetOperators().

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

614:    If you provide a matrix that has a MatSetNullSpace() and MatSetTransposeNullSpace() this will use that information to solve singular systems
615:    in the least squares sense with a norm minimizing solution.
616: $
617: $                   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()
618: $
619: $    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
620: $    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
621: $    direction thus the solution which is a linear combination of the search directions has no component in the nullspace(A).
622: $
623: $    We recommend always using GMRES for such singular systems.
624: $    If nullspace(A) = nullspace(A') (note symmetric matrices always satisfy this property) then both left and right preconditioning will work
625: $    If nullspace(A) != nullspace(A') then left preconditioning will work but right preconditioning may not work (or it may).

627:    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
628:        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
629:        such as diagonal scaling we cannot apply the inverse of the preconditioner to a vector and thus cannot compute the nullspace(AB).


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

637:    Understanding Convergence:
638:    The routines KSPMonitorSet(), KSPComputeEigenvalues(), and
639:    KSPComputeEigenvaluesExplicitly() provide information on additional
640:    options to monitor convergence and print eigenvalue information.

642:    Level: beginner

644: .seealso: KSPCreate(), KSPSetUp(), KSPDestroy(), KSPSetTolerances(), KSPConvergedDefault(),
645:           KSPSolveTranspose(), KSPGetIterationNumber(), MatNullSpaceCreate(), MatSetNullSpace(), MatSetTransposeNullSpace(), KSP
646: @*/
647: PetscErrorCode KSPSolve(KSP ksp,Vec b,Vec x)
648: {
649:   PetscErrorCode    ierr;
650:   PetscBool         flg = PETSC_FALSE,inXisinB=PETSC_FALSE,guess_zero;
651:   Mat               mat,pmat;
652:   MPI_Comm          comm;
653:   MatNullSpace      nullsp;
654:   Vec               btmp,vec_rhs=0;

660:   comm = PetscObjectComm((PetscObject)ksp);
661:   if (x && x == b) {
662:     if (!ksp->guess_zero) SETERRQ(comm,PETSC_ERR_ARG_INCOMP,"Cannot use x == b with nonzero initial guess");
663:     VecDuplicate(b,&x);
664:     inXisinB = PETSC_TRUE;
665:   }
666:   if (b) {
667:     PetscObjectReference((PetscObject)b);
668:     VecDestroy(&ksp->vec_rhs);
669:     ksp->vec_rhs = b;
670:   }
671:   if (x) {
672:     PetscObjectReference((PetscObject)x);
673:     VecDestroy(&ksp->vec_sol);
674:     ksp->vec_sol = x;
675:   }
676:   if (ksp->viewPre) {ObjectView((PetscObject) ksp, ksp->viewerPre, ksp->formatPre);}

678:   ksp->transpose_solve = PETSC_FALSE;

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

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

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

687:   if (ksp->guess) {
688:     PetscObjectState ostate,state;

690:     KSPGuessSetUp(ksp->guess);
691:     PetscObjectStateGet((PetscObject)ksp->vec_sol,&ostate);
692:     KSPGuessFormGuess(ksp->guess,ksp->vec_rhs,ksp->vec_sol);
693:     PetscObjectStateGet((PetscObject)ksp->vec_sol,&state);
694:     if (state != ostate) {
695:       ksp->guess_zero = PETSC_FALSE;
696:     } else {
697:       PetscInfo(ksp,"Using zero initial guess since the KSPGuess object did not change the vector\n");
698:       ksp->guess_zero = PETSC_TRUE;
699:     }
700:   }

702:   /* KSPSetUp() scales the matrix if needed */
703:   KSPSetUp(ksp);
704:   KSPSetUpOnBlocks(ksp);

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

708:   PCGetOperators(ksp->pc,&mat,&pmat);
709:   /* diagonal scale RHS if called for */
710:   if (ksp->dscale) {
711:     VecPointwiseMult(ksp->vec_rhs,ksp->vec_rhs,ksp->diagonal);
712:     /* second time in, but matrix was scaled back to original */
713:     if (ksp->dscalefix && ksp->dscalefix2) {
714:       Mat mat,pmat;

716:       PCGetOperators(ksp->pc,&mat,&pmat);
717:       MatDiagonalScale(pmat,ksp->diagonal,ksp->diagonal);
718:       if (mat != pmat) {MatDiagonalScale(mat,ksp->diagonal,ksp->diagonal);}
719:     }

721:     /* scale initial guess */
722:     if (!ksp->guess_zero) {
723:       if (!ksp->truediagonal) {
724:         VecDuplicate(ksp->diagonal,&ksp->truediagonal);
725:         VecCopy(ksp->diagonal,ksp->truediagonal);
726:         VecReciprocal(ksp->truediagonal);
727:       }
728:       VecPointwiseMult(ksp->vec_sol,ksp->vec_sol,ksp->truediagonal);
729:     }
730:   }
731:   PCPreSolve(ksp->pc,ksp);

733:   if (ksp->guess_zero) { VecSet(ksp->vec_sol,0.0);}
734:   if (ksp->guess_knoll) { /* The Knoll trick is independent on the KSPGuess specified */
735:     PCApply(ksp->pc,ksp->vec_rhs,ksp->vec_sol);
736:     KSP_RemoveNullSpace(ksp,ksp->vec_sol);
737:     ksp->guess_zero = PETSC_FALSE;
738:   }

740:   /* can we mark the initial guess as zero for this solve? */
741:   guess_zero = ksp->guess_zero;
742:   if (!ksp->guess_zero) {
743:     PetscReal norm;

745:     VecNormAvailable(ksp->vec_sol,NORM_2,&flg,&norm);
746:     if (flg && !norm) ksp->guess_zero = PETSC_TRUE;
747:   }
748:   MatGetTransposeNullSpace(pmat,&nullsp);
749:   if (nullsp) {
750:     VecDuplicate(ksp->vec_rhs,&btmp);
751:     VecCopy(ksp->vec_rhs,btmp);
752:     MatNullSpaceRemove(nullsp,btmp);
753:     vec_rhs      = ksp->vec_rhs;
754:     ksp->vec_rhs = btmp;
755:   }
756:   VecLockReadPush(ksp->vec_rhs);
757:   if (ksp->reason == KSP_DIVERGED_PC_FAILED) {
758:     VecSetInf(ksp->vec_sol);
759:   }
760:   (*ksp->ops->solve)(ksp);

762:   VecLockReadPop(ksp->vec_rhs);
763:   if (nullsp) {
764:     ksp->vec_rhs = vec_rhs;
765:     VecDestroy(&btmp);
766:   }

768:   ksp->guess_zero = guess_zero;

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

773:   if (ksp->viewReason) {KSPReasonView_Internal(ksp, ksp->viewerReason, ksp->formatReason);}
774:   PCPostSolve(ksp->pc,ksp);

776:   /* diagonal scale solution if called for */
777:   if (ksp->dscale) {
778:     VecPointwiseMult(ksp->vec_sol,ksp->vec_sol,ksp->diagonal);
779:     /* unscale right hand side and matrix */
780:     if (ksp->dscalefix) {
781:       Mat mat,pmat;

783:       VecReciprocal(ksp->diagonal);
784:       VecPointwiseMult(ksp->vec_rhs,ksp->vec_rhs,ksp->diagonal);
785:       PCGetOperators(ksp->pc,&mat,&pmat);
786:       MatDiagonalScale(pmat,ksp->diagonal,ksp->diagonal);
787:       if (mat != pmat) {MatDiagonalScale(mat,ksp->diagonal,ksp->diagonal);}
788:       VecReciprocal(ksp->diagonal);
789:       ksp->dscalefix2 = PETSC_TRUE;
790:     }
791:   }
792:   PetscLogEventEnd(KSP_Solve,ksp,ksp->vec_rhs,ksp->vec_sol,0);
793:   if (ksp->guess) {
794:     KSPGuessUpdate(ksp->guess,ksp->vec_rhs,ksp->vec_sol);
795:   }
796:   if (ksp->postsolve) {
797:     (*ksp->postsolve)(ksp,ksp->vec_rhs,ksp->vec_sol,ksp->postctx);
798:   }

