Date: 2026-03-01T05:24:55+00:00

Actual source code: precon.c

      1: /*
      2:     The PC (preconditioner) interface routines, callable by users.
      3: */
      4: #include <petsc/private/pcimpl.h>
      5: #include <petscdm.h>

      7: /* Logging support */
      8: PetscClassId  PC_CLASSID;
      9: PetscLogEvent PC_SetUp, PC_SetUpOnBlocks, PC_Apply, PC_MatApply, PC_ApplyCoarse, PC_ApplySymmetricLeft;
     10: PetscLogEvent PC_ApplySymmetricRight, PC_ModifySubMatrices, PC_ApplyOnBlocks, PC_ApplyTransposeOnBlocks;
     11: PetscInt      PetscMGLevelId;
     12: PetscLogStage PCMPIStage;

     14: PETSC_INTERN PetscErrorCode PCGetDefaultType_Private(PC pc, const char *type[])
     15: {
     16:   PetscMPIInt size;
     17:   PetscBool   hasopblock, hasopsolve, flg1, flg2, set, flg3, isnormal;

     19:   PetscFunctionBegin;
     20:   PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)pc), &size));
     21:   if (pc->pmat) {
     22:     PetscCall(MatHasOperation(pc->pmat, MATOP_GET_DIAGONAL_BLOCK, &hasopblock));
     23:     PetscCall(MatHasOperation(pc->pmat, MATOP_SOLVE, &hasopsolve));
     24:     if (size == 1) {
     25:       PetscCall(MatGetFactorAvailable(pc->pmat, "petsc", MAT_FACTOR_ICC, &flg1));
     26:       PetscCall(MatGetFactorAvailable(pc->pmat, "petsc", MAT_FACTOR_ILU, &flg2));
     27:       PetscCall(MatIsSymmetricKnown(pc->pmat, &set, &flg3));
     28:       PetscCall(PetscObjectTypeCompareAny((PetscObject)pc->pmat, &isnormal, MATNORMAL, MATNORMALHERMITIAN, NULL));
     29:       if (flg1 && (!flg2 || (set && flg3))) {
     30:         *type = PCICC;
     31:       } else if (flg2) {
     32:         *type = PCILU;
     33:       } else if (isnormal) {
     34:         *type = PCNONE;
     35:       } else if (hasopblock) { /* likely is a parallel matrix run on one processor */
     36:         *type = PCBJACOBI;
     37:       } else if (hasopsolve) {
     38:         *type = PCMAT;
     39:       } else {
     40:         *type = PCNONE;
     41:       }
     42:     } else {
     43:       if (hasopblock) {
     44:         *type = PCBJACOBI;
     45:       } else if (hasopsolve) {
     46:         *type = PCMAT;
     47:       } else {
     48:         *type = PCNONE;
     49:       }
     50:     }
     51:   } else *type = NULL;
     52:   PetscFunctionReturn(PETSC_SUCCESS);
     53: }

     55: /* do not log solves, setup and applications of preconditioners while constructing preconditioners; perhaps they should be logged separately from the regular solves */
     56: PETSC_EXTERN PetscLogEvent KSP_Solve, KSP_SetUp;

     58: static PetscErrorCode PCLogEventsDeactivatePush(void)
     59: {
     60:   PetscFunctionBegin;
     61:   PetscCall(KSPInitializePackage());
     62:   PetscCall(PetscLogEventDeactivatePush(KSP_Solve));
     63:   PetscCall(PetscLogEventDeactivatePush(KSP_SetUp));
     64:   PetscCall(PetscLogEventDeactivatePush(PC_Apply));
     65:   PetscCall(PetscLogEventDeactivatePush(PC_SetUp));
     66:   PetscCall(PetscLogEventDeactivatePush(PC_SetUpOnBlocks));
     67:   PetscFunctionReturn(PETSC_SUCCESS);
     68: }

     70: static PetscErrorCode PCLogEventsDeactivatePop(void)
     71: {
     72:   PetscFunctionBegin;
     73:   PetscCall(KSPInitializePackage());
     74:   PetscCall(PetscLogEventDeactivatePop(KSP_Solve));
     75:   PetscCall(PetscLogEventDeactivatePop(KSP_SetUp));
     76:   PetscCall(PetscLogEventDeactivatePop(PC_Apply));
     77:   PetscCall(PetscLogEventDeactivatePop(PC_SetUp));
     78:   PetscCall(PetscLogEventDeactivatePop(PC_SetUpOnBlocks));
     79:   PetscFunctionReturn(PETSC_SUCCESS);
     80: }

     82: /*@
     83:   PCReset - Resets a `PC` context to the state it was in before `PCSetUp()` was called, and removes any allocated `Vec` and `Mat` from its data structure

     85:   Collective

     87:   Input Parameter:
     88: . pc - the `PC` preconditioner context

     90:   Level: developer

     92:   Notes:
     93:   Any options set, including those set with `KSPSetFromOptions()` remain.

     95:   This allows a `PC` to be reused for a different sized linear system but using the same options that have been previously set in `pc`

     97: .seealso: [](ch_ksp), `PC`, `PCCreate()`, `PCSetUp()`
     98: @*/
     99: PetscErrorCode PCReset(PC pc)
    100: {
    101:   PetscFunctionBegin;
    103:   PetscTryTypeMethod(pc, reset);
    104:   PetscCall(VecDestroy(&pc->diagonalscaleright));
    105:   PetscCall(VecDestroy(&pc->diagonalscaleleft));
    106:   PetscCall(MatDestroy(&pc->pmat));
    107:   PetscCall(MatDestroy(&pc->mat));

    109:   pc->setupcalled = PETSC_FALSE;
    110:   PetscFunctionReturn(PETSC_SUCCESS);
    111: }

    113: /*@
    114:   PCDestroy - Destroys `PC` context that was created with `PCCreate()`.

    116:   Collective

    118:   Input Parameter:
    119: . pc - the `PC` preconditioner context

    121:   Level: developer

    123: .seealso: [](ch_ksp), `PC`, `PCCreate()`, `PCSetUp()`
    124: @*/
    125: PetscErrorCode PCDestroy(PC *pc)
    126: {
    127:   PetscFunctionBegin;
    128:   if (!*pc) PetscFunctionReturn(PETSC_SUCCESS);
    130:   if (--((PetscObject)*pc)->refct > 0) {
    131:     *pc = NULL;
    132:     PetscFunctionReturn(PETSC_SUCCESS);
    133:   }

    135:   PetscCall(PCReset(*pc));

    137:   /* if memory was published with SAWs then destroy it */
    138:   PetscCall(PetscObjectSAWsViewOff((PetscObject)*pc));
    139:   PetscTryTypeMethod(*pc, destroy);
    140:   PetscCall(DMDestroy(&(*pc)->dm));
    141:   PetscCall(PetscHeaderDestroy(pc));
    142:   PetscFunctionReturn(PETSC_SUCCESS);
    143: }

    145: /*@
    146:   PCGetDiagonalScale - Indicates if the preconditioner applies an additional left and right
    147:   scaling as needed by certain time-stepping codes.

    149:   Logically Collective

    151:   Input Parameter:
    152: . pc - the `PC` preconditioner context

    154:   Output Parameter:
    155: . flag - `PETSC_TRUE` if it applies the scaling

    157:   Level: developer

    159:   Note:
    160:   If this returns `PETSC_TRUE` then the system solved via the Krylov method is, for left and right preconditioning,

    162:   $$
    163:   \begin{align*}
    164:   D M A D^{-1} y = D M b  \\
    165:   D A M D^{-1} z = D b.
    166:   \end{align*}
    167:   $$

    169: .seealso: [](ch_ksp), `PC`, `PCCreate()`, `PCSetUp()`, `PCDiagonalScaleLeft()`, `PCDiagonalScaleRight()`, `PCSetDiagonalScale()`
    170: @*/
    171: PetscErrorCode PCGetDiagonalScale(PC pc, PetscBool *flag)
    172: {
    173:   PetscFunctionBegin;
    175:   PetscAssertPointer(flag, 2);
    176:   *flag = pc->diagonalscale;
    177:   PetscFunctionReturn(PETSC_SUCCESS);
    178: }

    180: /*@
    181:   PCSetDiagonalScale - Indicates the left scaling to use to apply an additional left and right
    182:   scaling as needed by certain time-stepping codes.

