Actual source code: itfunc.c
petsc-3.10.5 2019-03-28
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      2: /*
      3:       Interface KSP routines that the user calls.
      4: */

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

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

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

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

     23:    Not Collective

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

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

     31:    Options Database Keys:
     32: .  -ksp_compute_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_compute_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: .keywords: compute, extreme, singular, values

     53: .seealso: KSPSetComputeSingularValues(), KSPMonitorSingularValue(), KSPComputeEigenvalues(), KSP
     54: @*/
     55: PetscErrorCode  KSPComputeExtremeSingularValues(KSP ksp,PetscReal *emax,PetscReal *emin)
     56: {

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

     65:   if (ksp->ops->computeextremesingularvalues) {
     66:     (*ksp->ops->computeextremesingularvalues)(ksp,emax,emin);
     67:   } else {
     68:     *emin = -1.0;
     69:     *emax = -1.0;
     70:   }
     71:   return(0);
     72: }

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

     78:    Not Collective

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

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

     90:    Options Database Keys:
     91: +  -ksp_compute_eigenvalues - Prints eigenvalues to stdout
     92: -  -ksp_plot_eigenvalues - Plots eigenvalues in an x-window display

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

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

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

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

    113:    Level: advanced

    115: .keywords: compute, extreme, singular, values

    117: .seealso: KSPSetComputeSingularValues(), KSPMonitorSingularValue(), KSPComputeExtremeSingularValues(), KSP
    118: @*/
    119: PetscErrorCode  KSPComputeEigenvalues(KSP ksp,PetscInt n,PetscReal r[],PetscReal c[],PetscInt *neig)
    120: {

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

    131:   if (n && ksp->ops->computeeigenvalues) {
    132:     (*ksp->ops->computeeigenvalues)(ksp,n,r,c,neig);
    133:   } else {
    134:     *neig = 0;
    135:   }
    136:   return(0);
    137: }

    139: /*@
    140:    KSPComputeRitz - Computes the Ritz or harmonic Ritz pairs associated to the
    141:    smallest or largest in modulus, for the preconditioned operator.
    142:    Called after KSPSolve().

    144:    Not Collective

    146:    Input Parameter:
    147: +  ksp   - iterative context obtained from KSPCreate()
    148: .  ritz  - PETSC_TRUE or PETSC_FALSE for ritz pairs or harmonic Ritz pairs, respectively
    149: .  small - PETSC_TRUE or PETSC_FALSE for smallest or largest (harmonic) Ritz values, respectively
    150: .  nrit  - number of (harmonic) Ritz pairs to compute

    152:    Output Parameters:
    153: +  nrit  - actual number of computed (harmonic) Ritz pairs
    154: .  S     - multidimensional vector with Ritz vectors
    155: .  tetar - real part of the Ritz values
    156: .  tetai - imaginary part of the Ritz values

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

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

    173:    Level: advanced

    175: .keywords: compute, ritz, values

    177: .seealso: KSPSetComputeRitz(), KSP
    178: @*/
    179: PetscErrorCode  KSPComputeRitz(KSP ksp,PetscBool ritz,PetscBool small,PetscInt *nrit,Vec S[],PetscReal tetar[],PetscReal tetai[])
    180: {

    185:   if (!ksp->calc_ritz) SETERRQ(PetscObjectComm((PetscObject)ksp),4,"Ritz pairs not requested before KSPSetUp()");
    186:   if (ksp->ops->computeritz) {(*ksp->ops->computeritz)(ksp,ritz,small,nrit,S,tetar,tetai);}
    187:   return(0);
    188: }
    189: /*@
    190:    KSPSetUpOnBlocks - Sets up the preconditioner for each block in
    191:    the block Jacobi, block Gauss-Seidel, and overlapping Schwarz
    192:    methods.

    194:    Collective on KSP

    196:    Input Parameter:
    197: .  ksp - the KSP context

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

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

    208:    Level: advanced

    210: .keywords: setup, blocks

    212: .seealso: PCSetUpOnBlocks(), KSPSetUp(), PCSetUp(), KSP
    213: @*/
    214: PetscErrorCode  KSPSetUpOnBlocks(KSP ksp)
    215: {
    216:   PC             pc;
    218:   PCFailedReason pcreason;

    222:   KSPGetPC(ksp,&pc);
    223:   PCSetUpOnBlocks(pc);
    224:   PCGetSetUpFailedReason(pc,&pcreason);
    225:   if (pcreason) {
    226:     ksp->reason = KSP_DIVERGED_PCSETUP_FAILED;
    227:   }
    228:   return(0);
    229: }

    231: /*@
    232:    KSPSetReusePreconditioner - reuse the current preconditioner, do not construct a new one even if the operator changes

    234:    Collective on KSP

    236:    Input Parameters:
    237: +  ksp   - iterative context obtained from KSPCreate()
    238: -  flag - PETSC_TRUE to reuse the current preconditioner

    240:    Level: intermediate

    242: .keywords: setup

    244: .seealso: KSPCreate(), KSPSolve(), KSPDestroy(), PCSetReusePreconditioner(), KSP
    245: @*/
    246: PetscErrorCode  KSPSetReusePreconditioner(KSP ksp,PetscBool flag)
    247: {
    248:   PC             pc;

    253:   KSPGetPC(ksp,&pc);
    254:   PCSetReusePreconditioner(pc,flag);
    255:   return(0);
    256: }

    258: /*@
    259:    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

    261:    Collective on KSP

    263:    Input Parameters:
    264: +  ksp   - iterative context obtained from KSPCreate()
    265: -  flag - PETSC_TRUE to skip calling the PCSetFromOptions()

    267:    Level: intermediate

    269: .keywords: setup

    271: .seealso: KSPCreate(), KSPSolve(), KSPDestroy(), PCSetReusePreconditioner(), KSP
    272: @*/
    273: PetscErrorCode  KSPSetSkipPCSetFromOptions(KSP ksp,PetscBool flag)
    274: {
    277:   ksp->skippcsetfromoptions = flag;
    278:   return(0);
    279: }

    281: /*@
    282:    KSPSetUp - Sets up the internal data structures for the
    283:    later use of an iterative solver.

    285:    Collective on KSP

    287:    Input Parameter:
    288: .  ksp   - iterative context obtained from KSPCreate()

    290:    Level: developer

    292: .keywords: setup

    294: .seealso: KSPCreate(), KSPSolve(), KSPDestroy(), KSP
    295: @*/
    296: PetscErrorCode KSPSetUp(KSP ksp)
    297: {
    299:   Mat            A,B;
    300:   Mat            mat,pmat;
    301:   MatNullSpace   nullsp;
    302:   PCFailedReason pcreason;
    303:

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

    310:   if (!((PetscObject)ksp)->type_name) {
    311:     KSPSetType(ksp,KSPGMRES);
    312:   }
    313:   KSPSetUpNorms_Private(ksp,PETSC_TRUE,&ksp->normtype,&ksp->pc_side);

    315:   if (ksp->dmActive && !ksp->setupstage) {
    316:     /* first time in so build matrix and vector data structures using DM */
    317:     if (!ksp->vec_rhs) {DMCreateGlobalVector(ksp->dm,&ksp->vec_rhs);}
    318:     if (!ksp->vec_sol) {DMCreateGlobalVector(ksp->dm,&ksp->vec_sol);}
    319:     DMCreateMatrix(ksp->dm,&A);
    320:     KSPSetOperators(ksp,A,A);
    321:     PetscObjectDereference((PetscObject)A);
    322:   }

    324:   if (ksp->dmActive) {
    325:     DMKSP kdm;
    326:     DMGetDMKSP(ksp->dm,&kdm);

    328:     if (kdm->ops->computeinitialguess && ksp->setupstage != KSP_SETUP_NEWRHS) {
    329:       /* only computes initial guess the first time through */
    330:       (*kdm->ops->computeinitialguess)(ksp,ksp->vec_sol,kdm->initialguessctx);
    331:       KSPSetInitialGuessNonzero(ksp,PETSC_TRUE);
    332:     }
    333:     if (kdm->ops->computerhs) {
    334:       (*kdm->ops->computerhs)(ksp,ksp->vec_rhs,kdm->rhsctx);
    335:     }

    337:     if (ksp->setupstage != KSP_SETUP_NEWRHS) {
    338:       if (kdm->ops->computeoperators) {
    339:         KSPGetOperators(ksp,&A,&B);
    340:         (*kdm->ops->computeoperators)(ksp,A,B,kdm->operatorsctx);
    341:       } else SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_WRONGSTATE,"You called KSPSetDM() but did not use DMKSPSetComputeOperators() or KSPSetDMActive(ksp,PETSC_FALSE);");
    342:     }
    343:   }

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

    348:   switch (ksp->setupstage) {
    349:   case KSP_SETUP_NEW:
    350:     (*ksp->ops->setup)(ksp);
    351:     break;
    352:   case KSP_SETUP_NEWMATRIX: {   /* This should be replaced with a more general mechanism */
    353:     if (ksp->setupnewmatrix) {
    354:       (*ksp->ops->setup)(ksp);
    355:     }
    356:   } break;
    357:   default: break;
    358:   }

    360:   if (!ksp->pc) {KSPGetPC(ksp,&ksp->pc);}
    361:   PCGetOperators(ksp->pc,&mat,&pmat);
    362:   /* scale the matrix if requested */
    363:   if (ksp->dscale) {
    364:     PetscScalar *xx;
    365:     PetscInt    i,n;
    366:     PetscBool   zeroflag = PETSC_FALSE;
    367:     if (!ksp->pc) {KSPGetPC(ksp,&ksp->pc);}
    368:     if (!ksp->diagonal) { /* allocate vector to hold diagonal */
    369:       MatCreateVecs(pmat,&ksp->diagonal,0);
    370:     }
    371:     MatGetDiagonal(pmat,ksp->diagonal);
    372:     VecGetLocalSize(ksp->diagonal,&n);
    373:     VecGetArray(ksp->diagonal,&xx);
    374:     for (i=0; i<n; i++) {
    375:       if (xx[i] != 0.0) xx[i] = 1.0/PetscSqrtReal(PetscAbsScalar(xx[i]));
    376:       else {
    377:         xx[i]    = 1.0;
    378:         zeroflag = PETSC_TRUE;
    379:       }
    380:     }
    381:     VecRestoreArray(ksp->diagonal,&xx);
    382:     if (zeroflag) {
    383:       PetscInfo(ksp,"Zero detected in diagonal of matrix, using 1 at those locations\n");
    384:     }
    385:     MatDiagonalScale(pmat,ksp->diagonal,ksp->diagonal);
    386:     if (mat != pmat) {MatDiagonalScale(mat,ksp->diagonal,ksp->diagonal);}
    387:     ksp->dscalefix2 = PETSC_FALSE;
    388:   }
    389:   PetscLogEventEnd(KSP_SetUp,ksp,ksp->vec_rhs,ksp->vec_sol,0);
    390:   PCSetErrorIfFailure(ksp->pc,ksp->errorifnotconverged);
    391:   PCSetUp(ksp->pc);
    392:   PCGetSetUpFailedReason(ksp->pc,&pcreason);
    393:   if (pcreason) {
    394:     ksp->reason = KSP_DIVERGED_PCSETUP_FAILED;
    395:   }