800:   PCGetOperators(ksp->pc,&mat,&pmat);
801:   if (ksp->viewEV)       {KSPViewEigenvalues_Internal(ksp, PETSC_FALSE, ksp->viewerEV,    ksp->formatEV);}
802:   if (ksp->viewEVExp)    {KSPViewEigenvalues_Internal(ksp, PETSC_TRUE,  ksp->viewerEVExp, ksp->formatEVExp);}
803:   if (ksp->viewSV)       {KSPViewSingularvalues_Internal(ksp, ksp->viewerSV, ksp->formatSV);}
804:   if (ksp->viewFinalRes) {KSPViewFinalResidual_Internal(ksp, ksp->viewerFinalRes, ksp->formatFinalRes);}
805:   if (ksp->viewMat)      {ObjectView((PetscObject) mat,           ksp->viewerMat,    ksp->formatMat);}
806:   if (ksp->viewPMat)     {ObjectView((PetscObject) pmat,          ksp->viewerPMat,   ksp->formatPMat);}
807:   if (ksp->viewRhs)      {ObjectView((PetscObject) ksp->vec_rhs,  ksp->viewerRhs,    ksp->formatRhs);}
808:   if (ksp->viewSol)      {ObjectView((PetscObject) ksp->vec_sol,  ksp->viewerSol,    ksp->formatSol);}
809:   if (ksp->view)         {ObjectView((PetscObject) ksp,           ksp->viewer,       ksp->format);}
810:   if (ksp->viewDScale)   {ObjectView((PetscObject) ksp->diagonal, ksp->viewerDScale, ksp->formatDScale);}
811:   if (ksp->viewMatExp)   {
812:     Mat A, B;

814:     PCGetOperators(ksp->pc, &A, NULL);
815:     MatComputeOperator(A, MATAIJ, &B);
816:     ObjectView((PetscObject) B, ksp->viewerMatExp, ksp->formatMatExp);
817:     MatDestroy(&B);
818:   }
819:   if (ksp->viewPOpExp)   {
820:     Mat B;

822:     KSPComputeOperator(ksp, MATAIJ, &B);
823:     ObjectView((PetscObject) B, ksp->viewerPOpExp, ksp->formatPOpExp);
824:     MatDestroy(&B);
825:   }

827:   if (inXisinB) {
828:     VecCopy(x,b);
829:     VecDestroy(&x);
830:   }
831:   PetscObjectSAWsBlock((PetscObject)ksp);
832:   if (ksp->errorifnotconverged && ksp->reason < 0 && ksp->reason != KSP_DIVERGED_ITS) SETERRQ1(comm,PETSC_ERR_NOT_CONVERGED,"KSPSolve has not converged, reason %s",KSPConvergedReasons[ksp->reason]);
833:   return(0);
834: }

836: /*@
837:    KSPSolveTranspose - Solves the transpose of a linear system.

839:    Collective on ksp

841:    Input Parameter:
842: +  ksp - iterative context obtained from KSPCreate()
843: .  b - right hand side vector
844: -  x - solution vector

846:    Notes:
847:     For complex numbers this solve the non-Hermitian transpose system.

849:    This currently does NOT correctly use the null space of the operator and its transpose for solving singular systems.

851:    Developer Notes:
852:     We need to implement a KSPSolveHermitianTranspose()

854:    Level: developer

856: .seealso: KSPCreate(), KSPSetUp(), KSPDestroy(), KSPSetTolerances(), KSPConvergedDefault(),
857:           KSPSolve(), KSP
858: @*/

860: PetscErrorCode  KSPSolveTranspose(KSP ksp,Vec b,Vec x)
861: {
863:   PetscBool      inXisinB=PETSC_FALSE;
864:   Vec            vec_rhs = 0,btmp;
865:   Mat            mat,pmat;
866:   MatNullSpace   nullsp;

872:   if (x == b) {
873:     VecDuplicate(b,&x);
874:     inXisinB = PETSC_TRUE;
875:   }
876:   PetscObjectReference((PetscObject)b);
877:   PetscObjectReference((PetscObject)x);
878:   VecDestroy(&ksp->vec_rhs);
879:   VecDestroy(&ksp->vec_sol);

881:   ksp->vec_rhs         = b;
882:   ksp->vec_sol         = x;
883:   ksp->transpose_solve = PETSC_TRUE;

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

887:   PetscLogEventBegin(KSP_SolveTranspose,ksp,ksp->vec_rhs,ksp->vec_sol,0);
888:   if (ksp->guess) {
889:     PetscObjectState ostate,state;

891:     KSPGuessSetUp(ksp->guess);
892:     PetscObjectStateGet((PetscObject)ksp->vec_sol,&ostate);
893:     KSPGuessFormGuess(ksp->guess,ksp->vec_rhs,ksp->vec_sol);
894:     PetscObjectStateGet((PetscObject)ksp->vec_sol,&state);
895:     if (state != ostate) {
896:       ksp->guess_zero = PETSC_FALSE;
897:     } else {
898:       PetscInfo(ksp,"Using zero initial guess since the KSPGuess object did not change the vector\n");
899:       ksp->guess_zero = PETSC_TRUE;
900:     }
901:   }

903:   KSPSetUp(ksp);
904:   KSPSetUpOnBlocks(ksp);
905:   if (ksp->guess_zero) { VecSet(ksp->vec_sol,0.0);}

907:   PCGetOperators(ksp->pc,&mat,&pmat);
908:   MatGetNullSpace(pmat,&nullsp);
909:   if (nullsp) {
910:     VecDuplicate(ksp->vec_rhs,&btmp);
911:     VecCopy(ksp->vec_rhs,btmp);
912:     MatNullSpaceRemove(nullsp,btmp);
913:     vec_rhs      = ksp->vec_rhs;
914:     ksp->vec_rhs = btmp;
915:   }

917:   (*ksp->ops->solve)(ksp);
918:   ksp->totalits += ksp->its;
919:   if (nullsp) {
920:     ksp->vec_rhs = vec_rhs;
921:     VecDestroy(&btmp);
922:   }
923:   if (!ksp->reason) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_PLIB,"Internal error, solver returned without setting converged reason");
924:   if (ksp->viewReason) {KSPReasonView_Internal(ksp, ksp->viewerReason, ksp->formatReason);}
925:   PetscLogEventEnd(KSP_SolveTranspose,ksp,ksp->vec_rhs,ksp->vec_sol,0);
926:   if (ksp->guess) {
927:     KSPGuessUpdate(ksp->guess,ksp->vec_rhs,ksp->vec_sol);
928:   }
929:   if (ksp->postsolve) {
930:     (*ksp->postsolve)(ksp,ksp->vec_rhs,ksp->vec_sol,ksp->postctx);
931:   }

933:   if (ksp->viewMat)      {ObjectView((PetscObject) mat,          ksp->viewerMat,  ksp->formatMat);}
934:   if (ksp->viewPMat)     {ObjectView((PetscObject) pmat,         ksp->viewerPMat, ksp->formatPMat);}
935:   if (ksp->viewRhs)      {ObjectView((PetscObject) ksp->vec_rhs, ksp->viewerRhs,  ksp->formatRhs);}
936:   if (ksp->viewSol)      {ObjectView((PetscObject) ksp->vec_sol, ksp->viewerSol,  ksp->formatSol);}
937:   if (ksp->view)         {ObjectView((PetscObject) ksp,          ksp->viewer,     ksp->format);}

939:   if (inXisinB) {
940:     VecCopy(x,b);
941:     VecDestroy(&x);
942:   }
943:   if (ksp->errorifnotconverged && ksp->reason < 0) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_NOT_CONVERGED,"KSPSolve has not converged");
944:   return(0);
945: }

947: /*@
948:    KSPResetViewers - Resets all the viewers set from the options database during KSPSetFromOptions()

950:    Collective on ksp

952:    Input Parameter:
953: .  ksp - iterative context obtained from KSPCreate()

955:    Level: beginner

957: .seealso: KSPCreate(), KSPSetUp(), KSPSolve(), KSPSetFromOptions(), KSP
958: @*/
959: PetscErrorCode  KSPResetViewers(KSP ksp)
960: {

965:   if (!ksp) return(0);
966:   PetscViewerDestroy(&ksp->viewer);
967:   PetscViewerDestroy(&ksp->viewerPre);
968:   PetscViewerDestroy(&ksp->viewerReason);
969:   PetscViewerDestroy(&ksp->viewerMat);
970:   PetscViewerDestroy(&ksp->viewerPMat);
971:   PetscViewerDestroy(&ksp->viewerRhs);
972:   PetscViewerDestroy(&ksp->viewerSol);
973:   PetscViewerDestroy(&ksp->viewerMatExp);
974:   PetscViewerDestroy(&ksp->viewerEV);
975:   PetscViewerDestroy(&ksp->viewerSV);
976:   PetscViewerDestroy(&ksp->viewerEVExp);
977:   PetscViewerDestroy(&ksp->viewerFinalRes);
978:   PetscViewerDestroy(&ksp->viewerPOpExp);
979:   PetscViewerDestroy(&ksp->viewerDScale);
980:   ksp->view         = PETSC_FALSE;
981:   ksp->viewPre      = PETSC_FALSE;
982:   ksp->viewReason   = PETSC_FALSE;
983:   ksp->viewMat      = PETSC_FALSE;
984:   ksp->viewPMat     = PETSC_FALSE;
985:   ksp->viewRhs      = PETSC_FALSE;
986:   ksp->viewSol      = PETSC_FALSE;
987:   ksp->viewMatExp   = PETSC_FALSE;
988:   ksp->viewEV       = PETSC_FALSE;
989:   ksp->viewSV       = PETSC_FALSE;
990:   ksp->viewEVExp    = PETSC_FALSE;
991:   ksp->viewFinalRes = PETSC_FALSE;
992:   ksp->viewPOpExp   = PETSC_FALSE;
993:   ksp->viewDScale   = PETSC_FALSE;
994:   return(0);
995: }

