Date: 2021-03-03T22:27:20+00:00

Actual source code: itfunc.c
petsc-3.14.5 2021-03-03
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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: }