    397:   MatGetNullSpace(mat,&nullsp);
    398:   if (nullsp) {
    399:     PetscBool test = PETSC_FALSE;
    400:     PetscOptionsGetBool(((PetscObject)ksp)->options,((PetscObject)ksp)->prefix,"-ksp_test_null_space",&test,NULL);
    401:     if (test) {
    402:       MatNullSpaceTest(nullsp,mat,NULL);
    403:     }
    404:   }
    405:   ksp->setupstage = KSP_SETUP_NEWRHS;
    406:   return(0);
    407: }

    409: static PetscErrorCode KSPReasonView_Internal(KSP ksp, PetscViewer viewer, PetscViewerFormat format)
    410: {
    412:   PetscBool      isAscii;

    415:   if (format != PETSC_VIEWER_DEFAULT) {PetscViewerPushFormat(viewer,format);}
    416:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isAscii);
    417:   if (isAscii) {
    418:     PetscViewerASCIIAddTab(viewer,((PetscObject)ksp)->tablevel);
    419:     if (ksp->reason > 0) {
    420:       if (((PetscObject) ksp)->prefix) {
    421:         PetscViewerASCIIPrintf(viewer,"Linear %s solve converged due to %s iterations %D\n",((PetscObject) ksp)->prefix,KSPConvergedReasons[ksp->reason],ksp->its);
    422:       } else {
    423:         PetscViewerASCIIPrintf(viewer,"Linear solve converged due to %s iterations %D\n",KSPConvergedReasons[ksp->reason],ksp->its);
    424:       }
    425:     } else {
    426:       if (((PetscObject) ksp)->prefix) {
    427:         PetscViewerASCIIPrintf(viewer,"Linear %s solve did not converge due to %s iterations %D\n",((PetscObject) ksp)->prefix,KSPConvergedReasons[ksp->reason],ksp->its);
    428:       } else {
    429:         PetscViewerASCIIPrintf(viewer,"Linear solve did not converge due to %s iterations %D\n",KSPConvergedReasons[ksp->reason],ksp->its);
    430:       }
    431:       if (ksp->reason == KSP_DIVERGED_PCSETUP_FAILED) {
    432:         PCFailedReason reason;
    433:         PCGetSetUpFailedReason(ksp->pc,&reason);
    434:         PetscViewerASCIIPrintf(viewer,"               PCSETUP_FAILED due to %s \n",PCFailedReasons[reason]);
    435:       }
    436:     }
    437:     PetscViewerASCIISubtractTab(viewer,((PetscObject)ksp)->tablevel);
    438:   }
    439:   if (format != PETSC_VIEWER_DEFAULT) {PetscViewerPopFormat(viewer);}
    440:   return(0);
    441: }

    443: /*@
    444:    KSPReasonView - Displays the reason a KSP solve converged or diverged to a viewer

    446:    Collective on KSP

    448:    Parameter:
    449: +  ksp - iterative context obtained from KSPCreate()
    450: -  viewer - the viewer to display the reason

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

    456:    Level: beginner

    458: .keywords: solve, linear system

    460: .seealso: KSPCreate(), KSPSetUp(), KSPDestroy(), KSPSetTolerances(), KSPConvergedDefault(),
    461:           KSPSolveTranspose(), KSPGetIterationNumber(), KSP
    462: @*/
    463: PetscErrorCode KSPReasonView(KSP ksp,PetscViewer viewer)
    464: {

    468:   KSPReasonView_Internal(ksp, viewer, PETSC_VIEWER_DEFAULT);
    469:   return(0);
    470: }

    472: #if defined(PETSC_HAVE_THREADSAFETY)
    473: #define KSPReasonViewFromOptions KSPReasonViewFromOptionsUnsafe
    474: #else
    475: #endif
    476: /*@C
    477:   KSPReasonViewFromOptions - Processes command line options to determine if/how a KSPReason is to be viewed.

    479:   Collective on KSP

    481:   Input Parameters:
    482: . ksp   - the KSP object

    484:   Level: intermediate

    486: @*/
    487: PetscErrorCode KSPReasonViewFromOptions(KSP ksp)
    488: {
    489:   PetscViewer       viewer;
    490:   PetscBool         flg;
    491:   PetscViewerFormat format;
    492:   PetscErrorCode    ierr;

    495:   PetscOptionsGetViewer(PetscObjectComm((PetscObject)ksp),((PetscObject)ksp)->prefix,"-ksp_converged_reason",&viewer,&format,&flg);
    496:   if (flg) {
    497:     KSPReasonView_Internal(ksp, viewer, format);
    498:     PetscViewerDestroy(&viewer);
    499:   }
    500:   return(0);
    501: }

    503:  #include <petscdraw.h>

    505: static PetscErrorCode KSPViewEigenvalues_Internal(KSP ksp, PetscBool isExplicit, PetscViewer viewer, PetscViewerFormat format)
    506: {
    507:   PetscReal     *r, *c;
    508:   PetscInt       n, i, neig;
    509:   PetscBool      isascii, isdraw;
    510:   PetscMPIInt    rank;

    514:   MPI_Comm_rank(PetscObjectComm((PetscObject) ksp), &rank);
    515:   PetscObjectTypeCompare((PetscObject) viewer, PETSCVIEWERASCII, &isascii);
    516:   PetscObjectTypeCompare((PetscObject) viewer, PETSCVIEWERDRAW,  &isdraw);
    517:   if (isExplicit) {
    518:     VecGetSize(ksp->vec_sol,&n);
    519:     PetscMalloc2(n, &r, n, &c);
    520:     KSPComputeEigenvaluesExplicitly(ksp, n, r, c);
    521:     neig = n;
    522:   } else {
    523:     PetscInt nits;

    525:     KSPGetIterationNumber(ksp, &nits);
    526:     n    = nits+2;
    527:     if (!nits) {PetscViewerASCIIPrintf(viewer, "Zero iterations in solver, cannot approximate any eigenvalues\n");return(0);}
    528:     PetscMalloc2(n, &r, n, &c);
    529:     KSPComputeEigenvalues(ksp, n, r, c, &neig);
    530:   }
    531:   if (isascii) {
    532:     PetscViewerASCIIPrintf(viewer, "%s computed eigenvalues\n", isExplicit ? "Explicitly" : "Iteratively");
    533:     for (i = 0; i < neig; ++i) {
    534:       if (c[i] >= 0.0) {PetscViewerASCIIPrintf(viewer, "%g + %gi\n", (double) r[i],  (double) c[i]);}
    535:       else             {PetscViewerASCIIPrintf(viewer, "%g - %gi\n", (double) r[i], -(double) c[i]);}
    536:     }
    537:   } else if (isdraw && !rank) {
    538:     PetscDraw   draw;
    539:     PetscDrawSP drawsp;

    541:     if (format == PETSC_VIEWER_DRAW_CONTOUR) {
    542:       KSPPlotEigenContours_Private(ksp,neig,r,c);
    543:     } else {
    544:       if (!ksp->eigviewer) {PetscViewerDrawOpen(PETSC_COMM_SELF,0,isExplicit ? "Explicitly Computed Eigenvalues" : "Iteratively Computed Eigenvalues",PETSC_DECIDE,PETSC_DECIDE,400,400,&ksp->eigviewer);}
    545:       PetscViewerDrawGetDraw(ksp->eigviewer,0,&draw);
    546:       PetscDrawSPCreate(draw,1,&drawsp);
    547:       PetscDrawSPReset(drawsp);
    548:       for (i = 0; i < neig; ++i) {PetscDrawSPAddPoint(drawsp,r+i,c+i);}
    549:       PetscDrawSPDraw(drawsp,PETSC_TRUE);
    550:       PetscDrawSPSave(drawsp);
    551:       PetscDrawSPDestroy(&drawsp);
    552:     }
    553:   }
    554:   PetscFree2(r, c);
    555:   return(0);
    556: }

    558: static PetscErrorCode KSPViewSingularvalues_Internal(KSP ksp, PetscViewer viewer, PetscViewerFormat format)
    559: {
    560:   PetscReal      smax, smin;
    561:   PetscInt       nits;
    562:   PetscBool      isascii;

    566:   PetscObjectTypeCompare((PetscObject) viewer, PETSCVIEWERASCII, &isascii);
    567:   KSPGetIterationNumber(ksp, &nits);
    568:   if (!nits) {PetscViewerASCIIPrintf(viewer, "Zero iterations in solver, cannot approximate any singular values\n");return(0);}
    569:   KSPComputeExtremeSingularValues(ksp, &smax, &smin);
    570:   if (isascii) {PetscViewerASCIIPrintf(viewer, "Iteratively computed extreme singular values: max %g min %g max/min %g\n",(double)smax,(double)smin,(double)(smax/smin));}
    571:   return(0);
    572: }

    574: static PetscErrorCode KSPViewFinalResidual_Internal(KSP ksp, PetscViewer viewer, PetscViewerFormat format)
    575: {
    576:   PetscBool      isascii;

    580:   PetscObjectTypeCompare((PetscObject) viewer, PETSCVIEWERASCII, &isascii);
    581:   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");
    582:   if (isascii) {
    583:     Mat       A;
    584:     Vec       t;
    585:     PetscReal norm;

    587:     PCGetOperators(ksp->pc, &A, NULL);
    588:     VecDuplicate(ksp->vec_rhs, &t);
    589:     KSP_MatMult(ksp, A, ksp->vec_sol, t);
    590:     VecAYPX(t, -1.0, ksp->vec_rhs);
    591:     VecNorm(t, NORM_2, &norm);
    592:     VecDestroy(&t);
    593:     PetscViewerASCIIPrintf(viewer, "KSP final norm of residual %g\n", (double) norm);
    594:   }
    595:   return(0);
    596: }

    598: /*@
    599:    KSPSolve - Solves linear system.

    601:    Collective on KSP

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

    608:    Options Database Keys:
    609: +  -ksp_compute_eigenvalues - compute preconditioned operators eigenvalues
    610: .  -ksp_plot_eigenvalues - plot the computed eigenvalues in an X-window
    611: .  -ksp_plot_eigencontours - plot the computed eigenvalues in an X-window with contours
    612: .  -ksp_compute_eigenvalues_explicitly - compute the eigenvalues by forming the dense operator and using LAPACK
    613: .  -ksp_plot_eigenvalues_explicitly - plot the explicitly computing eigenvalues
    614: .  -ksp_view_mat binary - save matrix to the default binary viewer
    615: .  -ksp_view_pmat binary - save matrix used to build preconditioner to the default binary viewer
    616: .  -ksp_view_rhs binary - save right hand side vector to the default binary viewer
    617: .  -ksp_view_solution binary - save computed solution vector to the default binary viewer
    618:            (can be read later with src/ksp/examples/tutorials/ex10.c for testing solvers)
    619: .  -ksp_view_mat_explicit - for matrix-free operators, computes the matrix entries and views them
    620: .  -ksp_view_preconditioned_operator_explicit - computes the product of the preconditioner and matrix as an explicit matrix and views it
    621: .  -ksp_converged_reason - print reason for converged or diverged, also prints number of iterations
    622: .  -ksp_final_residual - print 2-norm of true linear system residual at the end of the solution process
    623: -  -ksp_view - print the ksp data structure at the end of the system solution

    625:    Notes:

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

    629:    The operator is specified with KSPSetOperators().