997: /*@
998:    KSPReset - Resets a KSP context to the kspsetupcalled = 0 state and removes any allocated Vecs and Mats

1000:    Collective on ksp

1002:    Input Parameter:
1003: .  ksp - iterative context obtained from KSPCreate()

1005:    Level: beginner

1007: .seealso: KSPCreate(), KSPSetUp(), KSPSolve(), KSP
1008: @*/
1009: PetscErrorCode  KSPReset(KSP ksp)
1010: {

1015:   if (!ksp) return(0);
1016:   if (ksp->ops->reset) {
1017:     (*ksp->ops->reset)(ksp);
1018:   }
1019:   if (ksp->pc) {PCReset(ksp->pc);}
1020:   if (ksp->guess) {
1021:     KSPGuess guess = ksp->guess;
1022:     if (guess->ops->reset) { (*guess->ops->reset)(guess); }
1023:   }
1024:   VecDestroyVecs(ksp->nwork,&ksp->work);
1025:   VecDestroy(&ksp->vec_rhs);
1026:   VecDestroy(&ksp->vec_sol);
1027:   VecDestroy(&ksp->diagonal);
1028:   VecDestroy(&ksp->truediagonal);

1030:   KSPResetViewers(ksp);

1032:   ksp->setupstage = KSP_SETUP_NEW;
1033:   return(0);
1034: }

1036: /*@
1037:    KSPDestroy - Destroys KSP context.

1039:    Collective on ksp

1041:    Input Parameter:
1042: .  ksp - iterative context obtained from KSPCreate()

1044:    Level: beginner

1046: .seealso: KSPCreate(), KSPSetUp(), KSPSolve(), KSP
1047: @*/
1048: PetscErrorCode  KSPDestroy(KSP *ksp)
1049: {
1051:   PC             pc;

1054:   if (!*ksp) return(0);
1056:   if (--((PetscObject)(*ksp))->refct > 0) {*ksp = 0; return(0);}

1058:   PetscObjectSAWsViewOff((PetscObject)*ksp);

1060:   /*
1061:    Avoid a cascading call to PCReset(ksp->pc) from the following call:
1062:    PCReset() shouldn't be called from KSPDestroy() as it is unprotected by pc's
1063:    refcount (and may be shared, e.g., by other ksps).
1064:    */
1065:   pc         = (*ksp)->pc;
1066:   (*ksp)->pc = NULL;
1067:   KSPReset((*ksp));
1068:   (*ksp)->pc = pc;
1069:   if ((*ksp)->ops->destroy) {(*(*ksp)->ops->destroy)(*ksp);}

1071:   KSPGuessDestroy(&(*ksp)->guess);
1072:   DMDestroy(&(*ksp)->dm);
1073:   PCDestroy(&(*ksp)->pc);
1074:   PetscFree((*ksp)->res_hist_alloc);
1075:   if ((*ksp)->convergeddestroy) {
1076:     (*(*ksp)->convergeddestroy)((*ksp)->cnvP);
1077:   }
1078:   KSPMonitorCancel((*ksp));
1079:   PetscViewerDestroy(&(*ksp)->eigviewer);
1080:   PetscHeaderDestroy(ksp);
1081:   return(0);
1082: }

1084: /*@
1085:     KSPSetPCSide - Sets the preconditioning side.

1087:     Logically Collective on ksp

1089:     Input Parameter:
1090: .   ksp - iterative context obtained from KSPCreate()

1092:     Output Parameter:
1093: .   side - the preconditioning side, where side is one of
1094: .vb
1095:       PC_LEFT - left preconditioning (default)
1096:       PC_RIGHT - right preconditioning
1097:       PC_SYMMETRIC - symmetric preconditioning
1098: .ve

1100:     Options Database Keys:
1101: .   -ksp_pc_side <right,left,symmetric>

1103:     Notes:
1104:     Left preconditioning is used by default for most Krylov methods except KSPFGMRES which only supports right preconditioning.

1106:     For methods changing the side of the preconditioner changes the norm type that is used, see KSPSetNormType().

1108:     Symmetric preconditioning is currently available only for the KSPQCG method. Note, however, that
1109:     symmetric preconditioning can be emulated by using either right or left
1110:     preconditioning and a pre or post processing step.

1112:     Setting the PC side often affects the default norm type.  See KSPSetNormType() for details.

1114:     Level: intermediate

1116: .seealso: KSPGetPCSide(), KSPSetNormType(), KSPGetNormType(), KSP
1117: @*/
1118: PetscErrorCode  KSPSetPCSide(KSP ksp,PCSide side)
1119: {
1123:   ksp->pc_side = ksp->pc_side_set = side;
1124:   return(0);
1125: }

1127: /*@
1128:     KSPGetPCSide - Gets the preconditioning side.

1130:     Not Collective

1132:     Input Parameter:
1133: .   ksp - iterative context obtained from KSPCreate()

1135:     Output Parameter:
1136: .   side - the preconditioning side, where side is one of
1137: .vb
1138:       PC_LEFT - left preconditioning (default)
1139:       PC_RIGHT - right preconditioning
1140:       PC_SYMMETRIC - symmetric preconditioning
1141: .ve

1143:     Level: intermediate

1145: .seealso: KSPSetPCSide(), KSP
1146: @*/
1147: PetscErrorCode  KSPGetPCSide(KSP ksp,PCSide *side)
1148: {

1154:   KSPSetUpNorms_Private(ksp,PETSC_TRUE,&ksp->normtype,&ksp->pc_side);
1155:   *side = ksp->pc_side;
1156:   return(0);
1157: }

1159: /*@
1160:    KSPGetTolerances - Gets the relative, absolute, divergence, and maximum
1161:    iteration tolerances used by the default KSP convergence tests.

1163:    Not Collective

1165:    Input Parameter:
1166: .  ksp - the Krylov subspace context

1168:    Output Parameters:
1169: +  rtol - the relative convergence tolerance
1170: .  abstol - the absolute convergence tolerance
1171: .  dtol - the divergence tolerance
1172: -  maxits - maximum number of iterations

1174:    Notes:
1175:    The user can specify NULL for any parameter that is not needed.

1177:    Level: intermediate

1179:            maximum, iterations

1181: .seealso: KSPSetTolerances(), KSP
1182: @*/
1183: PetscErrorCode  KSPGetTolerances(KSP ksp,PetscReal *rtol,PetscReal *abstol,PetscReal *dtol,PetscInt *maxits)
1184: {
1187:   if (abstol) *abstol = ksp->abstol;
1188:   if (rtol) *rtol = ksp->rtol;
1189:   if (dtol) *dtol = ksp->divtol;
1190:   if (maxits) *maxits = ksp->max_it;
1191:   return(0);
1192: }

1194: /*@
1195:    KSPSetTolerances - Sets the relative, absolute, divergence, and maximum
1196:    iteration tolerances used by the default KSP convergence testers.

1198:    Logically Collective on ksp

1200:    Input Parameters:
1201: +  ksp - the Krylov subspace context
1202: .  rtol - the relative convergence tolerance, relative decrease in the (possibly preconditioned) residual norm
1203: .  abstol - the absolute convergence tolerance   absolute size of the (possibly preconditioned) residual norm
1204: .  dtol - the divergence tolerance,   amount (possibly preconditioned) residual norm can increase before KSPConvergedDefault() concludes that the method is diverging
1205: -  maxits - maximum number of iterations to use

1207:    Options Database Keys:
1208: +  -ksp_atol <abstol> - Sets abstol
1209: .  -ksp_rtol <rtol> - Sets rtol
1210: .  -ksp_divtol <dtol> - Sets dtol
1211: -  -ksp_max_it <maxits> - Sets maxits

1213:    Notes:
1214:    Use PETSC_DEFAULT to retain the default value of any of the tolerances.

1216:    See KSPConvergedDefault() for details how these parameters are used in the default convergence test.  See also KSPSetConvergenceTest()
1217:    for setting user-defined stopping criteria.