    184:   Logically Collective

    186:   Input Parameters:
    187: + pc - the `PC` preconditioner context
    188: - s  - scaling vector

    190:   Level: intermediate

    192:   Notes:
    193:   The system solved via the Krylov method is, for left and right preconditioning,
    194:   $$
    195:   \begin{align*}
    196:   D M A D^{-1} y = D M b \\
    197:   D A M D^{-1} z = D b.
    198:   \end{align*}
    199:   $$

    201:   `PCDiagonalScaleLeft()` scales a vector by $D$. `PCDiagonalScaleRight()` scales a vector by $D^{-1}$.

    203: .seealso: [](ch_ksp), `PCCreate()`, `PCSetUp()`, `PCDiagonalScaleLeft()`, `PCDiagonalScaleRight()`, `PCGetDiagonalScale()`
    204: @*/
    205: PetscErrorCode PCSetDiagonalScale(PC pc, Vec s)
    206: {
    207:   PetscFunctionBegin;
    210:   pc->diagonalscale = PETSC_TRUE;

    212:   PetscCall(PetscObjectReference((PetscObject)s));
    213:   PetscCall(VecDestroy(&pc->diagonalscaleleft));

    215:   pc->diagonalscaleleft = s;

    217:   PetscCall(VecDuplicate(s, &pc->diagonalscaleright));
    218:   PetscCall(VecCopy(s, pc->diagonalscaleright));
    219:   PetscCall(VecReciprocal(pc->diagonalscaleright));
    220:   PetscFunctionReturn(PETSC_SUCCESS);
    221: }

    223: /*@
    224:   PCDiagonalScaleLeft - Scales a vector by the left scaling as needed by certain time-stepping codes.

    226:   Logically Collective

    228:   Input Parameters:
    229: + pc  - the `PC` preconditioner context
    230: . in  - input vector
    231: - out - scaled vector (maybe the same as in)

    233:   Level: intermediate

    235:   Notes:
    236:   The system solved via the Krylov method is, for left and right preconditioning,

    238:   $$
    239:   \begin{align*}
    240:   D M A D^{-1} y = D M b  \\
    241:   D A M D^{-1} z = D b.
    242:   \end{align*}
    243:   $$

    245:   `PCDiagonalScaleLeft()` scales a vector by $D$. `PCDiagonalScaleRight()` scales a vector by $D^{-1}$.

    247:   If diagonal scaling is turned off and `in` is not `out` then `in` is copied to `out`

    249: .seealso: [](ch_ksp), `PCCreate()`, `PCSetUp()`, `PCSetDiagonalScale()`, `PCDiagonalScaleRight()`, `MatDiagonalScale()`
    250: @*/
    251: PetscErrorCode PCDiagonalScaleLeft(PC pc, Vec in, Vec out)
    252: {
    253:   PetscFunctionBegin;
    257:   if (pc->diagonalscale) {
    258:     PetscCall(VecPointwiseMult(out, pc->diagonalscaleleft, in));
    259:   } else if (in != out) {
    260:     PetscCall(VecCopy(in, out));
    261:   }
    262:   PetscFunctionReturn(PETSC_SUCCESS);
    263: }

    265: /*@
    266:   PCDiagonalScaleRight - Scales a vector by the right scaling as needed by certain time-stepping codes.

    268:   Logically Collective

    270:   Input Parameters:
    271: + pc  - the `PC` preconditioner context
    272: . in  - input vector
    273: - out - scaled vector (maybe the same as in)

    275:   Level: intermediate

    277:   Notes:
    278:   The system solved via the Krylov method is, for left and right preconditioning,

    280:   $$
    281:   \begin{align*}
    282:   D M A D^{-1} y = D M b  \\
    283:   D A M D^{-1} z = D b.
    284:   \end{align*}
    285:   $$

    287:   `PCDiagonalScaleLeft()` scales a vector by $D$. `PCDiagonalScaleRight()` scales a vector by $D^{-1}$.

    289:   If diagonal scaling is turned off and `in` is not `out` then `in` is copied to `out`

    291: .seealso: [](ch_ksp), `PCCreate()`, `PCSetUp()`, `PCDiagonalScaleLeft()`, `PCSetDiagonalScale()`, `MatDiagonalScale()`
    292: @*/
    293: PetscErrorCode PCDiagonalScaleRight(PC pc, Vec in, Vec out)
    294: {
    295:   PetscFunctionBegin;
    299:   if (pc->diagonalscale) {
    300:     PetscCall(VecPointwiseMult(out, pc->diagonalscaleright, in));
    301:   } else if (in != out) {
    302:     PetscCall(VecCopy(in, out));
    303:   }
    304:   PetscFunctionReturn(PETSC_SUCCESS);
    305: }

    307: /*@
    308:   PCSetUseAmat - Sets a flag to indicate that when the preconditioner needs to apply (part of) the
    309:   operator during the preconditioning process it applies the Amat provided to `TSSetRHSJacobian()`,
    310:   `TSSetIJacobian()`, `SNESSetJacobian()`, `KSPSetOperators()` or `PCSetOperators()` not the Pmat.

    312:   Logically Collective

    314:   Input Parameters:
    315: + pc  - the `PC` preconditioner context
    316: - flg - `PETSC_TRUE` to use the Amat, `PETSC_FALSE` to use the Pmat (default is false)

    318:   Options Database Key:
    319: . -pc_use_amat <true,false> - use the amat argument to `KSPSetOperators()` or `PCSetOperators()` to apply the operator

    321:   Level: intermediate

    323:   Note:
    324:   For the common case in which the linear system matrix and the matrix used to construct the
    325:   preconditioner are identical, this routine has no affect.

    327: .seealso: [](ch_ksp), `PC`, `PCGetUseAmat()`, `PCBJACOBI`, `PCMG`, `PCFIELDSPLIT`, `PCCOMPOSITE`,
    328:           `KSPSetOperators()`, `PCSetOperators()`
    329: @*/
    330: PetscErrorCode PCSetUseAmat(PC pc, PetscBool flg)
    331: {
    332:   PetscFunctionBegin;
    334:   pc->useAmat = flg;
    335:   PetscFunctionReturn(PETSC_SUCCESS);
    336: }

    338: /*@
    339:   PCSetErrorIfFailure - Causes `PC` to generate an error if a floating point exception, for example a zero pivot, is detected.

    341:   Logically Collective

    343:   Input Parameters:
    344: + pc  - iterative context obtained from `PCCreate()`
    345: - flg - `PETSC_TRUE` indicates you want the error generated

    347:   Level: advanced

    349:   Notes:
    350:   Normally PETSc continues if a linear solver fails due to a failed setup of a preconditioner, you can call `KSPGetConvergedReason()` after a `KSPSolve()`
    351:   to determine if it has converged or failed. Or use -ksp_error_if_not_converged to cause the program to terminate as soon as lack of convergence is
    352:   detected.

    354:   This is propagated into `KSP`s used by this `PC`, which then propagate it into `PC`s used by those `KSP`s

    356: .seealso: [](ch_ksp), `PC`, `KSPSetErrorIfNotConverged()`, `PCGetInitialGuessNonzero()`, `PCSetInitialGuessKnoll()`, `PCGetInitialGuessKnoll()`
    357: @*/
    358: PetscErrorCode PCSetErrorIfFailure(PC pc, PetscBool flg)
    359: {
    360:   PetscFunctionBegin;
    363:   pc->erroriffailure = flg;
    364:   PetscFunctionReturn(PETSC_SUCCESS);
    365: }

    367: /*@
    368:   PCGetUseAmat - Gets a flag to indicate that when the preconditioner needs to apply (part of) the
    369:   operator during the preconditioning process it applies the Amat provided to `TSSetRHSJacobian()`,
    370:   `TSSetIJacobian()`, `SNESSetJacobian()`, `KSPSetOperators()` or `PCSetOperators()` not the Pmat.