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

    634:    If you provide a matrix that has a MatSetNullSpace() and MatSetTransposeNullSpace() this will use that information to solve singular systems
    635:    in the least squares sense with a norm minimizing solution.
    636: $
    637: $                   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()
    638: $
    639: $    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
    640: $    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
    641: $    direction thus the solution which is a linear combination of the search directions has no component in the nullspace(A).
    642: $
    643: $    We recommend always using GMRES for such singular systems.
    644: $    If nullspace(A) = nullspace(A') (note symmetric matrices always satisfy this property) then both left and right preconditioning will work
    645: $    If nullspace(A) != nullspace(A') then left preconditioning will work but right preconditioning may not work (or it may).

    647:    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
    648:        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
    649:        such as diagonal scaling we cannot apply the inverse of the preconditioner to a vector and thus cannot compute the nullspace(AB).

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

    657:    Understanding Convergence:
    658:    The routines KSPMonitorSet(), KSPComputeEigenvalues(), and
    659:    KSPComputeEigenvaluesExplicitly() provide information on additional
    660:    options to monitor convergence and print eigenvalue information.

    662:    Level: beginner

    664: .keywords: solve, linear system

    666: .seealso: KSPCreate(), KSPSetUp(), KSPDestroy(), KSPSetTolerances(), KSPConvergedDefault(),
    667:           KSPSolveTranspose(), KSPGetIterationNumber(), MatNullSpaceCreate(), MatSetNullSpace(), MatSetTransposeNullSpace(), KSP
    668: @*/
    669: PetscErrorCode KSPSolve(KSP ksp,Vec b,Vec x)
    670: {
    671:   PetscErrorCode    ierr;
    672:   PetscBool         flg = PETSC_FALSE,inXisinB=PETSC_FALSE,guess_zero;
    673:   Mat               mat,pmat;
    674:   MPI_Comm          comm;
    675:   MatNullSpace      nullsp;
    676:   Vec               btmp,vec_rhs=0;

    682:   comm = PetscObjectComm((PetscObject)ksp);
    683:   if (x && x == b) {
    684:     if (!ksp->guess_zero) SETERRQ(comm,PETSC_ERR_ARG_INCOMP,"Cannot use x == b with nonzero initial guess");
    685:     VecDuplicate(b,&x);
    686:     inXisinB = PETSC_TRUE;
    687:   }
    688:   if (b) {
    689:     PetscObjectReference((PetscObject)b);
    690:     VecDestroy(&ksp->vec_rhs);
    691:     ksp->vec_rhs = b;
    692:   }
    693:   if (x) {
    694:     PetscObjectReference((PetscObject)x);
    695:     VecDestroy(&ksp->vec_sol);
    696:     ksp->vec_sol = x;
    697:   }
    698:   if (ksp->viewPre) {ObjectView((PetscObject) ksp, ksp->viewerPre, ksp->formatPre);}

    700:   if (ksp->presolve) {(*ksp->presolve)(ksp,ksp->vec_rhs,ksp->vec_sol,ksp->prectx);}
    701:   PetscLogEventBegin(KSP_Solve,ksp,ksp->vec_rhs,ksp->vec_sol,0);

    703:   /* reset the residual history list if requested */
    704:   if (ksp->res_hist_reset) ksp->res_hist_len = 0;
    705:   ksp->transpose_solve = PETSC_FALSE;

    707:   if (ksp->guess) {
    708:     PetscObjectState ostate,state;

    710:     KSPGuessSetUp(ksp->guess);
    711:     PetscObjectStateGet((PetscObject)ksp->vec_sol,&ostate);
    712:     KSPGuessFormGuess(ksp->guess,ksp->vec_rhs,ksp->vec_sol);
    713:     PetscObjectStateGet((PetscObject)ksp->vec_sol,&state);
    714:     if (state != ostate) {
    715:       ksp->guess_zero = PETSC_FALSE;
    716:     } else {
    717:       PetscInfo(ksp,"Using zero initial guess since the KSPGuess object did not change the vector\n");
    718:       ksp->guess_zero = PETSC_TRUE;
    719:     }
    720:   }

    722:   /* KSPSetUp() scales the matrix if needed */
    723:   KSPSetUp(ksp);
    724:   KSPSetUpOnBlocks(ksp);

    726:   VecLocked(ksp->vec_sol,3);

    728:   PCGetOperators(ksp->pc,&mat,&pmat);
    729:   /* diagonal scale RHS if called for */
    730:   if (ksp->dscale) {
    731:     VecPointwiseMult(ksp->vec_rhs,ksp->vec_rhs,ksp->diagonal);
    732:     /* second time in, but matrix was scaled back to original */
    733:     if (ksp->dscalefix && ksp->dscalefix2) {
    734:       Mat mat,pmat;

    736:       PCGetOperators(ksp->pc,&mat,&pmat);
    737:       MatDiagonalScale(pmat,ksp->diagonal,ksp->diagonal);
    738:       if (mat != pmat) {MatDiagonalScale(mat,ksp->diagonal,ksp->diagonal);}
    739:     }

    741:     /* scale initial guess */
    742:     if (!ksp->guess_zero) {
    743:       if (!ksp->truediagonal) {
    744:         VecDuplicate(ksp->diagonal,&ksp->truediagonal);
    745:         VecCopy(ksp->diagonal,ksp->truediagonal);
    746:         VecReciprocal(ksp->truediagonal);
    747:       }
    748:       VecPointwiseMult(ksp->vec_sol,ksp->vec_sol,ksp->truediagonal);
    749:     }
    750:   }
    751:   PCPreSolve(ksp->pc,ksp);

    753:   if (ksp->guess_zero) { VecSet(ksp->vec_sol,0.0);}
    754:   if (ksp->guess_knoll) { /* The Knoll trick is independent on the KSPGuess specified */
    755:     PCApply(ksp->pc,ksp->vec_rhs,ksp->vec_sol);
    756:     KSP_RemoveNullSpace(ksp,ksp->vec_sol);
    757:     ksp->guess_zero = PETSC_FALSE;
    758:   }

    760:   /* can we mark the initial guess as zero for this solve? */
    761:   guess_zero = ksp->guess_zero;
    762:   if (!ksp->guess_zero) {
    763:     PetscReal norm;

    765:     VecNormAvailable(ksp->vec_sol,NORM_2,&flg,&norm);
    766:     if (flg && !norm) ksp->guess_zero = PETSC_TRUE;
    767:   }
    768:   MatGetTransposeNullSpace(pmat,&nullsp);
    769:   if (nullsp) {
    770:     VecDuplicate(ksp->vec_rhs,&btmp);
    771:     VecCopy(ksp->vec_rhs,btmp);
    772:     MatNullSpaceRemove(nullsp,btmp);
    773:     vec_rhs      = ksp->vec_rhs;
    774:     ksp->vec_rhs = btmp;
    775:   }
    776:   VecLockPush(ksp->vec_rhs);
    777:   if (ksp->reason == KSP_DIVERGED_PCSETUP_FAILED) {
    778:     VecSetInf(ksp->vec_sol);
    779:   }
    780:   (*ksp->ops->solve)(ksp);

    782:   VecLockPop(ksp->vec_rhs);
    783:   if (nullsp) {
    784:     ksp->vec_rhs = vec_rhs;
    785:     VecDestroy(&btmp);
    786:   }

    788:   ksp->guess_zero = guess_zero;

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

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

    796:   /* diagonal scale solution if called for */
    797:   if (ksp->dscale) {
    798:     VecPointwiseMult(ksp->vec_sol,ksp->vec_sol,ksp->diagonal);
    799:     /* unscale right hand side and matrix */
    800:     if (ksp->dscalefix) {
    801:       Mat mat,pmat;

    803:       VecReciprocal(ksp->diagonal);
    804:       VecPointwiseMult(ksp->vec_rhs,ksp->vec_rhs,ksp->diagonal);
    805:       PCGetOperators(ksp->pc,&mat,&pmat);
    806:       MatDiagonalScale(pmat,ksp->diagonal,ksp->diagonal);
    807:       if (mat != pmat) {MatDiagonalScale(mat,ksp->diagonal,ksp->diagonal);}
    808:       VecReciprocal(ksp->diagonal);
    809:       ksp->dscalefix2 = PETSC_TRUE;
    810:     }
    811:   }
    812:   PetscLogEventEnd(KSP_Solve,ksp,ksp->vec_rhs,ksp->vec_sol,0);
    813:   if (ksp->postsolve) {
    814:     (*ksp->postsolve)(ksp,ksp->vec_rhs,ksp->vec_sol,ksp->postctx);
    815:   }
    816:   if (ksp->guess) {
    817:     KSPGuessUpdate(ksp->guess,ksp->vec_rhs,ksp->vec_sol);
    818:   }

    820:   PCGetOperators(ksp->pc,&mat,&pmat);
    821:   if (ksp->viewEV)       {KSPViewEigenvalues_Internal(ksp, PETSC_FALSE, ksp->viewerEV,    ksp->formatEV);}
    822:   if (ksp->viewEVExp)    {KSPViewEigenvalues_Internal(ksp, PETSC_TRUE,  ksp->viewerEVExp, ksp->formatEVExp);}
    823:   if (ksp->viewSV)       {KSPViewSingularvalues_Internal(ksp, ksp->viewerSV, ksp->formatSV);}
    824:   if (ksp->viewFinalRes) {KSPViewFinalResidual_Internal(ksp, ksp->viewerFinalRes, ksp->formatFinalRes);}
    825:   if (ksp->viewMat)      {ObjectView((PetscObject) mat,          ksp->viewerMat,  ksp->formatMat);}
    826:   if (ksp->viewPMat)     {ObjectView((PetscObject) pmat,         ksp->viewerPMat, ksp->formatPMat);}
    827:   if (ksp->viewRhs)      {ObjectView((PetscObject) ksp->vec_rhs, ksp->viewerRhs,  ksp->formatRhs);}
    828:   if (ksp->viewSol)      {ObjectView((PetscObject) ksp->vec_sol, ksp->viewerSol,  ksp->formatSol);}
    829:   if (ksp->view)         {ObjectView((PetscObject) ksp,          ksp->viewer,     ksp->format);}
    830:   if (ksp->viewMatExp)   {
    831:     Mat A, B;

    833:     PCGetOperators(ksp->pc, &A, NULL);
    834:     MatComputeExplicitOperator(A, &B);
    835:     ObjectView((PetscObject) B, ksp->viewerMatExp, ksp->formatMatExp);
    836:     MatDestroy(&B);
    837:   }
    838:   if (ksp->viewPOpExp)   {
    839:     Mat B;

    841:     KSPComputeExplicitOperator(ksp, &B);
    842:     ObjectView((PetscObject) B, ksp->viewerPOpExp, ksp->formatPOpExp);
    843:     MatDestroy(&B);
    844:   }

    846:   if (inXisinB) {
    847:     VecCopy(x,b);
    848:     VecDestroy(&x);
    849:   }
    850:   PetscObjectSAWsBlock((PetscObject)ksp);
    851:   if (ksp->errorifnotconverged && ksp->reason < 0) SETERRQ(comm,PETSC_ERR_NOT_CONVERGED,"KSPSolve has not converged");
    852:   return(0);
    853: }

    855: /*@
    856:    KSPSolveTranspose - Solves the transpose of a linear system.