1219:    Level: intermediate

1221:            convergence, maximum, iterations

1223: .seealso: KSPGetTolerances(), KSPConvergedDefault(), KSPSetConvergenceTest(), KSP
1224: @*/
1225: PetscErrorCode  KSPSetTolerances(KSP ksp,PetscReal rtol,PetscReal abstol,PetscReal dtol,PetscInt maxits)
1226: {

1234:   if (rtol != PETSC_DEFAULT) {
1235:     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);
1236:     ksp->rtol = rtol;
1237:   }
1238:   if (abstol != PETSC_DEFAULT) {
1239:     if (abstol < 0.0) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Absolute tolerance %g must be non-negative",(double)abstol);
1240:     ksp->abstol = abstol;
1241:   }
1242:   if (dtol != PETSC_DEFAULT) {
1243:     if (dtol < 0.0) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Divergence tolerance %g must be larger than 1.0",(double)dtol);
1244:     ksp->divtol = dtol;
1245:   }
1246:   if (maxits != PETSC_DEFAULT) {
1247:     if (maxits < 0) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Maximum number of iterations %D must be non-negative",maxits);
1248:     ksp->max_it = maxits;
1249:   }
1250:   return(0);
1251: }

1253: /*@
1254:    KSPSetInitialGuessNonzero - Tells the iterative solver that the
1255:    initial guess is nonzero; otherwise KSP assumes the initial guess
1256:    is to be zero (and thus zeros it out before solving).

1258:    Logically Collective on ksp

1260:    Input Parameters:
1261: +  ksp - iterative context obtained from KSPCreate()
1262: -  flg - PETSC_TRUE indicates the guess is non-zero, PETSC_FALSE indicates the guess is zero

1264:    Options database keys:
1265: .  -ksp_initial_guess_nonzero : use nonzero initial guess; this takes an optional truth value (0/1/no/yes/true/false)

1267:    Level: beginner

1269:    Notes:
1270:     If this is not called the X vector is zeroed in the call to KSPSolve().

1272: .seealso: KSPGetInitialGuessNonzero(), KSPSetGuessType(), KSPGuessType, KSP
1273: @*/
1274: PetscErrorCode  KSPSetInitialGuessNonzero(KSP ksp,PetscBool flg)
1275: {
1279:   ksp->guess_zero = (PetscBool) !(int)flg;
1280:   return(0);
1281: }

1283: /*@
1284:    KSPGetInitialGuessNonzero - Determines whether the KSP solver is using
1285:    a zero initial guess.

1287:    Not Collective

1289:    Input Parameter:
1290: .  ksp - iterative context obtained from KSPCreate()

1292:    Output Parameter:
1293: .  flag - PETSC_TRUE if guess is nonzero, else PETSC_FALSE

1295:    Level: intermediate

1297: .seealso: KSPSetInitialGuessNonzero(), KSP
1298: @*/
1299: PetscErrorCode  KSPGetInitialGuessNonzero(KSP ksp,PetscBool  *flag)
1300: {
1304:   if (ksp->guess_zero) *flag = PETSC_FALSE;
1305:   else *flag = PETSC_TRUE;
1306:   return(0);
1307: }

1309: /*@
1310:    KSPSetErrorIfNotConverged - Causes KSPSolve() to generate an error if the solver has not converged.

1312:    Logically Collective on ksp

1314:    Input Parameters:
1315: +  ksp - iterative context obtained from KSPCreate()
1316: -  flg - PETSC_TRUE indicates you want the error generated

1318:    Options database keys:
1319: .  -ksp_error_if_not_converged : this takes an optional truth value (0/1/no/yes/true/false)

1321:    Level: intermediate

1323:    Notes:
1324:     Normally PETSc continues if a linear solver fails to converge, you can call KSPGetConvergedReason() after a KSPSolve()
1325:     to determine if it has converged.


1328: .seealso: KSPGetErrorIfNotConverged(), KSP
1329: @*/
1330: PetscErrorCode  KSPSetErrorIfNotConverged(KSP ksp,PetscBool flg)
1331: {
1335:   ksp->errorifnotconverged = flg;
1336:   return(0);
1337: }

1339: /*@
1340:    KSPGetErrorIfNotConverged - Will KSPSolve() generate an error if the solver does not converge?

1342:    Not Collective

1344:    Input Parameter:
1345: .  ksp - iterative context obtained from KSPCreate()

1347:    Output Parameter:
1348: .  flag - PETSC_TRUE if it will generate an error, else PETSC_FALSE

1350:    Level: intermediate

1352: .seealso: KSPSetErrorIfNotConverged(), KSP
1353: @*/
1354: PetscErrorCode  KSPGetErrorIfNotConverged(KSP ksp,PetscBool  *flag)
1355: {
1359:   *flag = ksp->errorifnotconverged;
1360:   return(0);
1361: }

1363: /*@
1364:    KSPSetInitialGuessKnoll - Tells the iterative solver to use PCApply(pc,b,..) to compute the initial guess (The Knoll trick)

1366:    Logically Collective on ksp

1368:    Input Parameters:
1369: +  ksp - iterative context obtained from KSPCreate()
1370: -  flg - PETSC_TRUE or PETSC_FALSE

1372:    Level: advanced

1374:    Developer Note: the Knoll trick is not currently implemented using the KSPGuess class

1376: .seealso: KSPGetInitialGuessKnoll(), KSPSetInitialGuessNonzero(), KSPGetInitialGuessNonzero(), KSP
1377: @*/
1378: PetscErrorCode  KSPSetInitialGuessKnoll(KSP ksp,PetscBool flg)
1379: {
1383:   ksp->guess_knoll = flg;
1384:   return(0);
1385: }

1387: /*@
1388:    KSPGetInitialGuessKnoll - Determines whether the KSP solver is using the Knoll trick (using PCApply(pc,b,...) to compute
1389:      the initial guess

1391:    Not Collective

1393:    Input Parameter:
1394: .  ksp - iterative context obtained from KSPCreate()

1396:    Output Parameter:
1397: .  flag - PETSC_TRUE if using Knoll trick, else PETSC_FALSE

1399:    Level: advanced

1401: .seealso: KSPSetInitialGuessKnoll(), KSPSetInitialGuessNonzero(), KSPGetInitialGuessNonzero(), KSP
1402: @*/
1403: PetscErrorCode  KSPGetInitialGuessKnoll(KSP ksp,PetscBool  *flag)
1404: {
1408:   *flag = ksp->guess_knoll;
1409:   return(0);
1410: }

1412: /*@
1413:    KSPGetComputeSingularValues - Gets the flag indicating whether the extreme singular
1414:    values will be calculated via a Lanczos or Arnoldi process as the linear
1415:    system is solved.

1417:    Not Collective

1419:    Input Parameter:
1420: .  ksp - iterative context obtained from KSPCreate()

1422:    Output Parameter:
1423: .  flg - PETSC_TRUE or PETSC_FALSE

1425:    Options Database Key:
1426: .  -ksp_monitor_singular_value - Activates KSPSetComputeSingularValues()

1428:    Notes:
1429:    Currently this option is not valid for all iterative methods.

1431:    Many users may just want to use the monitoring routine
1432:    KSPMonitorSingularValue() (which can be set with option -ksp_monitor_singular_value)
1433:    to print the singular values at each iteration of the linear solve.

1435:    Level: advanced

1437: .seealso: KSPComputeExtremeSingularValues(), KSPMonitorSingularValue(), KSP
1438: @*/
1439: PetscErrorCode  KSPGetComputeSingularValues(KSP ksp,PetscBool  *flg)
1440: {
1444:   *flg = ksp->calc_sings;
1445:   return(0);
1446: }

1448: /*@
1449:    KSPSetComputeSingularValues - Sets a flag so that the extreme singular
1450:    values will be calculated via a Lanczos or Arnoldi process as the linear
1451:    system is solved.

1453:    Logically Collective on ksp

1455:    Input Parameters:
1456: +  ksp - iterative context obtained from KSPCreate()
1457: -  flg - PETSC_TRUE or PETSC_FALSE

1459:    Options Database Key:
1460: .  -ksp_monitor_singular_value - Activates KSPSetComputeSingularValues()

1462:    Notes:
1463:    Currently this option is not valid for all iterative methods.

1465:    Many users may just want to use the monitoring routine
1466:    KSPMonitorSingularValue() (which can be set with option -ksp_monitor_singular_value)
1467:    to print the singular values at each iteration of the linear solve.

1469:    Level: advanced

1471: .seealso: KSPComputeExtremeSingularValues(), KSPMonitorSingularValue(), KSP
1472: @*/
1473: PetscErrorCode  KSPSetComputeSingularValues(KSP ksp,PetscBool flg)
1474: {
1478:   ksp->calc_sings = flg;
1479:   return(0);
1480: }

1482: /*@
1483:    KSPGetComputeEigenvalues - Gets the flag indicating that the extreme eigenvalues
1484:    values will be calculated via a Lanczos or Arnoldi process as the linear
1485:    system is solved.