    372:   Logically Collective

    374:   Input Parameter:
    375: . pc - the `PC` preconditioner context

    377:   Output Parameter:
    378: . flg - `PETSC_TRUE` to use the Amat, `PETSC_FALSE` to use the Pmat (default is false)

    380:   Level: intermediate

    382:   Note:
    383:   For the common case in which the linear system matrix and the matrix used to construct the
    384:   preconditioner are identical, this routine is does nothing.

    386: .seealso: [](ch_ksp), `PC`, `PCSetUseAmat()`, `PCBJACOBI`, `PCMG`, `PCFIELDSPLIT`, `PCCOMPOSITE`
    387: @*/
    388: PetscErrorCode PCGetUseAmat(PC pc, PetscBool *flg)
    389: {
    390:   PetscFunctionBegin;
    392:   *flg = pc->useAmat;
    393:   PetscFunctionReturn(PETSC_SUCCESS);
    394: }

    396: /*@
    397:   PCSetKSPNestLevel - sets the amount of nesting the `KSP` that contains this `PC` has

    399:   Collective

    401:   Input Parameters:
    402: + pc    - the `PC`
    403: - level - the nest level

    405:   Level: developer

    407: .seealso: [](ch_ksp), `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSP`, `KSPGMRES`, `KSPType`, `KSPGetNestLevel()`, `PCGetKSPNestLevel()`, `KSPSetNestLevel()`
    408: @*/
    409: PetscErrorCode PCSetKSPNestLevel(PC pc, PetscInt level)
    410: {
    411:   PetscFunctionBegin;
    414:   pc->kspnestlevel = level;
    415:   PetscFunctionReturn(PETSC_SUCCESS);
    416: }

    418: /*@
    419:   PCGetKSPNestLevel - gets the amount of nesting the `KSP` that contains this `PC` has

    421:   Not Collective

    423:   Input Parameter:
    424: . pc - the `PC`

    426:   Output Parameter:
    427: . level - the nest level

    429:   Level: developer

    431: .seealso: [](ch_ksp), `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSP`, `KSPGMRES`, `KSPType`, `KSPSetNestLevel()`, `PCSetKSPNestLevel()`, `KSPGetNestLevel()`
    432: @*/
    433: PetscErrorCode PCGetKSPNestLevel(PC pc, PetscInt *level)
    434: {
    435:   PetscFunctionBegin;
    437:   PetscAssertPointer(level, 2);
    438:   *level = pc->kspnestlevel;
    439:   PetscFunctionReturn(PETSC_SUCCESS);
    440: }

    442: /*@
    443:   PCCreate - Creates a preconditioner context, `PC`

    445:   Collective

    447:   Input Parameter:
    448: . comm - MPI communicator

    450:   Output Parameter:
    451: . newpc - location to put the `PC` preconditioner context

    453:   Level: developer

    455:   Notes:
    456:   This is rarely called directly by users since `KSP` manages the `PC` objects it uses. Use `KSPGetPC()` to access the `PC` used by a `KSP`.

    458:   Use `PCSetType()` or `PCSetFromOptions()` with the option `-pc_type pctype` to set the `PCType` for this `PC`

    460:   The default preconditioner type `PCType` for sparse matrices is `PCILU` or `PCICC` with 0 fill on one process and block Jacobi (`PCBJACOBI`) with `PCILU` or `PCICC`
    461:   in parallel. For dense matrices it is always `PCNONE`.

    463: .seealso: [](ch_ksp), `PC`, `PCType`, `PCSetType`, `PCSetUp()`, `PCApply()`, `PCDestroy()`, `KSP`, `KSPGetPC()`
    464: @*/
    465: PetscErrorCode PCCreate(MPI_Comm comm, PC *newpc)
    466: {
    467:   PC pc;

    469:   PetscFunctionBegin;
    470:   PetscAssertPointer(newpc, 2);
    471:   PetscCall(PCInitializePackage());

    473:   PetscCall(PetscHeaderCreate(pc, PC_CLASSID, "PC", "Preconditioner", "PC", comm, PCDestroy, PCView));
    474:   pc->mat                  = NULL;
    475:   pc->pmat                 = NULL;
    476:   pc->setupcalled          = PETSC_FALSE;
    477:   pc->setfromoptionscalled = 0;
    478:   pc->data                 = NULL;
    479:   pc->diagonalscale        = PETSC_FALSE;
    480:   pc->diagonalscaleleft    = NULL;
    481:   pc->diagonalscaleright   = NULL;

    483:   pc->modifysubmatrices  = NULL;
    484:   pc->modifysubmatricesP = NULL;

    486:   *newpc = pc;
    487:   PetscFunctionReturn(PETSC_SUCCESS);
    488: }

    490: /*@
    491:   PCApply - Applies the preconditioner to a vector.

    493:   Collective

    495:   Input Parameters:
    496: + pc - the `PC` preconditioner context
    497: - x  - input vector

    499:   Output Parameter:
    500: . y - output vector

    502:   Level: developer

    504: .seealso: [](ch_ksp), `PC`, `PCApplyTranspose()`, `PCApplyBAorAB()`
    505: @*/
    506: PetscErrorCode PCApply(PC pc, Vec x, Vec y)
    507: {
    508:   PetscInt m, n, mv, nv;

    510:   PetscFunctionBegin;
    514:   PetscCheck(x != y, PetscObjectComm((PetscObject)pc), PETSC_ERR_ARG_IDN, "x and y must be different vectors");
    515:   if (pc->erroriffailure) PetscCall(VecValidValues_Internal(x, 2, PETSC_TRUE));
    516:   /* use pmat to check vector sizes since for KSPLSQR the pmat may be of a different size than mat */
    517:   PetscCall(MatGetLocalSize(pc->pmat, &m, &n));
    518:   PetscCall(VecGetLocalSize(x, &mv));
    519:   PetscCall(VecGetLocalSize(y, &nv));
    520:   /* check pmat * y = x is feasible */
    521:   PetscCheck(mv == m, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Preconditioner number of local rows %" PetscInt_FMT " does not equal input vector size %" PetscInt_FMT, m, mv);
    522:   PetscCheck(nv == n, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Preconditioner number of local columns %" PetscInt_FMT " does not equal output vector size %" PetscInt_FMT, n, nv);
    523:   PetscCall(VecSetErrorIfLocked(y, 3));

    525:   PetscCall(PCSetUp(pc));
    526:   PetscCall(VecLockReadPush(x));
    527:   PetscCall(PetscLogEventBegin(PC_Apply, pc, x, y, 0));
    528:   PetscUseTypeMethod(pc, apply, x, y);
    529:   PetscCall(PetscLogEventEnd(PC_Apply, pc, x, y, 0));
    530:   if (pc->erroriffailure) PetscCall(VecValidValues_Internal(y, 3, PETSC_FALSE));
    531:   PetscCall(VecLockReadPop(x));
    532:   PetscFunctionReturn(PETSC_SUCCESS);
    533: }

    535: static PetscErrorCode PCMatApplyTranspose_Private(PC pc, Mat X, Mat Y, PetscBool transpose)
    536: {
    537:   Mat       A;
    538:   Vec       cy, cx;
    539:   PetscInt  m1, M1, m2, M2, n1, N1, n2, N2, m3, M3, n3, N3;
    540:   PetscBool match;