    858:    Collective on KSP

    860:    Input Parameter:
    861: +  ksp - iterative context obtained from KSPCreate()
    862: .  b - right hand side vector
    863: -  x - solution vector

    865:    Notes:
    866:     For complex numbers this solve the non-Hermitian transpose system.

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

    870:    Developer Notes:
    871:     We need to implement a KSPSolveHermitianTranspose()

    873:    Level: developer

    875: .keywords: solve, linear system

    877: .seealso: KSPCreate(), KSPSetUp(), KSPDestroy(), KSPSetTolerances(), KSPConvergedDefault(),
    878:           KSPSolve(), KSP
    879: @*/

    881: PetscErrorCode  KSPSolveTranspose(KSP ksp,Vec b,Vec x)
    882: {
    884:   PetscBool      inXisinB=PETSC_FALSE;
    885:   Vec            vec_rhs = 0,btmp;
    886:   Mat            mat,pmat;
    887:   MatNullSpace   nullsp;

    893:   if (x == b) {
    894:     VecDuplicate(b,&x);
    895:     inXisinB = PETSC_TRUE;
    896:   }
    897:   PetscObjectReference((PetscObject)b);
    898:   PetscObjectReference((PetscObject)x);
    899:   VecDestroy(&ksp->vec_rhs);
    900:   VecDestroy(&ksp->vec_sol);

    902:   ksp->vec_rhs         = b;
    903:   ksp->vec_sol         = x;
    904:   ksp->transpose_solve = PETSC_TRUE;

    906:   if (ksp->guess) {
    907:     PetscObjectState ostate,state;

    909:     KSPGuessSetUp(ksp->guess);
    910:     PetscObjectStateGet((PetscObject)ksp->vec_sol,&ostate);
    911:     KSPGuessFormGuess(ksp->guess,ksp->vec_rhs,ksp->vec_sol);
    912:     PetscObjectStateGet((PetscObject)ksp->vec_sol,&state);
    913:     if (state != ostate) {
    914:       ksp->guess_zero = PETSC_FALSE;
    915:     } else {
    916:       PetscInfo(ksp,"Using zero initial guess since the KSPGuess object did not change the vector\n");
    917:       ksp->guess_zero = PETSC_TRUE;
    918:     }
    919:   }

    921:   KSPSetUp(ksp);
    922:   KSPSetUpOnBlocks(ksp);
    923:   if (ksp->guess_zero) { VecSet(ksp->vec_sol,0.0);}

    925:   PCGetOperators(ksp->pc,&mat,&pmat);
    926:   MatGetNullSpace(pmat,&nullsp);
    927:   if (nullsp) {
    928:     VecDuplicate(ksp->vec_rhs,&btmp);
    929:     VecCopy(ksp->vec_rhs,btmp);
    930:     MatNullSpaceRemove(nullsp,btmp);
    931:     vec_rhs      = ksp->vec_rhs;
    932:     ksp->vec_rhs = btmp;
    933:   }

    935:   (*ksp->ops->solve)(ksp);
    936:   if (nullsp) {
    937:     ksp->vec_rhs = vec_rhs;
    938:     VecDestroy(&btmp);
    939:   }
    940:   if (!ksp->reason) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_PLIB,"Internal error, solver returned without setting converged reason");
    941:   if (ksp->viewReason) {KSPReasonView_Internal(ksp, ksp->viewerReason, ksp->formatReason);}
    942:   if (ksp->guess) {
    943:     KSPGuessUpdate(ksp->guess,ksp->vec_rhs,ksp->vec_sol);
    944:   }

    946:   if (ksp->viewMat)      {ObjectView((PetscObject) mat,          ksp->viewerMat,  ksp->formatMat);}
    947:   if (ksp->viewPMat)     {ObjectView((PetscObject) pmat,         ksp->viewerPMat, ksp->formatPMat);}
    948:   if (ksp->viewRhs)      {ObjectView((PetscObject) ksp->vec_rhs, ksp->viewerRhs,  ksp->formatRhs);}
    949:   if (ksp->viewSol)      {ObjectView((PetscObject) ksp->vec_sol, ksp->viewerSol,  ksp->formatSol);}

    951:   if (inXisinB) {
    952:     VecCopy(x,b);
    953:     VecDestroy(&x);
    954:   }
    955:   if (ksp->errorifnotconverged && ksp->reason < 0) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_NOT_CONVERGED,"KSPSolve has not converged");
    956:   return(0);
    957: }

    959: /*@
    960:    KSPReset - Resets a KSP context to the kspsetupcalled = 0 state and removes any allocated Vecs and Mats

    962:    Collective on KSP

    964:    Input Parameter:
    965: .  ksp - iterative context obtained from KSPCreate()

    967:    Level: beginner

    969: .keywords: destroy

    971: .seealso: KSPCreate(), KSPSetUp(), KSPSolve(), KSP
    972: @*/
    973: PetscErrorCode  KSPReset(KSP ksp)
    974: {

    979:   if (!ksp) return(0);
    980:   if (ksp->ops->reset) {
    981:     (*ksp->ops->reset)(ksp);
    982:   }
    983:   if (ksp->pc) {PCReset(ksp->pc);}
    984:   if (ksp->guess) {
    985:     KSPGuess guess = ksp->guess;
    986:     if (guess->ops->reset) { (*guess->ops->reset)(guess); }
    987:   }
    988:   VecDestroyVecs(ksp->nwork,&ksp->work);
    989:   VecDestroy(&ksp->vec_rhs);
    990:   VecDestroy(&ksp->vec_sol);
    991:   VecDestroy(&ksp->diagonal);
    992:   VecDestroy(&ksp->truediagonal);

    994:   PetscViewerDestroy(&ksp->viewer);
    995:   PetscViewerDestroy(&ksp->viewerPre);
    996:   PetscViewerDestroy(&ksp->viewerReason);
    997:   PetscViewerDestroy(&ksp->viewerMat);
    998:   PetscViewerDestroy(&ksp->viewerPMat);
    999:   PetscViewerDestroy(&ksp->viewerRhs);
    1000:   PetscViewerDestroy(&ksp->viewerSol);
    1001:   PetscViewerDestroy(&ksp->viewerMatExp);
    1002:   PetscViewerDestroy(&ksp->viewerEV);
    1003:   PetscViewerDestroy(&ksp->viewerSV);
    1004:   PetscViewerDestroy(&ksp->viewerEVExp);
    1005:   PetscViewerDestroy(&ksp->viewerFinalRes);
    1006:   PetscViewerDestroy(&ksp->viewerPOpExp);

    1008:   ksp->setupstage = KSP_SETUP_NEW;
    1009:   return(0);
    1010: }

    1012: /*@
    1013:    KSPDestroy - Destroys KSP context.

    1015:    Collective on KSP

    1017:    Input Parameter:
    1018: .  ksp - iterative context obtained from KSPCreate()

    1020:    Level: beginner

    1022: .keywords: destroy

    1024: .seealso: KSPCreate(), KSPSetUp(), KSPSolve(), KSP
    1025: @*/
    1026: PetscErrorCode  KSPDestroy(KSP *ksp)
    1027: {
    1029:   PC             pc;

    1032:   if (!*ksp) return(0);
    1034:   if (--((PetscObject)(*ksp))->refct > 0) {*ksp = 0; return(0);}

    1036:   PetscObjectSAWsViewOff((PetscObject)*ksp);

    1038:   /*
    1039:    Avoid a cascading call to PCReset(ksp->pc) from the following call:
    1040:    PCReset() shouldn't be called from KSPDestroy() as it is unprotected by pc's
    1041:    refcount (and may be shared, e.g., by other ksps).
    1042:    */
    1043:   pc         = (*ksp)->pc;
    1044:   (*ksp)->pc = NULL;
    1045:   KSPReset((*ksp));
    1046:   (*ksp)->pc = pc;
    1047:   if ((*ksp)->ops->destroy) {(*(*ksp)->ops->destroy)(*ksp);}

    1049:   KSPGuessDestroy(&(*ksp)->guess);
    1050:   DMDestroy(&(*ksp)->dm);
    1051:   PCDestroy(&(*ksp)->pc);
    1052:   PetscFree((*ksp)->res_hist_alloc);
    1053:   if ((*ksp)->convergeddestroy) {
    1054:     (*(*ksp)->convergeddestroy)((*ksp)->cnvP);
    1055:   }
    1056:   KSPMonitorCancel((*ksp));
    1057:   PetscViewerDestroy(&(*ksp)->eigviewer);
    1058:   PetscHeaderDestroy(ksp);
    1059:   return(0);
    1060: }

    1062: /*@
    1063:     KSPSetPCSide - Sets the preconditioning side.

    1065:     Logically Collective on KSP

    1067:     Input Parameter:
    1068: .   ksp - iterative context obtained from KSPCreate()

    1070:     Output Parameter:
    1071: .   side - the preconditioning side, where side is one of
    1072: .vb
    1073:       PC_LEFT - left preconditioning (default)
    1074:       PC_RIGHT - right preconditioning
    1075:       PC_SYMMETRIC - symmetric preconditioning
    1076: .ve

    1078:     Options Database Keys:
    1079: .   -ksp_pc_side <right,left,symmetric>

    1081:     Notes:
    1082:     Left preconditioning is used by default for most Krylov methods except KSPFGMRES which only supports right preconditioning.

    1084:     For methods changing the side of the preconditioner changes the norm type that is used, see KSPSetNormType().

    1086:     Symmetric preconditioning is currently available only for the KSPQCG method. Note, however, that
    1087:     symmetric preconditioning can be emulated by using either right or left
    1088:     preconditioning and a pre or post processing step.

    1090:     Setting the PC side often affects the default norm type.  See KSPSetNormType() for details.

    1092:     Level: intermediate

    1094: .keywords: set, right, left, symmetric, side, preconditioner, flag

    1096: .seealso: KSPGetPCSide(), KSPSetNormType(), KSPGetNormType(), KSP
    1097: @*/
    1098: PetscErrorCode  KSPSetPCSide(KSP ksp,PCSide side)
    1099: {
    1103:   ksp->pc_side = ksp->pc_side_set = side;
    1104:   return(0);
    1105: }

    1107: /*@
    1108:     KSPGetPCSide - Gets the preconditioning side.