1487:    Not Collective

1489:    Input Parameter:
1490: .  ksp - iterative context obtained from KSPCreate()

1492:    Output Parameter:
1493: .  flg - PETSC_TRUE or PETSC_FALSE

1495:    Notes:
1496:    Currently this option is not valid for all iterative methods.

1498:    Level: advanced

1500: .seealso: KSPComputeEigenvalues(), KSPComputeEigenvaluesExplicitly(), KSP
1501: @*/
1502: PetscErrorCode  KSPGetComputeEigenvalues(KSP ksp,PetscBool  *flg)
1503: {
1507:   *flg = ksp->calc_sings;
1508:   return(0);
1509: }

1511: /*@
1512:    KSPSetComputeEigenvalues - Sets a flag so that the extreme eigenvalues
1513:    values will be calculated via a Lanczos or Arnoldi process as the linear
1514:    system is solved.

1516:    Logically Collective on ksp

1518:    Input Parameters:
1519: +  ksp - iterative context obtained from KSPCreate()
1520: -  flg - PETSC_TRUE or PETSC_FALSE

1522:    Notes:
1523:    Currently this option is not valid for all iterative methods.

1525:    Level: advanced

1527: .seealso: KSPComputeEigenvalues(), KSPComputeEigenvaluesExplicitly(), KSP
1528: @*/
1529: PetscErrorCode  KSPSetComputeEigenvalues(KSP ksp,PetscBool flg)
1530: {
1534:   ksp->calc_sings = flg;
1535:   return(0);
1536: }

1538: /*@
1539:    KSPSetComputeRitz - Sets a flag so that the Ritz or harmonic Ritz pairs
1540:    will be calculated via a Lanczos or Arnoldi process as the linear
1541:    system is solved.

1543:    Logically Collective on ksp

1545:    Input Parameters:
1546: +  ksp - iterative context obtained from KSPCreate()
1547: -  flg - PETSC_TRUE or PETSC_FALSE

1549:    Notes:
1550:    Currently this option is only valid for the GMRES method.

1552:    Level: advanced

1554: .seealso: KSPComputeRitz(), KSP
1555: @*/
1556: PetscErrorCode  KSPSetComputeRitz(KSP ksp, PetscBool flg)
1557: {
1561:   ksp->calc_ritz = flg;
1562:   return(0);
1563: }

1565: /*@
1566:    KSPGetRhs - Gets the right-hand-side vector for the linear system to
1567:    be solved.

1569:    Not Collective

1571:    Input Parameter:
1572: .  ksp - iterative context obtained from KSPCreate()

1574:    Output Parameter:
1575: .  r - right-hand-side vector

1577:    Level: developer

1579: .seealso: KSPGetSolution(), KSPSolve(), KSP
1580: @*/
1581: PetscErrorCode  KSPGetRhs(KSP ksp,Vec *r)
1582: {
1586:   *r = ksp->vec_rhs;
1587:   return(0);
1588: }

1590: /*@
1591:    KSPGetSolution - Gets the location of the solution for the
1592:    linear system to be solved.  Note that this may not be where the solution
1593:    is stored during the iterative process; see KSPBuildSolution().

1595:    Not Collective

1597:    Input Parameters:
1598: .  ksp - iterative context obtained from KSPCreate()

1600:    Output Parameters:
1601: .  v - solution vector

1603:    Level: developer

1605: .seealso: KSPGetRhs(),  KSPBuildSolution(), KSPSolve(), KSP
1606: @*/
1607: PetscErrorCode  KSPGetSolution(KSP ksp,Vec *v)
1608: {
1612:   *v = ksp->vec_sol;
1613:   return(0);
1614: }

1616: /*@
1617:    KSPSetPC - Sets the preconditioner to be used to calculate the
1618:    application of the preconditioner on a vector.

1620:    Collective on ksp

1622:    Input Parameters:
1623: +  ksp - iterative context obtained from KSPCreate()
1624: -  pc   - the preconditioner object

1626:    Notes:
1627:    Use KSPGetPC() to retrieve the preconditioner context (for example,
1628:    to free it at the end of the computations).

1630:    Level: developer

1632: .seealso: KSPGetPC(), KSP
1633: @*/
1634: PetscErrorCode  KSPSetPC(KSP ksp,PC pc)
1635: {

1642:   PetscObjectReference((PetscObject)pc);
1643:   PCDestroy(&ksp->pc);
1644:   ksp->pc = pc;
1645:   PetscLogObjectParent((PetscObject)ksp,(PetscObject)ksp->pc);
1646:   return(0);
1647: }

1649: /*@
1650:    KSPGetPC - Returns a pointer to the preconditioner context
1651:    set with KSPSetPC().

1653:    Not Collective

1655:    Input Parameters:
1656: .  ksp - iterative context obtained from KSPCreate()

1658:    Output Parameter:
1659: .  pc - preconditioner context

1661:    Level: developer

1663: .seealso: KSPSetPC(), KSP
1664: @*/
1665: PetscErrorCode  KSPGetPC(KSP ksp,PC *pc)
1666: {

1672:   if (!ksp->pc) {
1673:     PCCreate(PetscObjectComm((PetscObject)ksp),&ksp->pc);
1674:     PetscObjectIncrementTabLevel((PetscObject)ksp->pc,(PetscObject)ksp,0);
1675:     PetscLogObjectParent((PetscObject)ksp,(PetscObject)ksp->pc);
1676:     PetscObjectSetOptions((PetscObject)ksp->pc,((PetscObject)ksp)->options);
1677:   }
1678:   *pc = ksp->pc;
1679:   return(0);
1680: }

1682: /*@
1683:    KSPMonitor - runs the user provided monitor routines, if they exist

1685:    Collective on ksp

1687:    Input Parameters:
1688: +  ksp - iterative context obtained from KSPCreate()
1689: .  it - iteration number
1690: -  rnorm - relative norm of the residual

1692:    Notes:
1693:    This routine is called by the KSP implementations.
1694:    It does not typically need to be called by the user.

1696:    Level: developer

1698: .seealso: KSPMonitorSet()
1699: @*/
1700: PetscErrorCode KSPMonitor(KSP ksp,PetscInt it,PetscReal rnorm)
1701: {
1702:   PetscInt       i, n = ksp->numbermonitors;

1706:   for (i=0; i<n; i++) {
1707:     (*ksp->monitor[i])(ksp,it,rnorm,ksp->monitorcontext[i]);
1708:   }
1709:   return(0);
1710: }

1712: /*

1714:     Checks if two monitors are identical; if they are then it destroys the new one
1715: */
1716: PetscErrorCode PetscMonitorCompare(PetscErrorCode (*nmon)(void),void *nmctx,PetscErrorCode (*nmdestroy)(void**),PetscErrorCode (*mon)(void),void *mctx,PetscErrorCode (*mdestroy)(void**),PetscBool *identical)
1717: {
1718:   *identical = PETSC_FALSE;
1719:   if (nmon == mon && nmdestroy == mdestroy) {
1720:     if (nmctx == mctx) *identical = PETSC_TRUE;
1721:     else if (nmdestroy == (PetscErrorCode (*)(void**)) PetscViewerAndFormatDestroy) {
1722:       PetscViewerAndFormat *old = (PetscViewerAndFormat*)mctx, *newo = (PetscViewerAndFormat*)nmctx;
1723:       if (old->viewer == newo->viewer && old->format == newo->format) *identical = PETSC_TRUE;
1724:     }
1725:     if (*identical) {
1726:       if (mdestroy) {
1728:         (*mdestroy)(&nmctx);
1729:       }
1730:     }
1731:   }
1732:   return(0);
1733: }

1735: /*@C
1736:    KSPMonitorSet - Sets an ADDITIONAL function to be called at every iteration to monitor
1737:    the residual/error etc.