    542:   PetscFunctionBegin;
    546:   PetscCheckSameComm(pc, 1, X, 2);
    547:   PetscCheckSameComm(pc, 1, Y, 3);
    548:   PetscCheck(Y != X, PetscObjectComm((PetscObject)pc), PETSC_ERR_ARG_IDN, "Y and X must be different matrices");
    549:   PetscCall(PCGetOperators(pc, NULL, &A));
    550:   PetscCall(MatGetLocalSize(A, &m3, &n3));
    551:   PetscCall(MatGetLocalSize(X, &m2, &n2));
    552:   PetscCall(MatGetLocalSize(Y, &m1, &n1));
    553:   PetscCall(MatGetSize(A, &M3, &N3));
    554:   PetscCall(MatGetSize(X, &M2, &N2));
    555:   PetscCall(MatGetSize(Y, &M1, &N1));
    556:   PetscCheck(n1 == n2 && N1 == N2, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Incompatible number of columns between block of input vectors (n,N) = (%" PetscInt_FMT ",%" PetscInt_FMT ") and block of output vectors (n,N) = (%" PetscInt_FMT ",%" PetscInt_FMT ")", n2, N2, n1, N1);
    557:   PetscCheck(m2 == m3 && M2 == M3, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Incompatible layout between block of input vectors (m,M) = (%" PetscInt_FMT ",%" PetscInt_FMT ") and Pmat (m,M)x(n,N) = (%" PetscInt_FMT ",%" PetscInt_FMT ")x(%" PetscInt_FMT ",%" PetscInt_FMT ")", m2, M2, m3, M3, n3, N3);
    558:   PetscCheck(m1 == n3 && M1 == N3, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Incompatible layout between block of output vectors (m,M) = (%" PetscInt_FMT ",%" PetscInt_FMT ") and Pmat (m,M)x(n,N) = (%" PetscInt_FMT ",%" PetscInt_FMT ")x(%" PetscInt_FMT ",%" PetscInt_FMT ")", m1, M1, m3, M3, n3, N3);
    559:   PetscCall(PetscObjectBaseTypeCompareAny((PetscObject)Y, &match, MATSEQDENSE, MATMPIDENSE, ""));
    560:   PetscCheck(match, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Provided block of output vectors not stored in a dense Mat");
    561:   PetscCall(PetscObjectBaseTypeCompareAny((PetscObject)X, &match, MATSEQDENSE, MATMPIDENSE, ""));
    562:   PetscCheck(match, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Provided block of input vectors not stored in a dense Mat");
    563:   PetscCall(PCSetUp(pc));
    564:   if (!transpose && pc->ops->matapply) {
    565:     PetscCall(PetscLogEventBegin(PC_MatApply, pc, X, Y, 0));
    566:     PetscUseTypeMethod(pc, matapply, X, Y);
    567:     PetscCall(PetscLogEventEnd(PC_MatApply, pc, X, Y, 0));
    568:   } else if (transpose && pc->ops->matapplytranspose) {
    569:     PetscCall(PetscLogEventBegin(PC_MatApply, pc, X, Y, 0));
    570:     PetscUseTypeMethod(pc, matapplytranspose, X, Y);
    571:     PetscCall(PetscLogEventEnd(PC_MatApply, pc, X, Y, 0));
    572:   } else {
    573:     PetscCall(PetscInfo(pc, "PC type %s applying column by column\n", ((PetscObject)pc)->type_name));
    574:     for (n1 = 0; n1 < N1; ++n1) {
    575:       PetscCall(MatDenseGetColumnVecRead(X, n1, &cx));
    576:       PetscCall(MatDenseGetColumnVecWrite(Y, n1, &cy));
    577:       if (!transpose) PetscCall(PCApply(pc, cx, cy));
    578:       else PetscCall(PCApplyTranspose(pc, cx, cy));
    579:       PetscCall(MatDenseRestoreColumnVecWrite(Y, n1, &cy));
    580:       PetscCall(MatDenseRestoreColumnVecRead(X, n1, &cx));
    581:     }
    582:   }
    583:   PetscFunctionReturn(PETSC_SUCCESS);
    584: }

    586: /*@
    587:   PCMatApply - Applies the preconditioner to multiple vectors stored as a `MATDENSE`. Like `PCApply()`, `Y` and `X` must be different matrices.

    589:   Collective

    591:   Input Parameters:
    592: + pc - the `PC` preconditioner context
    593: - X  - block of input vectors

    595:   Output Parameter:
    596: . Y - block of output vectors

    598:   Level: developer

    600: .seealso: [](ch_ksp), `PC`, `PCApply()`, `KSPMatSolve()`
    601: @*/
    602: PetscErrorCode PCMatApply(PC pc, Mat X, Mat Y)
    603: {
    604:   PetscFunctionBegin;
    605:   PetscCall(PCMatApplyTranspose_Private(pc, X, Y, PETSC_FALSE));
    606:   PetscFunctionReturn(PETSC_SUCCESS);
    607: }

    609: /*@
    610:   PCMatApplyTranspose - Applies the transpose of preconditioner to multiple vectors stored as a `MATDENSE`. Like `PCApplyTranspose()`, `Y` and `X` must be different matrices.

    612:   Collective

    614:   Input Parameters:
    615: + pc - the `PC` preconditioner context
    616: - X  - block of input vectors

    618:   Output Parameter:
    619: . Y - block of output vectors

    621:   Level: developer

    623: .seealso: [](ch_ksp), `PC`, `PCApplyTranspose()`, `KSPMatSolveTranspose()`
    624: @*/
    625: PetscErrorCode PCMatApplyTranspose(PC pc, Mat X, Mat Y)
    626: {
    627:   PetscFunctionBegin;
    628:   PetscCall(PCMatApplyTranspose_Private(pc, X, Y, PETSC_TRUE));
    629:   PetscFunctionReturn(PETSC_SUCCESS);
    630: }

    632: /*@
    633:   PCApplySymmetricLeft - Applies the left part of a symmetric preconditioner to a vector.

    635:   Collective

    637:   Input Parameters:
    638: + pc - the `PC` preconditioner context
    639: - x  - input vector

    641:   Output Parameter:
    642: . y - output vector

    644:   Level: developer

    646:   Note:
    647:   Currently, this routine is implemented only for `PCICC` and `PCJACOBI` preconditioners.

    649: .seealso: [](ch_ksp), `PC`, `PCApply()`, `PCApplySymmetricRight()`
    650: @*/
    651: PetscErrorCode PCApplySymmetricLeft(PC pc, Vec x, Vec y)
    652: {
    653:   PetscFunctionBegin;
    657:   PetscCheck(x != y, PetscObjectComm((PetscObject)pc), PETSC_ERR_ARG_IDN, "x and y must be different vectors");
    658:   if (pc->erroriffailure) PetscCall(VecValidValues_Internal(x, 2, PETSC_TRUE));
    659:   PetscCall(PCSetUp(pc));
    660:   PetscCall(VecLockReadPush(x));
    661:   PetscCall(PetscLogEventBegin(PC_ApplySymmetricLeft, pc, x, y, 0));
    662:   PetscUseTypeMethod(pc, applysymmetricleft, x, y);
    663:   PetscCall(PetscLogEventEnd(PC_ApplySymmetricLeft, pc, x, y, 0));
    664:   PetscCall(VecLockReadPop(x));
    665:   if (pc->erroriffailure) PetscCall(VecValidValues_Internal(y, 3, PETSC_FALSE));
    666:   PetscFunctionReturn(PETSC_SUCCESS);
    667: }

    669: /*@
    670:   PCApplySymmetricRight - Applies the right part of a symmetric preconditioner to a vector.

    672:   Collective

    674:   Input Parameters:
    675: + pc - the `PC` preconditioner context
    676: - x  - input vector

    678:   Output Parameter:
    679: . y - output vector

    681:   Level: developer

    683:   Note:
    684:   Currently, this routine is implemented only for `PCICC` and `PCJACOBI` preconditioners.

    686: .seealso: [](ch_ksp), `PC`, `PCApply()`, `PCApplySymmetricLeft()`
    687: @*/
    688: PetscErrorCode PCApplySymmetricRight(PC pc, Vec x, Vec y)
    689: {
    690:   PetscFunctionBegin;
    694:   PetscCheck(x != y, PetscObjectComm((PetscObject)pc), PETSC_ERR_ARG_IDN, "x and y must be different vectors");
    695:   if (pc->erroriffailure) PetscCall(VecValidValues_Internal(x, 2, PETSC_TRUE));
    696:   PetscCall(PCSetUp(pc));
    697:   PetscCall(VecLockReadPush(x));
    698:   PetscCall(PetscLogEventBegin(PC_ApplySymmetricRight, pc, x, y, 0));
    699:   PetscUseTypeMethod(pc, applysymmetricright, x, y);
    700:   PetscCall(PetscLogEventEnd(PC_ApplySymmetricRight, pc, x, y, 0));
    701:   PetscCall(VecLockReadPop(x));
    702:   if (pc->erroriffailure) PetscCall(VecValidValues_Internal(y, 3, PETSC_FALSE));
    703:   PetscFunctionReturn(PETSC_SUCCESS);
    704: }

    706: /*@
    707:   PCApplyTranspose - Applies the transpose of preconditioner to a vector.