    1110:     Not Collective

    1112:     Input Parameter:
    1113: .   ksp - iterative context obtained from KSPCreate()

    1115:     Output Parameter:
    1116: .   side - the preconditioning side, where side is one of
    1117: .vb
    1118:       PC_LEFT - left preconditioning (default)
    1119:       PC_RIGHT - right preconditioning
    1120:       PC_SYMMETRIC - symmetric preconditioning
    1121: .ve

    1123:     Level: intermediate

    1125: .keywords: get, right, left, symmetric, side, preconditioner, flag

    1127: .seealso: KSPSetPCSide(), KSP
    1128: @*/
    1129: PetscErrorCode  KSPGetPCSide(KSP ksp,PCSide *side)
    1130: {

    1136:   KSPSetUpNorms_Private(ksp,PETSC_TRUE,&ksp->normtype,&ksp->pc_side);
    1137:   *side = ksp->pc_side;
    1138:   return(0);
    1139: }

    1141: /*@
    1142:    KSPGetTolerances - Gets the relative, absolute, divergence, and maximum
    1143:    iteration tolerances used by the default KSP convergence tests.

    1145:    Not Collective

    1147:    Input Parameter:
    1148: .  ksp - the Krylov subspace context

    1150:    Output Parameters:
    1151: +  rtol - the relative convergence tolerance
    1152: .  abstol - the absolute convergence tolerance
    1153: .  dtol - the divergence tolerance
    1154: -  maxits - maximum number of iterations

    1156:    Notes:
    1157:    The user can specify NULL for any parameter that is not needed.

    1159:    Level: intermediate

    1161: .keywords: get, tolerance, absolute, relative, divergence, convergence,
    1162:            maximum, iterations

    1164: .seealso: KSPSetTolerances(), KSP
    1165: @*/
    1166: PetscErrorCode  KSPGetTolerances(KSP ksp,PetscReal *rtol,PetscReal *abstol,PetscReal *dtol,PetscInt *maxits)
    1167: {
    1170:   if (abstol) *abstol = ksp->abstol;
    1171:   if (rtol) *rtol = ksp->rtol;
    1172:   if (dtol) *dtol = ksp->divtol;
    1173:   if (maxits) *maxits = ksp->max_it;
    1174:   return(0);
    1175: }

    1177: /*@
    1178:    KSPSetTolerances - Sets the relative, absolute, divergence, and maximum
    1179:    iteration tolerances used by the default KSP convergence testers.

    1181:    Logically Collective on KSP

    1183:    Input Parameters:
    1184: +  ksp - the Krylov subspace context
    1185: .  rtol - the relative convergence tolerance, relative decrease in the (possibly preconditioned) residual norm
    1186: .  abstol - the absolute convergence tolerance   absolute size of the (possibly preconditioned) residual norm
    1187: .  dtol - the divergence tolerance,   amount (possibly preconditioned) residual norm can increase before KSPConvergedDefault() concludes that the method is diverging
    1188: -  maxits - maximum number of iterations to use

    1190:    Options Database Keys:
    1191: +  -ksp_atol <abstol> - Sets abstol
    1192: .  -ksp_rtol <rtol> - Sets rtol
    1193: .  -ksp_divtol <dtol> - Sets dtol
    1194: -  -ksp_max_it <maxits> - Sets maxits

    1196:    Notes:
    1197:    Use PETSC_DEFAULT to retain the default value of any of the tolerances.

    1199:    See KSPConvergedDefault() for details how these parameters are used in the default convergence test.  See also KSPSetConvergenceTest()
    1200:    for setting user-defined stopping criteria.

    1202:    Level: intermediate

    1204: .keywords: set, tolerance, absolute, relative, divergence,
    1205:            convergence, maximum, iterations

    1207: .seealso: KSPGetTolerances(), KSPConvergedDefault(), KSPSetConvergenceTest(), KSP
    1208: @*/
    1209: PetscErrorCode  KSPSetTolerances(KSP ksp,PetscReal rtol,PetscReal abstol,PetscReal dtol,PetscInt maxits)
    1210: {

    1218:   if (rtol != PETSC_DEFAULT) {
    1219:     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);
    1220:     ksp->rtol = rtol;
    1221:   }
    1222:   if (abstol != PETSC_DEFAULT) {
    1223:     if (abstol < 0.0) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Absolute tolerance %g must be non-negative",(double)abstol);
    1224:     ksp->abstol = abstol;
    1225:   }
    1226:   if (dtol != PETSC_DEFAULT) {
    1227:     if (dtol < 0.0) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Divergence tolerance %g must be larger than 1.0",(double)dtol);
    1228:     ksp->divtol = dtol;
    1229:   }
    1230:   if (maxits != PETSC_DEFAULT) {
    1231:     if (maxits < 0) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Maximum number of iterations %D must be non-negative",maxits);
    1232:     ksp->max_it = maxits;
    1233:   }
    1234:   return(0);
    1235: }

    1237: /*@
    1238:    KSPSetInitialGuessNonzero - Tells the iterative solver that the
    1239:    initial guess is nonzero; otherwise KSP assumes the initial guess
    1240:    is to be zero (and thus zeros it out before solving).

    1242:    Logically Collective on KSP

    1244:    Input Parameters:
    1245: +  ksp - iterative context obtained from KSPCreate()
    1246: -  flg - PETSC_TRUE indicates the guess is non-zero, PETSC_FALSE indicates the guess is zero

    1248:    Options database keys:
    1249: .  -ksp_initial_guess_nonzero : use nonzero initial guess; this takes an optional truth value (0/1/no/yes/true/false)

    1251:    Level: beginner

    1253:    Notes:
    1254:     If this is not called the X vector is zeroed in the call to KSPSolve().

    1256: .keywords: set, initial guess, nonzero

    1258: .seealso: KSPGetInitialGuessNonzero(), KSPSetGuessType(), KSPGuessType, KSP
    1259: @*/
    1260: PetscErrorCode  KSPSetInitialGuessNonzero(KSP ksp,PetscBool flg)
    1261: {
    1265:   ksp->guess_zero = (PetscBool) !(int)flg;
    1266:   return(0);
    1267: }

    1269: /*@
    1270:    KSPGetInitialGuessNonzero - Determines whether the KSP solver is using
    1271:    a zero initial guess.

    1273:    Not Collective

    1275:    Input Parameter:
    1276: .  ksp - iterative context obtained from KSPCreate()

    1278:    Output Parameter:
    1279: .  flag - PETSC_TRUE if guess is nonzero, else PETSC_FALSE

    1281:    Level: intermediate

    1283: .keywords: set, initial guess, nonzero

    1285: .seealso: KSPSetInitialGuessNonzero(), KSP
    1286: @*/
    1287: PetscErrorCode  KSPGetInitialGuessNonzero(KSP ksp,PetscBool  *flag)
    1288: {
    1292:   if (ksp->guess_zero) *flag = PETSC_FALSE;
    1293:   else *flag = PETSC_TRUE;
    1294:   return(0);
    1295: }

    1297: /*@
    1298:    KSPSetErrorIfNotConverged - Causes KSPSolve() to generate an error if the solver has not converged.

    1300:    Logically Collective on KSP

    1302:    Input Parameters:
    1303: +  ksp - iterative context obtained from KSPCreate()
    1304: -  flg - PETSC_TRUE indicates you want the error generated

    1306:    Options database keys:
    1307: .  -ksp_error_if_not_converged : this takes an optional truth value (0/1/no/yes/true/false)

    1309:    Level: intermediate

    1311:    Notes:
    1312:     Normally PETSc continues if a linear solver fails to converge, you can call KSPGetConvergedReason() after a KSPSolve()
    1313:     to determine if it has converged.

    1316: .seealso: KSPGetErrorIfNotConverged(), KSP
    1317: @*/
    1318: PetscErrorCode  KSPSetErrorIfNotConverged(KSP ksp,PetscBool flg)
    1319: {
    1323:   ksp->errorifnotconverged = flg;
    1324:   return(0);
    1325: }

    1327: /*@
    1328:    KSPGetErrorIfNotConverged - Will KSPSolve() generate an error if the solver does not converge?

    1330:    Not Collective

    1332:    Input Parameter:
    1333: .  ksp - iterative context obtained from KSPCreate()

    1335:    Output Parameter:
    1336: .  flag - PETSC_TRUE if it will generate an error, else PETSC_FALSE

    1338:    Level: intermediate

    1340: .seealso: KSPSetErrorIfNotConverged(), KSP
    1341: @*/
    1342: PetscErrorCode  KSPGetErrorIfNotConverged(KSP ksp,PetscBool  *flag)
    1343: {
    1347:   *flag = ksp->errorifnotconverged;
    1348:   return(0);
    1349: }

    1351: /*@
    1352:    KSPSetInitialGuessKnoll - Tells the iterative solver to use PCApply(pc,b,..) to compute the initial guess (The Knoll trick)

    1354:    Logically Collective on KSP

    1356:    Input Parameters:
    1357: +  ksp - iterative context obtained from KSPCreate()
    1358: -  flg - PETSC_TRUE or PETSC_FALSE

    1360:    Level: advanced

    1362:    Developer Note: the Knoll trick is not currently implemented using the KSPGuess class

    1364: .keywords: set, initial guess, nonzero

    1366: .seealso: KSPGetInitialGuessKnoll(), KSPSetInitialGuessNonzero(), KSPGetInitialGuessNonzero(), KSP
    1367: @*/
    1368: PetscErrorCode  KSPSetInitialGuessKnoll(KSP ksp,PetscBool flg)
    1369: {
    1373:   ksp->guess_knoll = flg;
    1374:   return(0);
    1375: }

    1377: /*@
    1378:    KSPGetInitialGuessKnoll - Determines whether the KSP solver is using the Knoll trick (using PCApply(pc,b,...) to compute
    1379:      the initial guess

    1381:    Not Collective

    1383:    Input Parameter:
    1384: .  ksp - iterative context obtained from KSPCreate()

    1386:    Output Parameter:
    1387: .  flag - PETSC_TRUE if using Knoll trick, else PETSC_FALSE

    1389:    Level: advanced

    1391: .keywords: set, initial guess, nonzero

    1393: .seealso: KSPSetInitialGuessKnoll(), KSPSetInitialGuessNonzero(), KSPGetInitialGuessNonzero(), KSP
    1394: @*/
    1395: PetscErrorCode  KSPGetInitialGuessKnoll(KSP ksp,PetscBool  *flag)
    1396: {
    1400:   *flag = ksp->guess_knoll;
    1401:   return(0);
    1402: }

    1404: /*@
    1405:    KSPGetComputeSingularValues - Gets the flag indicating whether the extreme singular
    1406:    values will be calculated via a Lanczos or Arnoldi process as the linear
    1407:    system is solved.

    1409:    Not Collective

    1411:    Input Parameter:
    1412: .  ksp - iterative context obtained from KSPCreate()

    1414:    Output Parameter:
    1415: .  flg - PETSC_TRUE or PETSC_FALSE

    1417:    Options Database Key:
    1418: .  -ksp_monitor_singular_value - Activates KSPSetComputeSingularValues()

    1420:    Notes:
    1421:    Currently this option is not valid for all iterative methods.

    1423:    Many users may just want to use the monitoring routine
    1424:    KSPMonitorSingularValue() (which can be set with option -ksp_monitor_singular_value)
    1425:    to print the singular values at each iteration of the linear solve.