1739:    Logically Collective on ksp

1741:    Input Parameters:
1742: +  ksp - iterative context obtained from KSPCreate()
1743: .  monitor - pointer to function (if this is NULL, it turns off monitoring
1744: .  mctx    - [optional] context for private data for the
1745:              monitor routine (use NULL if no context is desired)
1746: -  monitordestroy - [optional] routine that frees monitor context
1747:           (may be NULL)

1749:    Calling Sequence of monitor:
1750: $     monitor (KSP ksp, PetscInt it, PetscReal rnorm, void *mctx)

1752: +  ksp - iterative context obtained from KSPCreate()
1753: .  it - iteration number
1754: .  rnorm - (estimated) 2-norm of (preconditioned) residual
1755: -  mctx  - optional monitoring context, as set by KSPMonitorSet()

1757:    Options Database Keys:
1758: +    -ksp_monitor        - sets KSPMonitorDefault()
1759: .    -ksp_monitor_true_residual    - sets KSPMonitorTrueResidualNorm()
1760: .    -ksp_monitor_max    - sets KSPMonitorTrueResidualMaxNorm()
1761: .    -ksp_monitor_lg_residualnorm    - sets line graph monitor,
1762:                            uses KSPMonitorLGResidualNormCreate()
1763: .    -ksp_monitor_lg_true_residualnorm   - sets line graph monitor,
1764:                            uses KSPMonitorLGResidualNormCreate()
1765: .    -ksp_monitor_singular_value    - sets KSPMonitorSingularValue()
1766: -    -ksp_monitor_cancel - cancels all monitors that have
1767:                           been hardwired into a code by
1768:                           calls to KSPMonitorSet(), but
1769:                           does not cancel those set via
1770:                           the options database.

1772:    Notes:
1773:    The default is to do nothing.  To print the residual, or preconditioned
1774:    residual if KSPSetNormType(ksp,KSP_NORM_PRECONDITIONED) was called, use
1775:    KSPMonitorDefault() as the monitoring routine, with a ASCII viewer as the
1776:    context.

1778:    Several different monitoring routines may be set by calling
1779:    KSPMonitorSet() multiple times; all will be called in the
1780:    order in which they were set.

1782:    Fortran Notes:
1783:     Only a single monitor function can be set for each KSP object

1785:    Level: beginner

1787: .seealso: KSPMonitorDefault(), KSPMonitorLGResidualNormCreate(), KSPMonitorCancel(), KSP
1788: @*/
1789: PetscErrorCode  KSPMonitorSet(KSP ksp,PetscErrorCode (*monitor)(KSP,PetscInt,PetscReal,void*),void *mctx,PetscErrorCode (*monitordestroy)(void**))
1790: {
1791:   PetscInt       i;
1793:   PetscBool      identical;

1797:   for (i=0; i<ksp->numbermonitors;i++) {
1798:     PetscMonitorCompare((PetscErrorCode (*)(void))monitor,mctx,monitordestroy,(PetscErrorCode (*)(void))ksp->monitor[i],ksp->monitorcontext[i],ksp->monitordestroy[i],&identical);
1799:     if (identical) return(0);
1800:   }
1801:   if (ksp->numbermonitors >= MAXKSPMONITORS) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Too many KSP monitors set");
1802:   ksp->monitor[ksp->numbermonitors]          = monitor;
1803:   ksp->monitordestroy[ksp->numbermonitors]   = monitordestroy;
1804:   ksp->monitorcontext[ksp->numbermonitors++] = (void*)mctx;
1805:   return(0);
1806: }

1808: /*@
1809:    KSPMonitorCancel - Clears all monitors for a KSP object.

1811:    Logically Collective on ksp

1813:    Input Parameters:
1814: .  ksp - iterative context obtained from KSPCreate()

1816:    Options Database Key:
1817: .  -ksp_monitor_cancel - Cancels all monitors that have
1818:     been hardwired into a code by calls to KSPMonitorSet(),
1819:     but does not cancel those set via the options database.

1821:    Level: intermediate

1823: .seealso: KSPMonitorDefault(), KSPMonitorLGResidualNormCreate(), KSPMonitorSet(), KSP
1824: @*/
1825: PetscErrorCode  KSPMonitorCancel(KSP ksp)
1826: {
1828:   PetscInt       i;

1832:   for (i=0; i<ksp->numbermonitors; i++) {
1833:     if (ksp->monitordestroy[i]) {
1834:       (*ksp->monitordestroy[i])(&ksp->monitorcontext[i]);
1835:     }
1836:   }
1837:   ksp->numbermonitors = 0;
1838:   return(0);
1839: }

1841: /*@C
1842:    KSPGetMonitorContext - Gets the monitoring context, as set by
1843:    KSPMonitorSet() for the FIRST monitor only.

1845:    Not Collective

1847:    Input Parameter:
1848: .  ksp - iterative context obtained from KSPCreate()

1850:    Output Parameter:
1851: .  ctx - monitoring context

1853:    Level: intermediate

1855: .seealso: KSPMonitorDefault(), KSPMonitorLGResidualNormCreate(), KSP
1856: @*/
1857: PetscErrorCode  KSPGetMonitorContext(KSP ksp,void **ctx)
1858: {
1861:   *ctx =      (ksp->monitorcontext[0]);
1862:   return(0);
1863: }

1865: /*@
1866:    KSPSetResidualHistory - Sets the array used to hold the residual history.
1867:    If set, this array will contain the residual norms computed at each
1868:    iteration of the solver.

1870:    Not Collective

1872:    Input Parameters:
1873: +  ksp - iterative context obtained from KSPCreate()
1874: .  a   - array to hold history
1875: .  na  - size of a
1876: -  reset - PETSC_TRUE indicates the history counter is reset to zero
1877:            for each new linear solve

1879:    Level: advanced

1881:    Notes:
1882:     The array is NOT freed by PETSc so the user needs to keep track of
1883:            it and destroy once the KSP object is destroyed.

1885:    If 'a' is NULL then space is allocated for the history. If 'na' PETSC_DECIDE or PETSC_DEFAULT then a
1886:    default array of length 10000 is allocated.

1888: .seealso: KSPGetResidualHistory(), KSP

1890: @*/
1891: PetscErrorCode  KSPSetResidualHistory(KSP ksp,PetscReal a[],PetscInt na,PetscBool reset)
1892: {


1898:   PetscFree(ksp->res_hist_alloc);
1899:   if (na != PETSC_DECIDE && na != PETSC_DEFAULT && a) {
1900:     ksp->res_hist     = a;
1901:     ksp->res_hist_max = na;
1902:   } else {
1903:     if (na != PETSC_DECIDE && na != PETSC_DEFAULT) ksp->res_hist_max = na;
1904:     else                                           ksp->res_hist_max = 10000; /* like default ksp->max_it */
1905:     PetscCalloc1(ksp->res_hist_max,&ksp->res_hist_alloc);

1907:     ksp->res_hist = ksp->res_hist_alloc;
1908:   }
1909:   ksp->res_hist_len   = 0;
1910:   ksp->res_hist_reset = reset;
1911:   return(0);
1912: }

1914: /*@C
1915:    KSPGetResidualHistory - Gets the array used to hold the residual history
1916:    and the number of residuals it contains.

1918:    Not Collective

1920:    Input Parameter:
1921: .  ksp - iterative context obtained from KSPCreate()

1923:    Output Parameters:
1924: +  a   - pointer to array to hold history (or NULL)
1925: -  na  - number of used entries in a (or NULL)

1927:    Level: advanced

1929:    Notes:
1930:      Can only be called after a KSPSetResidualHistory() otherwise a and na are set to zero

1932:      The Fortran version of this routine has a calling sequence
1933: $   call KSPGetResidualHistory(KSP ksp, integer na, integer ierr)
1934:     note that you have passed a Fortran array into KSPSetResidualHistory() and you need
1935:     to access the residual values from this Fortran array you provided. Only the na (number of
1936:     residual norms currently held) is set.

1938: .seealso: KSPGetResidualHistory(), KSP

1940: @*/
1941: PetscErrorCode  KSPGetResidualHistory(KSP ksp,PetscReal *a[],PetscInt *na)
1942: {
1945:   if (a) *a = ksp->res_hist;
1946:   if (na) *na = ksp->res_hist_len;
1947:   return(0);
1948: }

1950: /*@C
1951:    KSPSetConvergenceTest - Sets the function to be used to determine
1952:    convergence.

1954:    Logically Collective on ksp

1956:    Input Parameters:
1957: +  ksp - iterative context obtained from KSPCreate()
1958: .  converge - pointer to the function
1959: .  cctx    - context for private data for the convergence routine (may be null)
1960: -  destroy - a routine for destroying the context (may be null)

1962:    Calling sequence of converge:
1963: $     converge (KSP ksp, PetscInt it, PetscReal rnorm, KSPConvergedReason *reason,void *mctx)

1965: +  ksp - iterative context obtained from KSPCreate()
1966: .  it - iteration number
1967: .  rnorm - (estimated) 2-norm of (preconditioned) residual
1968: .  reason - the reason why it has converged or diverged
1969: -  cctx  - optional convergence context, as set by KSPSetConvergenceTest()


1972:    Notes:
1973:    Must be called after the KSP type has been set so put this after
1974:    a call to KSPSetType(), or KSPSetFromOptions().