    709:   Collective

    711:   Input Parameters:
    712: + pc - the `PC` preconditioner context
    713: - x  - input vector

    715:   Output Parameter:
    716: . y - output vector

    718:   Level: developer

    720:   Note:
    721:   For complex numbers this applies the non-Hermitian transpose.

    723:   Developer Note:
    724:   We need to implement a `PCApplyHermitianTranspose()`

    726: .seealso: [](ch_ksp), `PC`, `PCApply()`, `PCApplyBAorAB()`, `PCApplyBAorABTranspose()`, `PCApplyTransposeExists()`
    727: @*/
    728: PetscErrorCode PCApplyTranspose(PC pc, Vec x, Vec y)
    729: {
    730:   PetscFunctionBegin;
    734:   PetscCheck(x != y, PetscObjectComm((PetscObject)pc), PETSC_ERR_ARG_IDN, "x and y must be different vectors");
    735:   if (pc->erroriffailure) PetscCall(VecValidValues_Internal(x, 2, PETSC_TRUE));
    736:   PetscCall(PCSetUp(pc));
    737:   PetscCall(VecLockReadPush(x));
    738:   PetscCall(PetscLogEventBegin(PC_Apply, pc, x, y, 0));
    739:   PetscUseTypeMethod(pc, applytranspose, x, y);
    740:   PetscCall(PetscLogEventEnd(PC_Apply, pc, x, y, 0));
    741:   PetscCall(VecLockReadPop(x));
    742:   if (pc->erroriffailure) PetscCall(VecValidValues_Internal(y, 3, PETSC_FALSE));
    743:   PetscFunctionReturn(PETSC_SUCCESS);
    744: }

    746: /*@
    747:   PCApplyTransposeExists - Test whether the preconditioner has a transpose apply operation

    749:   Collective

    751:   Input Parameter:
    752: . pc - the `PC` preconditioner context

    754:   Output Parameter:
    755: . flg - `PETSC_TRUE` if a transpose operation is defined

    757:   Level: developer

    759: .seealso: [](ch_ksp), `PC`, `PCApplyTranspose()`
    760: @*/
    761: PetscErrorCode PCApplyTransposeExists(PC pc, PetscBool *flg)
    762: {
    763:   PetscFunctionBegin;
    765:   PetscAssertPointer(flg, 2);
    766:   if (pc->ops->applytranspose) *flg = PETSC_TRUE;
    767:   else *flg = PETSC_FALSE;
    768:   PetscFunctionReturn(PETSC_SUCCESS);
    769: }

    771: /*@
    772:   PCApplyBAorAB - Applies the preconditioner and operator to a vector. $y = B*A*x $ or $ y = A*B*x$.

    774:   Collective

    776:   Input Parameters:
    777: + pc   - the `PC` preconditioner context
    778: . side - indicates the preconditioner side, one of `PC_LEFT`, `PC_RIGHT`, or `PC_SYMMETRIC`
    779: . x    - input vector
    780: - work - work vector

    782:   Output Parameter:
    783: . y - output vector

    785:   Level: developer

    787:   Note:
    788:   If the `PC` has had `PCSetDiagonalScale()` set then $ D M A D^{-1} $ for left preconditioning or $ D A M D^{-1} $ is actually applied.
    789:   The specific `KSPSolve()` method must also be written to handle the post-solve "correction" for the diagonal scaling.

    791: .seealso: [](ch_ksp), `PC`, `PCApply()`, `PCApplyTranspose()`, `PCApplyBAorABTranspose()`
    792: @*/
    793: PetscErrorCode PCApplyBAorAB(PC pc, PCSide side, Vec x, Vec y, Vec work)
    794: {
    795:   PetscFunctionBegin;
    801:   PetscCheckSameComm(pc, 1, x, 3);
    802:   PetscCheckSameComm(pc, 1, y, 4);
    803:   PetscCheckSameComm(pc, 1, work, 5);
    804:   PetscCheck(x != y, PetscObjectComm((PetscObject)pc), PETSC_ERR_ARG_IDN, "x and y must be different vectors");
    805:   PetscCheck(side == PC_LEFT || side == PC_SYMMETRIC || side == PC_RIGHT, PetscObjectComm((PetscObject)pc), PETSC_ERR_ARG_OUTOFRANGE, "Side must be right, left, or symmetric");
    806:   PetscCheck(!pc->diagonalscale || side != PC_SYMMETRIC, PetscObjectComm((PetscObject)pc), PETSC_ERR_SUP, "Cannot include diagonal scaling with symmetric preconditioner application");
    807:   if (pc->erroriffailure) PetscCall(VecValidValues_Internal(x, 3, PETSC_TRUE));

    809:   PetscCall(PCSetUp(pc));
    810:   if (pc->diagonalscale) {
    811:     if (pc->ops->applyBA) {
    812:       Vec work2; /* this is expensive, but to fix requires a second work vector argument to PCApplyBAorAB() */
    813:       PetscCall(VecDuplicate(x, &work2));
    814:       PetscCall(PCDiagonalScaleRight(pc, x, work2));
    815:       PetscUseTypeMethod(pc, applyBA, side, work2, y, work);
    816:       PetscCall(PCDiagonalScaleLeft(pc, y, y));
    817:       PetscCall(VecDestroy(&work2));
    818:     } else if (side == PC_RIGHT) {
    819:       PetscCall(PCDiagonalScaleRight(pc, x, y));
    820:       PetscCall(PCApply(pc, y, work));
    821:       PetscCall(MatMult(pc->mat, work, y));
    822:       PetscCall(PCDiagonalScaleLeft(pc, y, y));
    823:     } else if (side == PC_LEFT) {
    824:       PetscCall(PCDiagonalScaleRight(pc, x, y));
    825:       PetscCall(MatMult(pc->mat, y, work));
    826:       PetscCall(PCApply(pc, work, y));
    827:       PetscCall(PCDiagonalScaleLeft(pc, y, y));
    828:     } else PetscCheck(side != PC_SYMMETRIC, PetscObjectComm((PetscObject)pc), PETSC_ERR_SUP, "Cannot provide diagonal scaling with symmetric application of preconditioner");
    829:   } else {
    830:     if (pc->ops->applyBA) {
    831:       PetscUseTypeMethod(pc, applyBA, side, x, y, work);
    832:     } else if (side == PC_RIGHT) {
    833:       PetscCall(PCApply(pc, x, work));
    834:       PetscCall(MatMult(pc->mat, work, y));
    835:     } else if (side == PC_LEFT) {
    836:       PetscCall(MatMult(pc->mat, x, work));
    837:       PetscCall(PCApply(pc, work, y));
    838:     } else if (side == PC_SYMMETRIC) {
    839:       /* There's an extra copy here; maybe should provide 2 work vectors instead? */
    840:       PetscCall(PCApplySymmetricRight(pc, x, work));
    841:       PetscCall(MatMult(pc->mat, work, y));
    842:       PetscCall(VecCopy(y, work));
    843:       PetscCall(PCApplySymmetricLeft(pc, work, y));
    844:     }
    845:   }
    846:   if (pc->erroriffailure) PetscCall(VecValidValues_Internal(y, 4, PETSC_FALSE));
    847:   PetscFunctionReturn(PETSC_SUCCESS);
    848: }

    850: /*@
    851:   PCApplyBAorABTranspose - Applies the transpose of the preconditioner
    852:   and operator to a vector. That is, applies $B^T * A^T$ with left preconditioning,
    853:   NOT $(B*A)^T = A^T*B^T$.