    1427:    Level: advanced

    1429: .keywords: set, compute, singular values

    1431: .seealso: KSPComputeExtremeSingularValues(), KSPMonitorSingularValue(), KSP
    1432: @*/
    1433: PetscErrorCode  KSPGetComputeSingularValues(KSP ksp,PetscBool  *flg)
    1434: {
    1438:   *flg = ksp->calc_sings;
    1439:   return(0);
    1440: }

    1442: /*@
    1443:    KSPSetComputeSingularValues - Sets a flag so that the extreme singular
    1444:    values will be calculated via a Lanczos or Arnoldi process as the linear
    1445:    system is solved.

    1447:    Logically Collective on KSP

    1449:    Input Parameters:
    1450: +  ksp - iterative context obtained from KSPCreate()
    1451: -  flg - PETSC_TRUE or PETSC_FALSE

    1453:    Options Database Key:
    1454: .  -ksp_monitor_singular_value - Activates KSPSetComputeSingularValues()

    1456:    Notes:
    1457:    Currently this option is not valid for all iterative methods.

    1459:    Many users may just want to use the monitoring routine
    1460:    KSPMonitorSingularValue() (which can be set with option -ksp_monitor_singular_value)
    1461:    to print the singular values at each iteration of the linear solve.

    1463:    Level: advanced

    1465: .keywords: set, compute, singular values

    1467: .seealso: KSPComputeExtremeSingularValues(), KSPMonitorSingularValue(), KSP
    1468: @*/
    1469: PetscErrorCode  KSPSetComputeSingularValues(KSP ksp,PetscBool flg)
    1470: {
    1474:   ksp->calc_sings = flg;
    1475:   return(0);
    1476: }

    1478: /*@
    1479:    KSPGetComputeEigenvalues - Gets the flag indicating that the extreme eigenvalues
    1480:    values will be calculated via a Lanczos or Arnoldi process as the linear
    1481:    system is solved.

    1483:    Not Collective

    1485:    Input Parameter:
    1486: .  ksp - iterative context obtained from KSPCreate()

    1488:    Output Parameter:
    1489: .  flg - PETSC_TRUE or PETSC_FALSE

    1491:    Notes:
    1492:    Currently this option is not valid for all iterative methods.

    1494:    Level: advanced

    1496: .keywords: set, compute, eigenvalues

    1498: .seealso: KSPComputeEigenvalues(), KSPComputeEigenvaluesExplicitly(), KSP
    1499: @*/
    1500: PetscErrorCode  KSPGetComputeEigenvalues(KSP ksp,PetscBool  *flg)
    1501: {
    1505:   *flg = ksp->calc_sings;
    1506:   return(0);
    1507: }

    1509: /*@
    1510:    KSPSetComputeEigenvalues - Sets a flag so that the extreme eigenvalues
    1511:    values will be calculated via a Lanczos or Arnoldi process as the linear
    1512:    system is solved.

    1514:    Logically Collective on KSP

    1516:    Input Parameters:
    1517: +  ksp - iterative context obtained from KSPCreate()
    1518: -  flg - PETSC_TRUE or PETSC_FALSE

    1520:    Notes:
    1521:    Currently this option is not valid for all iterative methods.

    1523:    Level: advanced

    1525: .keywords: set, compute, eigenvalues

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

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

    1543:    Logically Collective on KSP

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

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

    1552:    Level: advanced

    1554: .keywords: set, compute, ritz

    1556: .seealso: KSPComputeRitz(), KSP
    1557: @*/
    1558: PetscErrorCode  KSPSetComputeRitz(KSP ksp, PetscBool flg)
    1559: {
    1563:   ksp->calc_ritz = flg;
    1564:   return(0);
    1565: }

    1567: /*@
    1568:    KSPGetRhs - Gets the right-hand-side vector for the linear system to
    1569:    be solved.

    1571:    Not Collective

    1573:    Input Parameter:
    1574: .  ksp - iterative context obtained from KSPCreate()

    1576:    Output Parameter:
    1577: .  r - right-hand-side vector

    1579:    Level: developer

    1581: .keywords: get, right-hand-side, rhs

    1583: .seealso: KSPGetSolution(), KSPSolve(), KSP
    1584: @*/
    1585: PetscErrorCode  KSPGetRhs(KSP ksp,Vec *r)
    1586: {
    1590:   *r = ksp->vec_rhs;
    1591:   return(0);
    1592: }

    1594: /*@
    1595:    KSPGetSolution - Gets the location of the solution for the
    1596:    linear system to be solved.  Note that this may not be where the solution
    1597:    is stored during the iterative process; see KSPBuildSolution().

    1599:    Not Collective

    1601:    Input Parameters:
    1602: .  ksp - iterative context obtained from KSPCreate()

    1604:    Output Parameters:
    1605: .  v - solution vector

    1607:    Level: developer

    1609: .keywords: get, solution

    1611: .seealso: KSPGetRhs(),  KSPBuildSolution(), KSPSolve(), KSP
    1612: @*/
    1613: PetscErrorCode  KSPGetSolution(KSP ksp,Vec *v)
    1614: {
    1618:   *v = ksp->vec_sol;
    1619:   return(0);
    1620: }

    1622: /*@
    1623:    KSPSetPC - Sets the preconditioner to be used to calculate the
    1624:    application of the preconditioner on a vector.

    1626:    Collective on KSP

    1628:    Input Parameters:
    1629: +  ksp - iterative context obtained from KSPCreate()
    1630: -  pc   - the preconditioner object

    1632:    Notes:
    1633:    Use KSPGetPC() to retrieve the preconditioner context (for example,
    1634:    to free it at the end of the computations).

    1636:    Level: developer

    1638: .keywords: set, precondition, Binv

    1640: .seealso: KSPGetPC(), KSP
    1641: @*/
    1642: PetscErrorCode  KSPSetPC(KSP ksp,PC pc)
    1643: {

    1650:   PetscObjectReference((PetscObject)pc);
    1651:   PCDestroy(&ksp->pc);
    1652:   ksp->pc = pc;
    1653:   PetscLogObjectParent((PetscObject)ksp,(PetscObject)ksp->pc);
    1654:   return(0);
    1655: }

    1657: /*@
    1658:    KSPGetPC - Returns a pointer to the preconditioner context
    1659:    set with KSPSetPC().

    1661:    Not Collective

    1663:    Input Parameters:
    1664: .  ksp - iterative context obtained from KSPCreate()

    1666:    Output Parameter:
    1667: .  pc - preconditioner context

    1669:    Level: developer

    1671: .keywords: get, preconditioner, Binv

    1673: .seealso: KSPSetPC(), KSP
    1674: @*/
    1675: PetscErrorCode  KSPGetPC(KSP ksp,PC *pc)
    1676: {

    1682:   if (!ksp->pc) {
    1683:     PCCreate(PetscObjectComm((PetscObject)ksp),&ksp->pc);
    1684:     PetscObjectIncrementTabLevel((PetscObject)ksp->pc,(PetscObject)ksp,0);
    1685:     PetscLogObjectParent((PetscObject)ksp,(PetscObject)ksp->pc);
    1686:   }
    1687:   *pc = ksp->pc;
    1688:   return(0);
    1689: }

    1691: /*@
    1692:    KSPMonitor - runs the user provided monitor routines, if they exist

    1694:    Collective on KSP

    1696:    Input Parameters:
    1697: +  ksp - iterative context obtained from KSPCreate()
    1698: .  it - iteration number
    1699: -  rnorm - relative norm of the residual

    1701:    Notes:
    1702:    This routine is called by the KSP implementations.
    1703:    It does not typically need to be called by the user.

    1705:    Level: developer

    1707: .seealso: KSPMonitorSet()
    1708: @*/
    1709: PetscErrorCode KSPMonitor(KSP ksp,PetscInt it,PetscReal rnorm)
    1710: {
    1711:   PetscInt       i, n = ksp->numbermonitors;

    1715:   for (i=0; i<n; i++) {
    1716:     (*ksp->monitor[i])(ksp,it,rnorm,ksp->monitorcontext[i]);
    1717:   }
    1718:   return(0);
    1719: }

    1721: /*

    1723:     Checks if two monitors are identical; if they are then it destroys the new one
    1724: */
    1725: PetscErrorCode PetscMonitorCompare(PetscErrorCode (*nmon)(void),void *nmctx,PetscErrorCode (*nmdestroy)(void**),PetscErrorCode (*mon)(void),void *mctx,PetscErrorCode (*mdestroy)(void**),PetscBool *identical)
    1726: {
    1727:   *identical = PETSC_FALSE;
    1728:   if (nmon == mon && nmdestroy == mdestroy) {
    1729:     if (nmctx == mctx) *identical = PETSC_TRUE;
    1730:     else if (nmdestroy == (PetscErrorCode (*)(void**)) PetscViewerAndFormatDestroy) {
    1731:       PetscViewerAndFormat *old = (PetscViewerAndFormat*)mctx, *newo = (PetscViewerAndFormat*)nmctx;
    1732:       if (old->viewer == newo->viewer && old->format == newo->format) *identical = PETSC_TRUE;
    1733:     }
    1734:     if (*identical) {
    1735:       if (mdestroy) {
    1737:         (*mdestroy)(&nmctx);
    1738:       }
    1739:     }
    1740:   }
    1741:   return(0);
    1742: }

    1744: /*@C
    1745:    KSPMonitorSet - Sets an ADDITIONAL function to be called at every iteration to monitor
    1746:    the residual/error etc.

    1748:    Logically Collective on KSP

    1750:    Input Parameters:
    1751: +  ksp - iterative context obtained from KSPCreate()
    1752: .  monitor - pointer to function (if this is NULL, it turns off monitoring
    1753: .  mctx    - [optional] context for private data for the
    1754:              monitor routine (use NULL if no context is desired)
    1755: -  monitordestroy - [optional] routine that frees monitor context
    1756:           (may be NULL)

    1758:    Calling Sequence of monitor:
    1759: $     monitor (KSP ksp, int it, PetscReal rnorm, void *mctx)

    1761: +  ksp - iterative context obtained from KSPCreate()
    1762: .  it - iteration number
    1763: .  rnorm - (estimated) 2-norm of (preconditioned) residual
    1764: -  mctx  - optional monitoring context, as set by KSPMonitorSet()

    1766:    Options Database Keys:
    1767: +    -ksp_monitor        - sets KSPMonitorDefault()
    1768: .    -ksp_monitor_true_residual    - sets KSPMonitorTrueResidualNorm()
    1769: .    -ksp_monitor_max    - sets KSPMonitorTrueResidualMaxNorm()
    1770: .    -ksp_monitor_lg_residualnorm    - sets line graph monitor,
    1771:                            uses KSPMonitorLGResidualNormCreate()
    1772: .    -ksp_monitor_lg_true_residualnorm   - sets line graph monitor,
    1773:                            uses KSPMonitorLGResidualNormCreate()
    1774: .    -ksp_monitor_singular_value    - sets KSPMonitorSingularValue()
    1775: -    -ksp_monitor_cancel - cancels all monitors that have
    1776:                           been hardwired into a code by
    1777:                           calls to KSPMonitorSet(), but
    1778:                           does not cancel those set via
    1779:                           the options database.

    1781:    Notes:
    1782:    The default is to do nothing.  To print the residual, or preconditioned
    1783:    residual if KSPSetNormType(ksp,KSP_NORM_PRECONDITIONED) was called, use
    1784:    KSPMonitorDefault() as the monitoring routine, with a ASCII viewer as the
    1785:    context.