1976:    The default convergence test, KSPConvergedDefault(), aborts if the
1977:    residual grows to more than 10000 times the initial residual.

1979:    The default is a combination of relative and absolute tolerances.
1980:    The residual value that is tested may be an approximation; routines
1981:    that need exact values should compute them.

1983:    In the default PETSc convergence test, the precise values of reason
1984:    are macros such as KSP_CONVERGED_RTOL, which are defined in petscksp.h.

1986:    Level: advanced

1988: .seealso: KSPConvergedDefault(), KSPGetConvergenceContext(), KSPSetTolerances(), KSP, KSPGetConvergenceTest(), KSPGetAndClearConvergenceTest()
1989: @*/
1990: PetscErrorCode  KSPSetConvergenceTest(KSP ksp,PetscErrorCode (*converge)(KSP,PetscInt,PetscReal,KSPConvergedReason*,void*),void *cctx,PetscErrorCode (*destroy)(void*))
1991: {

1996:   if (ksp->convergeddestroy) {
1997:     (*ksp->convergeddestroy)(ksp->cnvP);
1998:   }
1999:   ksp->converged        = converge;
2000:   ksp->convergeddestroy = destroy;
2001:   ksp->cnvP             = (void*)cctx;
2002:   return(0);
2003: }

2005: /*@C
2006:    KSPGetConvergenceTest - Gets the function to be used to determine
2007:    convergence.

2009:    Logically Collective on ksp

2011:    Input Parameter:
2012: .   ksp - iterative context obtained from KSPCreate()

2014:    Output Parameter:
2015: +  converge - pointer to convergence test function
2016: .  cctx    - context for private data for the convergence routine (may be null)
2017: -  destroy - a routine for destroying the context (may be null)

2019:    Calling sequence of converge:
2020: $     converge (KSP ksp, PetscInt it, PetscReal rnorm, KSPConvergedReason *reason,void *mctx)

2022: +  ksp - iterative context obtained from KSPCreate()
2023: .  it - iteration number
2024: .  rnorm - (estimated) 2-norm of (preconditioned) residual
2025: .  reason - the reason why it has converged or diverged
2026: -  cctx  - optional convergence context, as set by KSPSetConvergenceTest()

2028:    Level: advanced

2030: .seealso: KSPConvergedDefault(), KSPGetConvergenceContext(), KSPSetTolerances(), KSP, KSPSetConvergenceTest(), KSPGetAndClearConvergenceTest()
2031: @*/
2032: PetscErrorCode  KSPGetConvergenceTest(KSP ksp,PetscErrorCode (**converge)(KSP,PetscInt,PetscReal,KSPConvergedReason*,void*),void **cctx,PetscErrorCode (**destroy)(void*))
2033: {
2036:   if (converge) *converge = ksp->converged;
2037:   if (destroy)  *destroy  = ksp->convergeddestroy;
2038:   if (cctx)     *cctx     = ksp->cnvP;
2039:   return(0);
2040: }

2042: /*@C
2043:    KSPGetAndClearConvergenceTest - Gets the function to be used to determine convergence. Removes the current test without calling destroy on the test context

2045:    Logically Collective on ksp

2047:    Input Parameter:
2048: .   ksp - iterative context obtained from KSPCreate()

2050:    Output Parameter:
2051: +  converge - pointer to convergence test function
2052: .  cctx    - context for private data for the convergence routine
2053: -  destroy - a routine for destroying the context

2055:    Calling sequence of converge:
2056: $     converge (KSP ksp, PetscInt it, PetscReal rnorm, KSPConvergedReason *reason,void *mctx)

2058: +  ksp - iterative context obtained from KSPCreate()
2059: .  it - iteration number
2060: .  rnorm - (estimated) 2-norm of (preconditioned) residual
2061: .  reason - the reason why it has converged or diverged
2062: -  cctx  - optional convergence context, as set by KSPSetConvergenceTest()

2064:    Level: advanced

2066:    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
2067:           KSPSetConvergenceTest() on this original KSP. If you just called KSPGetConvergenceTest() followed by KSPSetConvergenceTest() the original context information
2068:           would be destroyed and hence the transferred context would be invalid and trigger a crash on use

2070: .seealso: KSPConvergedDefault(), KSPGetConvergenceContext(), KSPSetTolerances(), KSP, KSPSetConvergenceTest(), KSPGetConvergenceTest()
2071: @*/
2072: PetscErrorCode  KSPGetAndClearConvergenceTest(KSP ksp,PetscErrorCode (**converge)(KSP,PetscInt,PetscReal,KSPConvergedReason*,void*),void **cctx,PetscErrorCode (**destroy)(void*))
2073: {
2076:   *converge             = ksp->converged;
2077:   *destroy              = ksp->convergeddestroy;
2078:   *cctx                 = ksp->cnvP;
2079:   ksp->converged        = NULL;
2080:   ksp->cnvP             = NULL;
2081:   ksp->convergeddestroy = NULL;
2082:   return(0);
2083: }

2085: /*@C
2086:    KSPGetConvergenceContext - Gets the convergence context set with
2087:    KSPSetConvergenceTest().

2089:    Not Collective

2091:    Input Parameter:
2092: .  ksp - iterative context obtained from KSPCreate()

2094:    Output Parameter:
2095: .  ctx - monitoring context

2097:    Level: advanced

2099: .seealso: KSPConvergedDefault(), KSPSetConvergenceTest(), KSP
2100: @*/
2101: PetscErrorCode  KSPGetConvergenceContext(KSP ksp,void **ctx)
2102: {
2105:   *ctx = ksp->cnvP;
2106:   return(0);
2107: }

2109: /*@C
2110:    KSPBuildSolution - Builds the approximate solution in a vector provided.
2111:    This routine is NOT commonly needed (see KSPSolve()).

2113:    Collective on ksp

2115:    Input Parameter:
2116: .  ctx - iterative context obtained from KSPCreate()

2118:    Output Parameter:
2119:    Provide exactly one of
2120: +  v - location to stash solution.
2121: -  V - the solution is returned in this location. This vector is created
2122:        internally. This vector should NOT be destroyed by the user with
2123:        VecDestroy().

2125:    Notes:
2126:    This routine can be used in one of two ways
2127: .vb
2128:       KSPBuildSolution(ksp,NULL,&V);
2129:    or
2130:       KSPBuildSolution(ksp,v,NULL); or KSPBuildSolution(ksp,v,&v);
2131: .ve
2132:    In the first case an internal vector is allocated to store the solution
2133:    (the user cannot destroy this vector). In the second case the solution
2134:    is generated in the vector that the user provides. Note that for certain
2135:    methods, such as KSPCG, the second case requires a copy of the solution,
2136:    while in the first case the call is essentially free since it simply
2137:    returns the vector where the solution already is stored. For some methods
2138:    like GMRES this is a reasonably expensive operation and should only be
2139:    used in truly needed.

2141:    Level: advanced

2143: .seealso: KSPGetSolution(), KSPBuildResidual(), KSP
2144: @*/
2145: PetscErrorCode  KSPBuildSolution(KSP ksp,Vec v,Vec *V)
2146: {

2151:   if (!V && !v) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_WRONG,"Must provide either v or V");
2152:   if (!V) V = &v;
2153:   (*ksp->ops->buildsolution)(ksp,v,V);
2154:   return(0);
2155: }

2157: /*@C
2158:    KSPBuildResidual - Builds the residual in a vector provided.

2160:    Collective on ksp

2162:    Input Parameter:
2163: .  ksp - iterative context obtained from KSPCreate()

2165:    Output Parameters:
2166: +  v - optional location to stash residual.  If v is not provided,
2167:        then a location is generated.
2168: .  t - work vector.  If not provided then one is generated.
2169: -  V - the residual

2171:    Notes:
2172:    Regardless of whether or not v is provided, the residual is
2173:    returned in V.

2175:    Level: advanced

2177: .seealso: KSPBuildSolution()
2178: @*/
2179: PetscErrorCode  KSPBuildResidual(KSP ksp,Vec t,Vec v,Vec *V)
2180: {
2182:   PetscBool      flag = PETSC_FALSE;
2183:   Vec            w    = v,tt = t;

2187:   if (!w) {
2188:     VecDuplicate(ksp->vec_rhs,&w);
2189:     PetscLogObjectParent((PetscObject)ksp,(PetscObject)w);
2190:   }
2191:   if (!tt) {
2192:     VecDuplicate(ksp->vec_sol,&tt); flag = PETSC_TRUE;
2193:     PetscLogObjectParent((PetscObject)ksp,(PetscObject)tt);
2194:   }
2195:   (*ksp->ops->buildresidual)(ksp,tt,w,V);
2196:   if (flag) {VecDestroy(&tt);}
2197:   return(0);
2198: }

2200: /*@
2201:    KSPSetDiagonalScale - Tells KSP to symmetrically diagonally scale the system
2202:      before solving. This actually CHANGES the matrix (and right hand side).