    855:   Collective

    857:   Input Parameters:
    858: + pc   - the `PC` preconditioner context
    859: . side - indicates the preconditioner side, one of `PC_LEFT`, `PC_RIGHT`, or `PC_SYMMETRIC`
    860: . x    - input vector
    861: - work - work vector

    863:   Output Parameter:
    864: . y - output vector

    866:   Level: developer

    868:   Note:
    869:   This routine is used internally so that the same Krylov code can be used to solve $A x = b$ and $A^T x = b$, with a preconditioner
    870:   defined by $B^T$. This is why this has the funny form that it computes $B^T * A^T$

    872: .seealso: [](ch_ksp), `PC`, `PCApply()`, `PCApplyTranspose()`, `PCApplyBAorAB()`
    873: @*/
    874: PetscErrorCode PCApplyBAorABTranspose(PC pc, PCSide side, Vec x, Vec y, Vec work)
    875: {
    876:   PetscFunctionBegin;
    881:   PetscCheck(x != y, PetscObjectComm((PetscObject)pc), PETSC_ERR_ARG_IDN, "x and y must be different vectors");
    882:   if (pc->erroriffailure) PetscCall(VecValidValues_Internal(x, 3, PETSC_TRUE));
    883:   if (pc->ops->applyBAtranspose) {
    884:     PetscUseTypeMethod(pc, applyBAtranspose, side, x, y, work);
    885:     if (pc->erroriffailure) PetscCall(VecValidValues_Internal(y, 4, PETSC_FALSE));
    886:     PetscFunctionReturn(PETSC_SUCCESS);
    887:   }
    888:   PetscCheck(side == PC_LEFT || side == PC_RIGHT, PetscObjectComm((PetscObject)pc), PETSC_ERR_ARG_OUTOFRANGE, "Side must be right or left");

    890:   PetscCall(PCSetUp(pc));
    891:   if (side == PC_RIGHT) {
    892:     PetscCall(PCApplyTranspose(pc, x, work));
    893:     PetscCall(MatMultTranspose(pc->mat, work, y));
    894:   } else if (side == PC_LEFT) {
    895:     PetscCall(MatMultTranspose(pc->mat, x, work));
    896:     PetscCall(PCApplyTranspose(pc, work, y));
    897:   }
    898:   /* add support for PC_SYMMETRIC */
    899:   if (pc->erroriffailure) PetscCall(VecValidValues_Internal(y, 4, PETSC_FALSE));
    900:   PetscFunctionReturn(PETSC_SUCCESS);
    901: }

    903: /*@
    904:   PCApplyRichardsonExists - Determines whether a particular preconditioner has a
    905:   built-in fast application of Richardson's method.

    907:   Not Collective

    909:   Input Parameter:
    910: . pc - the preconditioner

    912:   Output Parameter:
    913: . exists - `PETSC_TRUE` or `PETSC_FALSE`

    915:   Level: developer

    917: .seealso: [](ch_ksp), `PC`, `KSPRICHARDSON`, `PCApplyRichardson()`
    918: @*/
    919: PetscErrorCode PCApplyRichardsonExists(PC pc, PetscBool *exists)
    920: {
    921:   PetscFunctionBegin;
    923:   PetscAssertPointer(exists, 2);
    924:   if (pc->ops->applyrichardson) *exists = PETSC_TRUE;
    925:   else *exists = PETSC_FALSE;
    926:   PetscFunctionReturn(PETSC_SUCCESS);
    927: }

    929: /*@
    930:   PCApplyRichardson - Applies several steps of Richardson iteration with
    931:   the particular preconditioner. This routine is usually used by the
    932:   Krylov solvers and not the application code directly.

    934:   Collective

    936:   Input Parameters:
    937: + pc        - the `PC` preconditioner context
    938: . b         - the right-hand side
    939: . w         - one work vector
    940: . rtol      - relative decrease in residual norm convergence criteria
    941: . abstol    - absolute residual norm convergence criteria
    942: . dtol      - divergence residual norm increase criteria
    943: . its       - the number of iterations to apply.
    944: - guesszero - if the input x contains nonzero initial guess

    946:   Output Parameters:
    947: + outits - number of iterations actually used (for SOR this always equals its)
    948: . reason - the reason the apply terminated
    949: - y      - the solution (also contains initial guess if guesszero is `PETSC_FALSE`

    951:   Level: developer

    953:   Notes:
    954:   Most preconditioners do not support this function. Use the command
    955:   `PCApplyRichardsonExists()` to determine if one does.

    957:   Except for the `PCMG` this routine ignores the convergence tolerances
    958:   and always runs for the number of iterations

    960: .seealso: [](ch_ksp), `PC`, `PCApplyRichardsonExists()`
    961: @*/
    962: PetscErrorCode PCApplyRichardson(PC pc, Vec b, Vec y, Vec w, PetscReal rtol, PetscReal abstol, PetscReal dtol, PetscInt its, PetscBool guesszero, PetscInt *outits, PCRichardsonConvergedReason *reason)
    963: {
    964:   PetscFunctionBegin;
    969:   PetscCheck(b != y, PetscObjectComm((PetscObject)pc), PETSC_ERR_ARG_IDN, "b and y must be different vectors");
    970:   PetscCall(PCSetUp(pc));
    971:   PetscUseTypeMethod(pc, applyrichardson, b, y, w, rtol, abstol, dtol, its, guesszero, outits, reason);
    972:   PetscFunctionReturn(PETSC_SUCCESS);
    973: }

    975: /*@
    976:   PCSetFailedReason - Sets the reason a `PCSetUp()` failed or `PC_NOERROR` if it did not fail

    978:   Logically Collective

    980:   Input Parameters:
    981: + pc     - the `PC` preconditioner context
    982: - reason - the reason it failed

    984:   Level: advanced

    986: .seealso: [](ch_ksp), `PC`, `PCCreate()`, `PCApply()`, `PCDestroy()`, `PCFailedReason`
    987: @*/
    988: PetscErrorCode PCSetFailedReason(PC pc, PCFailedReason reason)
    989: {
    990:   PetscFunctionBegin;
    992:   pc->failedreason = reason;
    993:   PetscFunctionReturn(PETSC_SUCCESS);
    994: }

    996: /*@
    997:   PCGetFailedReason - Gets the reason a `PCSetUp()` failed or `PC_NOERROR` if it did not fail

    999:   Not Collective

    1001:   Input Parameter:
    1002: . pc - the `PC` preconditioner context

    1004:   Output Parameter:
    1005: . reason - the reason it failed

    1007:   Level: advanced

    1009:   Note:
    1010:   After a call to `KSPCheckDot()` or  `KSPCheckNorm()` inside a `KSPSolve()` or a call to `PCReduceFailedReason()`
    1011:   this is the maximum reason over all MPI processes in the `PC` communicator and hence logically collective.
    1012:   Otherwise it returns the local value.

    1014: .seealso: [](ch_ksp), `PC`, `PCCreate()`, `PCApply()`, `PCDestroy()`, `PCSetFailedReason()`, `PCFailedReason`
    1015: @*/
    1016: PetscErrorCode PCGetFailedReason(PC pc, PCFailedReason *reason)
    1017: {
    1018:   PetscFunctionBegin;
    1020:   *reason = pc->failedreason;
    1021:   PetscFunctionReturn(PETSC_SUCCESS);
    1022: }

    1024: /*@
    1025:   PCReduceFailedReason - Reduce the failed reason among the MPI processes that share the `PC`

    1027:   Collective

    1029:   Input Parameter:
    1030: . pc - the `PC` preconditioner context

    1032:   Level: advanced

    1034:   Note:
    1035:   Different MPI processes may have different reasons or no reason, see `PCGetFailedReason()`. This routine
    1036:   makes them have a common value (failure if any MPI process had a failure).