    1787:    Several different monitoring routines may be set by calling
    1788:    KSPMonitorSet() multiple times; all will be called in the
    1789:    order in which they were set.

    1791:    Fortran Notes:
    1792:     Only a single monitor function can be set for each KSP object

    1794:    Level: beginner

    1796: .keywords: set, monitor

    1798: .seealso: KSPMonitorDefault(), KSPMonitorLGResidualNormCreate(), KSPMonitorCancel(), KSP
    1799: @*/
    1800: PetscErrorCode  KSPMonitorSet(KSP ksp,PetscErrorCode (*monitor)(KSP,PetscInt,PetscReal,void*),void *mctx,PetscErrorCode (*monitordestroy)(void**))
    1801: {
    1802:   PetscInt       i;
    1804:   PetscBool      identical;

    1808:   for (i=0; i<ksp->numbermonitors;i++) {
    1809:     PetscMonitorCompare((PetscErrorCode (*)(void))monitor,mctx,monitordestroy,(PetscErrorCode (*)(void))ksp->monitor[i],ksp->monitorcontext[i],ksp->monitordestroy[i],&identical);
    1810:     if (identical) return(0);
    1811:   }
    1812:   if (ksp->numbermonitors >= MAXKSPMONITORS) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Too many KSP monitors set");
    1813:   ksp->monitor[ksp->numbermonitors]          = monitor;
    1814:   ksp->monitordestroy[ksp->numbermonitors]   = monitordestroy;
    1815:   ksp->monitorcontext[ksp->numbermonitors++] = (void*)mctx;
    1816:   return(0);
    1817: }

    1819: /*@
    1820:    KSPMonitorCancel - Clears all monitors for a KSP object.

    1822:    Logically Collective on KSP

    1824:    Input Parameters:
    1825: .  ksp - iterative context obtained from KSPCreate()

    1827:    Options Database Key:
    1828: .  -ksp_monitor_cancel - Cancels all monitors that have
    1829:     been hardwired into a code by calls to KSPMonitorSet(),
    1830:     but does not cancel those set via the options database.

    1832:    Level: intermediate

    1834: .keywords: set, monitor

    1836: .seealso: KSPMonitorDefault(), KSPMonitorLGResidualNormCreate(), KSPMonitorSet(), KSP
    1837: @*/
    1838: PetscErrorCode  KSPMonitorCancel(KSP ksp)
    1839: {
    1841:   PetscInt       i;

    1845:   for (i=0; i<ksp->numbermonitors; i++) {
    1846:     if (ksp->monitordestroy[i]) {
    1847:       (*ksp->monitordestroy[i])(&ksp->monitorcontext[i]);
    1848:     }
    1849:   }
    1850:   ksp->numbermonitors = 0;
    1851:   return(0);
    1852: }

    1854: /*@C
    1855:    KSPGetMonitorContext - Gets the monitoring context, as set by
    1856:    KSPMonitorSet() for the FIRST monitor only.

    1858:    Not Collective

    1860:    Input Parameter:
    1861: .  ksp - iterative context obtained from KSPCreate()

    1863:    Output Parameter:
    1864: .  ctx - monitoring context

    1866:    Level: intermediate

    1868: .keywords: get, monitor, context

    1870: .seealso: KSPMonitorDefault(), KSPMonitorLGResidualNormCreate(), KSP
    1871: @*/
    1872: PetscErrorCode  KSPGetMonitorContext(KSP ksp,void **ctx)
    1873: {
    1876:   *ctx =      (ksp->monitorcontext[0]);
    1877:   return(0);
    1878: }

    1880: /*@
    1881:    KSPSetResidualHistory - Sets the array used to hold the residual history.
    1882:    If set, this array will contain the residual norms computed at each
    1883:    iteration of the solver.

    1885:    Not Collective

    1887:    Input Parameters:
    1888: +  ksp - iterative context obtained from KSPCreate()
    1889: .  a   - array to hold history
    1890: .  na  - size of a
    1891: -  reset - PETSC_TRUE indicates the history counter is reset to zero
    1892:            for each new linear solve

    1894:    Level: advanced

    1896:    Notes:
    1897:     The array is NOT freed by PETSc so the user needs to keep track of
    1898:            it and destroy once the KSP object is destroyed.

    1900:    If 'a' is NULL then space is allocated for the history. If 'na' PETSC_DECIDE or PETSC_DEFAULT then a
    1901:    default array of length 10000 is allocated.

    1903: .keywords: set, residual, history, norm

    1905: .seealso: KSPGetResidualHistory(), KSP

    1907: @*/
    1908: PetscErrorCode  KSPSetResidualHistory(KSP ksp,PetscReal a[],PetscInt na,PetscBool reset)
    1909: {

    1915:   PetscFree(ksp->res_hist_alloc);
    1916:   if (na != PETSC_DECIDE && na != PETSC_DEFAULT && a) {
    1917:     ksp->res_hist     = a;
    1918:     ksp->res_hist_max = na;
    1919:   } else {
    1920:     if (na != PETSC_DECIDE && na != PETSC_DEFAULT) ksp->res_hist_max = na;
    1921:     else                                           ksp->res_hist_max = 10000; /* like default ksp->max_it */
    1922:     PetscCalloc1(ksp->res_hist_max,&ksp->res_hist_alloc);

    1924:     ksp->res_hist = ksp->res_hist_alloc;
    1925:   }
    1926:   ksp->res_hist_len   = 0;
    1927:   ksp->res_hist_reset = reset;
    1928:   return(0);
    1929: }

    1931: /*@C
    1932:    KSPGetResidualHistory - Gets the array used to hold the residual history
    1933:    and the number of residuals it contains.

    1935:    Not Collective

    1937:    Input Parameter:
    1938: .  ksp - iterative context obtained from KSPCreate()

    1940:    Output Parameters:
    1941: +  a   - pointer to array to hold history (or NULL)
    1942: -  na  - number of used entries in a (or NULL)

    1944:    Level: advanced

    1946:    Notes:
    1947:      Can only be called after a KSPSetResidualHistory() otherwise a and na are set to zero

    1949:      The Fortran version of this routine has a calling sequence
    1950: $   call KSPGetResidualHistory(KSP ksp, integer na, integer ierr)
    1951:     note that you have passed a Fortran array into KSPSetResidualHistory() and you need
    1952:     to access the residual values from this Fortran array you provided. Only the na (number of
    1953:     residual norms currently held) is set.

    1955: .keywords: get, residual, history, norm

    1957: .seealso: KSPGetResidualHistory(), KSP

    1959: @*/
    1960: PetscErrorCode  KSPGetResidualHistory(KSP ksp,PetscReal *a[],PetscInt *na)
    1961: {
    1964:   if (a) *a = ksp->res_hist;
    1965:   if (na) *na = ksp->res_hist_len;
    1966:   return(0);
    1967: }

    1969: /*@C
    1970:    KSPSetConvergenceTest - Sets the function to be used to determine
    1971:    convergence.

    1973:    Logically Collective on KSP

    1975:    Input Parameters:
    1976: +  ksp - iterative context obtained from KSPCreate()
    1977: .  converge - pointer to int function
    1978: .  cctx    - context for private data for the convergence routine (may be null)
    1979: -  destroy - a routine for destroying the context (may be null)

    1981:    Calling sequence of converge:
    1982: $     converge (KSP ksp, int it, PetscReal rnorm, KSPConvergedReason *reason,void *mctx)

    1984: +  ksp - iterative context obtained from KSPCreate()
    1985: .  it - iteration number
    1986: .  rnorm - (estimated) 2-norm of (preconditioned) residual
    1987: .  reason - the reason why it has converged or diverged
    1988: -  cctx  - optional convergence context, as set by KSPSetConvergenceTest()

    1991:    Notes:
    1992:    Must be called after the KSP type has been set so put this after
    1993:    a call to KSPSetType(), or KSPSetFromOptions().

    1995:    The default convergence test, KSPConvergedDefault(), aborts if the
    1996:    residual grows to more than 10000 times the initial residual.

    1998:    The default is a combination of relative and absolute tolerances.
    1999:    The residual value that is tested may be an approximation; routines
    2000:    that need exact values should compute them.

    2002:    In the default PETSc convergence test, the precise values of reason
    2003:    are macros such as KSP_CONVERGED_RTOL, which are defined in petscksp.h.

    2005:    Level: advanced

    2007: .keywords: set, convergence, test, context

    2009: .seealso: KSPConvergedDefault(), KSPGetConvergenceContext(), KSPSetTolerances(), KSP
    2010: @*/
    2011: PetscErrorCode  KSPSetConvergenceTest(KSP ksp,PetscErrorCode (*converge)(KSP,PetscInt,PetscReal,KSPConvergedReason*,void*),void *cctx,PetscErrorCode (*destroy)(void*))
    2012: {

    2017:   if (ksp->convergeddestroy) {
    2018:     (*ksp->convergeddestroy)(ksp->cnvP);
    2019:   }
    2020:   ksp->converged        = converge;
    2021:   ksp->convergeddestroy = destroy;
    2022:   ksp->cnvP             = (void*)cctx;
    2023:   return(0);
    2024: }

    2026: /*@C
    2027:    KSPGetConvergenceContext - Gets the convergence context set with
    2028:    KSPSetConvergenceTest().

    2030:    Not Collective

    2032:    Input Parameter:
    2033: .  ksp - iterative context obtained from KSPCreate()

    2035:    Output Parameter:
    2036: .  ctx - monitoring context

    2038:    Level: advanced

    2040: .keywords: get, convergence, test, context

    2042: .seealso: KSPConvergedDefault(), KSPSetConvergenceTest(), KSP
    2043: @*/
    2044: PetscErrorCode  KSPGetConvergenceContext(KSP ksp,void **ctx)
    2045: {
    2048:   *ctx = ksp->cnvP;
    2049:   return(0);
    2050: }

    2052: /*@C
    2053:    KSPBuildSolution - Builds the approximate solution in a vector provided.
    2054:    This routine is NOT commonly needed (see KSPSolve()).

    2056:    Collective on KSP

    2058:    Input Parameter:
    2059: .  ctx - iterative context obtained from KSPCreate()

    2061:    Output Parameter:
    2062:    Provide exactly one of
    2063: +  v - location to stash solution.
    2064: -  V - the solution is returned in this location. This vector is created
    2065:        internally. This vector should NOT be destroyed by the user with
    2066:        VecDestroy().

    2068:    Notes:
    2069:    This routine can be used in one of two ways
    2070: .vb
    2071:       KSPBuildSolution(ksp,NULL,&V);
    2072:    or
    2073:       KSPBuildSolution(ksp,v,NULL); or KSPBuildSolution(ksp,v,&v);
    2074: .ve
    2075:    In the first case an internal vector is allocated to store the solution
    2076:    (the user cannot destroy this vector). In the second case the solution
    2077:    is generated in the vector that the user provides. Note that for certain
    2078:    methods, such as KSPCG, the second case requires a copy of the solution,
    2079:    while in the first case the call is essentially free since it simply
    2080:    returns the vector where the solution already is stored. For some methods
    2081:    like GMRES this is a reasonably expensive operation and should only be
    2082:    used in truly needed.