2204:    Logically Collective on ksp

2206:    Input Parameter:
2207: +  ksp - the KSP context
2208: -  scale - PETSC_TRUE or PETSC_FALSE

2210:    Options Database Key:
2211: +   -ksp_diagonal_scale -
2212: -   -ksp_diagonal_scale_fix - scale the matrix back AFTER the solve


2215:     Notes:
2216:     Scales the matrix by  D^(-1/2)  A  D^(-1/2)  [D^(1/2) x ] = D^(-1/2) b
2217:        where D_{ii} is 1/abs(A_{ii}) unless A_{ii} is zero and then it is 1.

2219:     BE CAREFUL with this routine: it actually scales the matrix and right
2220:     hand side that define the system. After the system is solved the matrix
2221:     and right hand side remain scaled unless you use KSPSetDiagonalScaleFix()

2223:     This should NOT be used within the SNES solves if you are using a line
2224:     search.

2226:     If you use this with the PCType Eisenstat preconditioner than you can
2227:     use the PCEisenstatSetNoDiagonalScaling() option, or -pc_eisenstat_no_diagonal_scaling
2228:     to save some unneeded, redundant flops.

2230:    Level: intermediate

2232: .seealso: KSPGetDiagonalScale(), KSPSetDiagonalScaleFix(), KSP
2233: @*/
2234: PetscErrorCode  KSPSetDiagonalScale(KSP ksp,PetscBool scale)
2235: {
2239:   ksp->dscale = scale;
2240:   return(0);
2241: }

2243: /*@
2244:    KSPGetDiagonalScale - Checks if KSP solver scales the matrix and
2245:                           right hand side

2247:    Not Collective

2249:    Input Parameter:
2250: .  ksp - the KSP context

2252:    Output Parameter:
2253: .  scale - PETSC_TRUE or PETSC_FALSE

2255:    Notes:
2256:     BE CAREFUL with this routine: it actually scales the matrix and right
2257:     hand side that define the system. After the system is solved the matrix
2258:     and right hand side remain scaled  unless you use KSPSetDiagonalScaleFix()

2260:    Level: intermediate

2262: .seealso: KSPSetDiagonalScale(), KSPSetDiagonalScaleFix(), KSP
2263: @*/
2264: PetscErrorCode  KSPGetDiagonalScale(KSP ksp,PetscBool  *scale)
2265: {
2269:   *scale = ksp->dscale;
2270:   return(0);
2271: }

2273: /*@
2274:    KSPSetDiagonalScaleFix - Tells KSP to diagonally scale the system
2275:      back after solving.

2277:    Logically Collective on ksp

2279:    Input Parameter:
2280: +  ksp - the KSP context
2281: -  fix - PETSC_TRUE to scale back after the system solve, PETSC_FALSE to not
2282:          rescale (default)

2284:    Notes:
2285:      Must be called after KSPSetDiagonalScale()

2287:      Using this will slow things down, because it rescales the matrix before and
2288:      after each linear solve. This is intended mainly for testing to allow one
2289:      to easily get back the original system to make sure the solution computed is
2290:      accurate enough.

2292:    Level: intermediate

2294: .seealso: KSPGetDiagonalScale(), KSPSetDiagonalScale(), KSPGetDiagonalScaleFix(), KSP
2295: @*/
2296: PetscErrorCode  KSPSetDiagonalScaleFix(KSP ksp,PetscBool fix)
2297: {
2301:   ksp->dscalefix = fix;
2302:   return(0);
2303: }

2305: /*@
2306:    KSPGetDiagonalScaleFix - Determines if KSP diagonally scales the system
2307:      back after solving.

2309:    Not Collective

2311:    Input Parameter:
2312: .  ksp - the KSP context

2314:    Output Parameter:
2315: .  fix - PETSC_TRUE to scale back after the system solve, PETSC_FALSE to not
2316:          rescale (default)

2318:    Notes:
2319:      Must be called after KSPSetDiagonalScale()

2321:      If PETSC_TRUE will slow things down, because it rescales the matrix before and
2322:      after each linear solve. This is intended mainly for testing to allow one
2323:      to easily get back the original system to make sure the solution computed is
2324:      accurate enough.

2326:    Level: intermediate

2328: .seealso: KSPGetDiagonalScale(), KSPSetDiagonalScale(), KSPSetDiagonalScaleFix(), KSP
2329: @*/
2330: PetscErrorCode  KSPGetDiagonalScaleFix(KSP ksp,PetscBool  *fix)
2331: {
2335:   *fix = ksp->dscalefix;
2336:   return(0);
2337: }

2339: /*@C
2340:    KSPSetComputeOperators - set routine to compute the linear operators

2342:    Logically Collective

2344:    Input Arguments:
2345: +  ksp - the KSP context
2346: .  func - function to compute the operators
2347: -  ctx - optional context

2349:    Calling sequence of func:
2350: $  func(KSP ksp,Mat A,Mat B,void *ctx)

2352: +  ksp - the KSP context
2353: .  A - the linear operator
2354: .  B - preconditioning matrix
2355: -  ctx - optional user-provided context

2357:    Notes:
2358:     The user provided func() will be called automatically at the very next call to KSPSolve(). It will not be called at future KSPSolve() calls
2359:           unless either KSPSetComputeOperators() or KSPSetOperators() is called before that KSPSolve() is called.

2361:           To reuse the same preconditioner for the next KSPSolve() and not compute a new one based on the most recently computed matrix call KSPSetReusePreconditioner()

2363:    Level: beginner

2365: .seealso: KSPSetOperators(), KSPSetComputeRHS(), DMKSPSetComputeOperators(), KSPSetComputeInitialGuess()
2366: @*/
2367: PetscErrorCode KSPSetComputeOperators(KSP ksp,PetscErrorCode (*func)(KSP,Mat,Mat,void*),void *ctx)
2368: {
2370:   DM             dm;

2374:   KSPGetDM(ksp,&dm);
2375:   DMKSPSetComputeOperators(dm,func,ctx);
2376:   if (ksp->setupstage == KSP_SETUP_NEWRHS) ksp->setupstage = KSP_SETUP_NEWMATRIX;
2377:   return(0);
2378: }

2380: /*@C
2381:    KSPSetComputeRHS - set routine to compute the right hand side of the linear system

2383:    Logically Collective

2385:    Input Arguments:
2386: +  ksp - the KSP context
2387: .  func - function to compute the right hand side
2388: -  ctx - optional context

2390:    Calling sequence of func:
2391: $  func(KSP ksp,Vec b,void *ctx)

2393: +  ksp - the KSP context
2394: .  b - right hand side of linear system
2395: -  ctx - optional user-provided context

2397:    Notes:
2398:     The routine you provide will be called EACH you call KSPSolve() to prepare the new right hand side for that solve

2400:    Level: beginner

2402: .seealso: KSPSolve(), DMKSPSetComputeRHS(), KSPSetComputeOperators()
2403: @*/
2404: PetscErrorCode KSPSetComputeRHS(KSP ksp,PetscErrorCode (*func)(KSP,Vec,void*),void *ctx)
2405: {
2407:   DM             dm;

2411:   KSPGetDM(ksp,&dm);
2412:   DMKSPSetComputeRHS(dm,func,ctx);
2413:   return(0);
2414: }

2416: /*@C
2417:    KSPSetComputeInitialGuess - set routine to compute the initial guess of the linear system

2419:    Logically Collective

2421:    Input Arguments:
2422: +  ksp - the KSP context
2423: .  func - function to compute the initial guess
2424: -  ctx - optional context

2426:    Calling sequence of func:
2427: $  func(KSP ksp,Vec x,void *ctx)

2429: +  ksp - the KSP context
2430: .  x - solution vector
2431: -  ctx - optional user-provided context

2433:    Notes: This should only be used in conjunction with KSPSetComputeRHS(), KSPSetComputeOperators(), otherwise
2434:    call KSPSetInitialGuessNonzero() and set the initial guess values in the solution vector passed to KSPSolve().

2436:    Level: beginner

2438: .seealso: KSPSolve(), KSPSetComputeRHS(), KSPSetComputeOperators(), DMKSPSetComputeInitialGuess()
2439: @*/
2440: PetscErrorCode KSPSetComputeInitialGuess(KSP ksp,PetscErrorCode (*func)(KSP,Vec,void*),void *ctx)
2441: {
2443:   DM             dm;

2447:   KSPGetDM(ksp,&dm);
2448:   DMKSPSetComputeInitialGuess(dm,func,ctx);
2449:   return(0);
2450: }