    1038: .seealso: [](ch_ksp), `PC`, `PCCreate()`, `PCApply()`, `PCDestroy()`, `PCGetFailedReason()`, `PCSetFailedReason()`, `PCFailedReason`
    1039: @*/
    1040: PetscErrorCode PCReduceFailedReason(PC pc)
    1041: {
    1042:   PetscInt buf;

    1044:   PetscFunctionBegin;
    1046:   buf = (PetscInt)pc->failedreason;
    1047:   PetscCallMPI(MPIU_Allreduce(MPI_IN_PLACE, &buf, 1, MPIU_INT, MPI_MAX, PetscObjectComm((PetscObject)pc)));
    1048:   pc->failedreason = (PCFailedReason)buf;
    1049:   PetscFunctionReturn(PETSC_SUCCESS);
    1050: }

    1052: /*
    1053:       a setupcall of 0 indicates never setup,
    1054:                      1 indicates has been previously setup
    1055:                     -1 indicates a PCSetUp() was attempted and failed
    1056: */
    1057: /*@
    1058:   PCSetUp - Prepares for the use of a preconditioner. Performs all the one-time operations needed before the preconditioner
    1059:   can be used with `PCApply()`

    1061:   Collective

    1063:   Input Parameter:
    1064: . pc - the `PC` preconditioner context

    1066:   Level: developer

    1068:   Notes:
    1069:   For example, for `PCLU` this will compute the factorization.

    1071:   This is called automatically by `KSPSetUp()` or `PCApply()` so rarely needs to be called directly.

    1073:   For nested preconditioners, such as `PCFIELDSPLIT` or `PCBJACOBI` this may not finish the construction of the preconditioner
    1074:   on the inner levels, the routine `PCSetUpOnBlocks()` may compute more of the preconditioner in those situations.

    1076: .seealso: [](ch_ksp), `PC`, `PCCreate()`, `PCApply()`, `PCDestroy()`, `KSPSetUp()`, `PCSetUpOnBlocks()`
    1077: @*/
    1078: PetscErrorCode PCSetUp(PC pc)
    1079: {
    1080:   const char      *def;
    1081:   PetscObjectState matstate, matnonzerostate;

    1083:   PetscFunctionBegin;
    1085:   PetscCheck(pc->mat, PetscObjectComm((PetscObject)pc), PETSC_ERR_ARG_WRONGSTATE, "Matrix must be set first");

    1087:   if (pc->setupcalled && pc->reusepreconditioner) {
    1088:     PetscCall(PetscInfo(pc, "Leaving PC with identical preconditioner since reuse preconditioner is set\n"));
    1089:     PetscFunctionReturn(PETSC_SUCCESS);
    1090:   }

    1092:   PetscCall(PetscObjectStateGet((PetscObject)pc->pmat, &matstate));
    1093:   PetscCall(MatGetNonzeroState(pc->pmat, &matnonzerostate));
    1094:   if (!pc->setupcalled) {
    1095:     //PetscCall(PetscInfo(pc, "Setting up PC for first time\n"));
    1096:     pc->flag = DIFFERENT_NONZERO_PATTERN;
    1097:   } else if (matstate == pc->matstate) PetscFunctionReturn(PETSC_SUCCESS);
    1098:   else {
    1099:     if (matnonzerostate != pc->matnonzerostate) {
    1100:       PetscCall(PetscInfo(pc, "Setting up PC with different nonzero pattern\n"));
    1101:       pc->flag = DIFFERENT_NONZERO_PATTERN;
    1102:     } else {
    1103:       //PetscCall(PetscInfo(pc, "Setting up PC with same nonzero pattern\n"));
    1104:       pc->flag = SAME_NONZERO_PATTERN;
    1105:     }
    1106:   }
    1107:   pc->matstate        = matstate;
    1108:   pc->matnonzerostate = matnonzerostate;

    1110:   if (!((PetscObject)pc)->type_name) {
    1111:     PetscCall(PCGetDefaultType_Private(pc, &def));
    1112:     PetscCall(PCSetType(pc, def));
    1113:   }

    1115:   PetscCall(MatSetErrorIfFailure(pc->pmat, pc->erroriffailure));
    1116:   PetscCall(MatSetErrorIfFailure(pc->mat, pc->erroriffailure));
    1117:   PetscCall(PetscLogEventBegin(PC_SetUp, pc, 0, 0, 0));
    1118:   if (pc->ops->setup) {
    1119:     PetscCall(PCLogEventsDeactivatePush());
    1120:     PetscUseTypeMethod(pc, setup);
    1121:     PetscCall(PCLogEventsDeactivatePop());
    1122:   }
    1123:   PetscCall(PetscLogEventEnd(PC_SetUp, pc, 0, 0, 0));
    1124:   if (pc->postsetup) PetscCall((*pc->postsetup)(pc));
    1125:   if (!pc->setupcalled) pc->setupcalled = PETSC_TRUE;
    1126:   PetscFunctionReturn(PETSC_SUCCESS);
    1127: }

    1129: /*@
    1130:   PCSetUpOnBlocks - Sets up the preconditioner for each block in
    1131:   the block Jacobi, overlapping Schwarz, and fieldsplit methods.

    1133:   Collective

    1135:   Input Parameter:
    1136: . pc - the `PC` preconditioner context

    1138:   Level: developer

    1140:   Notes:
    1141:   For nested preconditioners such as `PCBJACOBI`, `PCSetUp()` is not called on each sub-`KSP` when `PCSetUp()` is
    1142:   called on the outer `PC`, this routine ensures it is called.

    1144:   It calls `PCSetUp()` if not yet called.

    1146: .seealso: [](ch_ksp), `PC`, `PCSetUp()`, `PCCreate()`, `PCApply()`, `PCDestroy()`
    1147: @*/
    1148: PetscErrorCode PCSetUpOnBlocks(PC pc)
    1149: {
    1150:   PetscFunctionBegin;
    1152:   if (!pc->setupcalled) PetscCall(PCSetUp(pc)); /* "if" to prevent -info extra prints */
    1153:   if (!pc->ops->setuponblocks) PetscFunctionReturn(PETSC_SUCCESS);
    1154:   PetscCall(MatSetErrorIfFailure(pc->pmat, pc->erroriffailure));
    1155:   PetscCall(PetscLogEventBegin(PC_SetUpOnBlocks, pc, 0, 0, 0));
    1156:   PetscCall(PCLogEventsDeactivatePush());
    1157:   PetscUseTypeMethod(pc, setuponblocks);
    1158:   PetscCall(PCLogEventsDeactivatePop());
    1159:   PetscCall(PetscLogEventEnd(PC_SetUpOnBlocks, pc, 0, 0, 0));
    1160:   PetscFunctionReturn(PETSC_SUCCESS);
    1161: }

    1163: /*@C
    1164:   PCSetModifySubMatrices - Sets a user-defined routine for modifying the
    1165:   submatrices that arise within certain subdomain-based preconditioners such as `PCASM`

    1167:   Logically Collective

    1169:   Input Parameters:
    1170: + pc   - the `PC` preconditioner context
    1171: . func - routine for modifying the submatrices, see `PCModifySubMatricesFn`
    1172: - ctx  - optional user-defined context (may be `NULL`)

    1174:   Level: advanced

    1176:   Notes:
    1177:   The basic submatrices are extracted from the matrix used to construct the preconditioner as
    1178:   usual; the user can then alter these (for example, to set different boundary
    1179:   conditions for each submatrix) before they are used for the local solves.

    1181:   `PCSetModifySubMatrices()` MUST be called before `KSPSetUp()` and
    1182:   `KSPSolve()`.

    1184:   A routine set by `PCSetModifySubMatrices()` is currently called within
    1185:   the block Jacobi (`PCBJACOBI`) and additive Schwarz (`PCASM`)
    1186:   preconditioners.  All other preconditioners ignore this routine.

    1188: .seealso: [](ch_ksp), `PC`, `PCModifySubMatricesFn`, `PCBJACOBI`, `PCASM`, `PCModifySubMatrices()`
    1189: @*/
    1190: PetscErrorCode PCSetModifySubMatrices(PC pc, PCModifySubMatricesFn *func, void *ctx)
    1191: {
    1192:   PetscFunctionBegin;
    1194:   pc->modifysubmatrices  = func;
    1195:   pc->modifysubmatricesP = ctx;
    1196:   PetscFunctionReturn(PETSC_SUCCESS);
    1197: }

    1199: /*@C
    1200:   PCModifySubMatrices - Calls an optional user-defined routine within
    1201:   certain preconditioners if one has been set with `PCSetModifySubMatrices()`.