    2084:    Level: advanced

    2086: .keywords: build, solution

    2088: .seealso: KSPGetSolution(), KSPBuildResidual(), KSP
    2089: @*/
    2090: PetscErrorCode  KSPBuildSolution(KSP ksp,Vec v,Vec *V)
    2091: {

    2096:   if (!V && !v) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_WRONG,"Must provide either v or V");
    2097:   if (!V) V = &v;
    2098:   (*ksp->ops->buildsolution)(ksp,v,V);
    2099:   return(0);
    2100: }

    2102: /*@C
    2103:    KSPBuildResidual - Builds the residual in a vector provided.

    2105:    Collective on KSP

    2107:    Input Parameter:
    2108: .  ksp - iterative context obtained from KSPCreate()

    2110:    Output Parameters:
    2111: +  v - optional location to stash residual.  If v is not provided,
    2112:        then a location is generated.
    2113: .  t - work vector.  If not provided then one is generated.
    2114: -  V - the residual

    2116:    Notes:
    2117:    Regardless of whether or not v is provided, the residual is
    2118:    returned in V.

    2120:    Level: advanced

    2122: .keywords: KSP, build, residual

    2124: .seealso: KSPBuildSolution()
    2125: @*/
    2126: PetscErrorCode  KSPBuildResidual(KSP ksp,Vec t,Vec v,Vec *V)
    2127: {
    2129:   PetscBool      flag = PETSC_FALSE;
    2130:   Vec            w    = v,tt = t;

    2134:   if (!w) {
    2135:     VecDuplicate(ksp->vec_rhs,&w);
    2136:     PetscLogObjectParent((PetscObject)ksp,(PetscObject)w);
    2137:   }
    2138:   if (!tt) {
    2139:     VecDuplicate(ksp->vec_sol,&tt); flag = PETSC_TRUE;
    2140:     PetscLogObjectParent((PetscObject)ksp,(PetscObject)tt);
    2141:   }
    2142:   (*ksp->ops->buildresidual)(ksp,tt,w,V);
    2143:   if (flag) {VecDestroy(&tt);}
    2144:   return(0);
    2145: }

    2147: /*@
    2148:    KSPSetDiagonalScale - Tells KSP to symmetrically diagonally scale the system
    2149:      before solving. This actually CHANGES the matrix (and right hand side).

    2151:    Logically Collective on KSP

    2153:    Input Parameter:
    2154: +  ksp - the KSP context
    2155: -  scale - PETSC_TRUE or PETSC_FALSE

    2157:    Options Database Key:
    2158: +   -ksp_diagonal_scale -
    2159: -   -ksp_diagonal_scale_fix - scale the matrix back AFTER the solve

    2162:     Notes:
    2163:     Scales the matrix by  D^(-1/2)  A  D^(-1/2)  [D^(1/2) x ] = D^(-1/2) b
    2164:        where D_{ii} is 1/abs(A_{ii}) unless A_{ii} is zero and then it is 1.

    2166:     BE CAREFUL with this routine: it actually scales the matrix and right
    2167:     hand side that define the system. After the system is solved the matrix
    2168:     and right hand side remain scaled unless you use KSPSetDiagonalScaleFix()

    2170:     This should NOT be used within the SNES solves if you are using a line
    2171:     search.

    2173:     If you use this with the PCType Eisenstat preconditioner than you can
    2174:     use the PCEisenstatSetNoDiagonalScaling() option, or -pc_eisenstat_no_diagonal_scaling
    2175:     to save some unneeded, redundant flops.

    2177:    Level: intermediate

    2179: .keywords: set, options, prefix, database

    2181: .seealso: KSPGetDiagonalScale(), KSPSetDiagonalScaleFix(), KSP
    2182: @*/
    2183: PetscErrorCode  KSPSetDiagonalScale(KSP ksp,PetscBool scale)
    2184: {
    2188:   ksp->dscale = scale;
    2189:   return(0);
    2190: }

    2192: /*@
    2193:    KSPGetDiagonalScale - Checks if KSP solver scales the matrix and
    2194:                           right hand side

    2196:    Not Collective

    2198:    Input Parameter:
    2199: .  ksp - the KSP context

    2201:    Output Parameter:
    2202: .  scale - PETSC_TRUE or PETSC_FALSE

    2204:    Notes:
    2205:     BE CAREFUL with this routine: it actually scales the matrix and right
    2206:     hand side that define the system. After the system is solved the matrix
    2207:     and right hand side remain scaled  unless you use KSPSetDiagonalScaleFix()

    2209:    Level: intermediate

    2211: .keywords: set, options, prefix, database

    2213: .seealso: KSPSetDiagonalScale(), KSPSetDiagonalScaleFix(), KSP
    2214: @*/
    2215: PetscErrorCode  KSPGetDiagonalScale(KSP ksp,PetscBool  *scale)
    2216: {
    2220:   *scale = ksp->dscale;
    2221:   return(0);
    2222: }

    2224: /*@
    2225:    KSPSetDiagonalScaleFix - Tells KSP to diagonally scale the system
    2226:      back after solving.

    2228:    Logically Collective on KSP

    2230:    Input Parameter:
    2231: +  ksp - the KSP context
    2232: -  fix - PETSC_TRUE to scale back after the system solve, PETSC_FALSE to not
    2233:          rescale (default)

    2235:    Notes:
    2236:      Must be called after KSPSetDiagonalScale()

    2238:      Using this will slow things down, because it rescales the matrix before and
    2239:      after each linear solve. This is intended mainly for testing to allow one
    2240:      to easily get back the original system to make sure the solution computed is
    2241:      accurate enough.

    2243:    Level: intermediate

    2245: .keywords: set, options, prefix, database

    2247: .seealso: KSPGetDiagonalScale(), KSPSetDiagonalScale(), KSPGetDiagonalScaleFix(), KSP
    2248: @*/
    2249: PetscErrorCode  KSPSetDiagonalScaleFix(KSP ksp,PetscBool fix)
    2250: {
    2254:   ksp->dscalefix = fix;
    2255:   return(0);
    2256: }

    2258: /*@
    2259:    KSPGetDiagonalScaleFix - Determines if KSP diagonally scales the system
    2260:      back after solving.

    2262:    Not Collective

    2264:    Input Parameter:
    2265: .  ksp - the KSP context

    2267:    Output Parameter:
    2268: .  fix - PETSC_TRUE to scale back after the system solve, PETSC_FALSE to not
    2269:          rescale (default)

    2271:    Notes:
    2272:      Must be called after KSPSetDiagonalScale()

    2274:      If PETSC_TRUE will slow things down, because it rescales the matrix before and
    2275:      after each linear solve. This is intended mainly for testing to allow one
    2276:      to easily get back the original system to make sure the solution computed is
    2277:      accurate enough.

    2279:    Level: intermediate

    2281: .keywords: set, options, prefix, database

    2283: .seealso: KSPGetDiagonalScale(), KSPSetDiagonalScale(), KSPSetDiagonalScaleFix(), KSP
    2284: @*/
    2285: PetscErrorCode  KSPGetDiagonalScaleFix(KSP ksp,PetscBool  *fix)
    2286: {
    2290:   *fix = ksp->dscalefix;
    2291:   return(0);
    2292: }

    2294: /*@C
    2295:    KSPSetComputeOperators - set routine to compute the linear operators

    2297:    Logically Collective

    2299:    Input Arguments:
    2300: +  ksp - the KSP context
    2301: .  func - function to compute the operators
    2302: -  ctx - optional context

    2304:    Calling sequence of func:
    2305: $  func(KSP ksp,Mat A,Mat B,void *ctx)

    2307: +  ksp - the KSP context
    2308: .  A - the linear operator
    2309: .  B - preconditioning matrix
    2310: -  ctx - optional user-provided context

    2312:    Notes:
    2313:     The user provided func() will be called automatically at the very next call to KSPSolve(). It will not be called at future KSPSolve() calls
    2314:           unless either KSPSetComputeOperators() or KSPSetOperators() is called before that KSPSolve() is called.

    2316:           To reuse the same preconditioner for the next KSPSolve() and not compute a new one based on the most recently computed matrix call KSPSetReusePreconditioner()

    2318:    Level: beginner

    2320: .seealso: KSPSetOperators(), KSPSetComputeRHS(), DMKSPSetComputeOperators(), KSPSetComputeInitialGuess()
    2321: @*/
    2322: PetscErrorCode KSPSetComputeOperators(KSP ksp,PetscErrorCode (*func)(KSP,Mat,Mat,void*),void *ctx)
    2323: {
    2325:   DM             dm;

    2329:   KSPGetDM(ksp,&dm);
    2330:   DMKSPSetComputeOperators(dm,func,ctx);
    2331:   if (ksp->setupstage == KSP_SETUP_NEWRHS) ksp->setupstage = KSP_SETUP_NEWMATRIX;
    2332:   return(0);
    2333: }

    2335: /*@C
    2336:    KSPSetComputeRHS - set routine to compute the right hand side of the linear system

    2338:    Logically Collective

    2340:    Input Arguments:
    2341: +  ksp - the KSP context
    2342: .  func - function to compute the right hand side
    2343: -  ctx - optional context

    2345:    Calling sequence of func:
    2346: $  func(KSP ksp,Vec b,void *ctx)

    2348: +  ksp - the KSP context
    2349: .  b - right hand side of linear system
    2350: -  ctx - optional user-provided context

    2352:    Notes:
    2353:     The routine you provide will be called EACH you call KSPSolve() to prepare the new right hand side for that solve

    2355:    Level: beginner

    2357: .seealso: KSPSolve(), DMKSPSetComputeRHS(), KSPSetComputeOperators()
    2358: @*/
    2359: PetscErrorCode KSPSetComputeRHS(KSP ksp,PetscErrorCode (*func)(KSP,Vec,void*),void *ctx)
    2360: {
    2362:   DM             dm;

    2366:   KSPGetDM(ksp,&dm);
    2367:   DMKSPSetComputeRHS(dm,func,ctx);
    2368:   return(0);
    2369: }

    2371: /*@C
    2372:    KSPSetComputeInitialGuess - set routine to compute the initial guess of the linear system

    2374:    Logically Collective

    2376:    Input Arguments:
    2377: +  ksp - the KSP context
    2378: .  func - function to compute the initial guess
    2379: -  ctx - optional context

    2381:    Calling sequence of func:
    2382: $  func(KSP ksp,Vec x,void *ctx)

    2384: +  ksp - the KSP context
    2385: .  x - solution vector
    2386: -  ctx - optional user-provided context

    2388:    Level: beginner

    2390: .seealso: KSPSolve(), KSPSetComputeRHS(), KSPSetComputeOperators(), DMKSPSetComputeInitialGuess()
    2391: @*/
    2392: PetscErrorCode KSPSetComputeInitialGuess(KSP ksp,PetscErrorCode (*func)(KSP,Vec,void*),void *ctx)
    2393: {
    2395:   DM             dm;

    2399:   KSPGetDM(ksp,&dm);
    2400:   DMKSPSetComputeInitialGuess(dm,func,ctx);
    2401:   return(0);
    2402: }