    1203:   Collective

    1205:   Input Parameters:
    1206: + pc     - the `PC` preconditioner context
    1207: . nsub   - the number of local submatrices
    1208: . row    - an array of index sets that contain the global row numbers
    1209:          that comprise each local submatrix
    1210: . col    - an array of index sets that contain the global column numbers
    1211:          that comprise each local submatrix
    1212: . submat - array of local submatrices
    1213: - ctx    - optional user-defined context for private data for the
    1214:          user-defined routine (may be `NULL`)

    1216:   Output Parameter:
    1217: . submat - array of local submatrices (the entries of which may
    1218:             have been modified)

    1220:   Level: developer

    1222:   Note:
    1223:   The user should NOT generally call this routine, as it will
    1224:   automatically be called within certain preconditioners.

    1226: .seealso: [](ch_ksp), `PC`, `PCModifySubMatricesFn`, `PCSetModifySubMatrices()`
    1227: @*/
    1228: PetscErrorCode PCModifySubMatrices(PC pc, PetscInt nsub, const IS row[], const IS col[], Mat submat[], void *ctx)
    1229: {
    1230:   PetscFunctionBegin;
    1232:   if (!pc->modifysubmatrices) PetscFunctionReturn(PETSC_SUCCESS);
    1233:   PetscCall(PetscLogEventBegin(PC_ModifySubMatrices, pc, 0, 0, 0));
    1234:   PetscCall((*pc->modifysubmatrices)(pc, nsub, row, col, submat, ctx));
    1235:   PetscCall(PetscLogEventEnd(PC_ModifySubMatrices, pc, 0, 0, 0));
    1236:   PetscFunctionReturn(PETSC_SUCCESS);
    1237: }

    1239: /*@
    1240:   PCSetOperators - Sets the matrix associated with the linear system and
    1241:   a (possibly) different one from which the preconditioner will be constructed.

    1243:   Logically Collective

    1245:   Input Parameters:
    1246: + pc   - the `PC` preconditioner context
    1247: . Amat - the matrix that defines the linear system
    1248: - Pmat - the matrix to be used in constructing the preconditioner, usually the same as Amat.

    1250:   Level: advanced

    1252:   Notes:
    1253:   Using this routine directly is rarely needed, the preferred, and equivalent, usage is `KSPSetOperators()`.

    1255:   Passing a `NULL` for `Amat` or `Pmat` removes the matrix that is currently used.

    1257:   If you wish to replace either `Amat` or `Pmat` but leave the other one untouched then
    1258:   first call `KSPGetOperators()` to get the one you wish to keep, call `PetscObjectReference()`
    1259:   on it and then pass it back in in your call to `KSPSetOperators()`.

    1261:   More Notes about Repeated Solution of Linear Systems:
    1262:   PETSc does NOT reset the matrix entries of either `Amat` or `Pmat`
    1263:   to zero after a linear solve; the user is completely responsible for
    1264:   matrix assembly.  See the routine `MatZeroEntries()` if desiring to
    1265:   zero all elements of a matrix.

    1267: .seealso: [](ch_ksp), `PC`, `PCGetOperators()`, `MatZeroEntries()`
    1268:  @*/
    1269: PetscErrorCode PCSetOperators(PC pc, Mat Amat, Mat Pmat)
    1270: {
    1271:   PetscInt m1, n1, m2, n2;

    1273:   PetscFunctionBegin;
    1277:   if (Amat) PetscCheckSameComm(pc, 1, Amat, 2);
    1278:   if (Pmat) PetscCheckSameComm(pc, 1, Pmat, 3);
    1279:   if (pc->setupcalled && pc->mat && pc->pmat && Amat && Pmat) {
    1280:     PetscCall(MatGetLocalSize(Amat, &m1, &n1));
    1281:     PetscCall(MatGetLocalSize(pc->mat, &m2, &n2));
    1282:     PetscCheck(m1 == m2 && n1 == n2, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Cannot change local size of Amat after use old sizes %" PetscInt_FMT " %" PetscInt_FMT " new sizes %" PetscInt_FMT " %" PetscInt_FMT, m2, n2, m1, n1);
    1283:     PetscCall(MatGetLocalSize(Pmat, &m1, &n1));
    1284:     PetscCall(MatGetLocalSize(pc->pmat, &m2, &n2));
    1285:     PetscCheck(m1 == m2 && n1 == n2, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Cannot change local size of Pmat after use old sizes %" PetscInt_FMT " %" PetscInt_FMT " new sizes %" PetscInt_FMT " %" PetscInt_FMT, m2, n2, m1, n1);
    1286:   }

    1288:   if (Pmat != pc->pmat) {
    1289:     /* changing the operator that defines the preconditioner thus reneed to clear current states so new preconditioner is built */
    1290:     pc->matnonzerostate = -1;
    1291:     pc->matstate        = -1;
    1292:   }

    1294:   /* reference first in case the matrices are the same */
    1295:   if (Amat) PetscCall(PetscObjectReference((PetscObject)Amat));
    1296:   PetscCall(MatDestroy(&pc->mat));
    1297:   if (Pmat) PetscCall(PetscObjectReference((PetscObject)Pmat));
    1298:   PetscCall(MatDestroy(&pc->pmat));
    1299:   pc->mat  = Amat;
    1300:   pc->pmat = Pmat;
    1301:   PetscFunctionReturn(PETSC_SUCCESS);
    1302: }

    1304: /*@
    1305:   PCSetReusePreconditioner - reuse the current preconditioner even if the operator in the preconditioner `PC` has changed.

    1307:   Logically Collective

    1309:   Input Parameters:
    1310: + pc   - the `PC` preconditioner context
    1311: - flag - `PETSC_TRUE` do not compute a new preconditioner, `PETSC_FALSE` do compute a new preconditioner

    1313:   Level: intermediate

    1315:   Note:
    1316:   Normally if a matrix inside a `PC` changes the `PC` automatically updates itself using information from the changed matrix. This option
    1317:   prevents this.

    1319: .seealso: [](ch_ksp), `PC`, `PCGetOperators()`, `MatZeroEntries()`, `PCGetReusePreconditioner()`, `KSPSetReusePreconditioner()`
    1320:  @*/
    1321: PetscErrorCode PCSetReusePreconditioner(PC pc, PetscBool flag)
    1322: {
    1323:   PetscFunctionBegin;
    1326:   pc->reusepreconditioner = flag;
    1327:   PetscTryMethod(pc, "PCSetReusePreconditioner_C", (PC, PetscBool), (pc, flag));
    1328:   PetscFunctionReturn(PETSC_SUCCESS);
    1329: }

    1331: /*@
    1332:   PCGetReusePreconditioner - Determines if the `PC` reuses the current preconditioner even if the operator in the preconditioner has changed.

    1334:   Not Collective

    1336:   Input Parameter:
    1337: . pc - the `PC` preconditioner context

    1339:   Output Parameter:
    1340: . flag - `PETSC_TRUE` do not compute a new preconditioner, `PETSC_FALSE` do compute a new preconditioner

    1342:   Level: intermediate

    1344: .seealso: [](ch_ksp), `PC`, `PCGetOperators()`, `MatZeroEntries()`, `PCSetReusePreconditioner()`
    1345:  @*/
    1346: PetscErrorCode PCGetReusePreconditioner(PC pc, PetscBool *flag)
    1347: {
    1348:   PetscFunctionBegin;
    1350:   PetscAssertPointer(flag, 2);
    1351:   *flag = pc->reusepreconditioner;
    1352:   PetscFunctionReturn(PETSC_SUCCESS);
    1353: }

    1355: /*@
    1356:   PCGetOperators - Gets the matrix associated with the linear system and
    1357:   possibly a different one which is used to construct the preconditioner.

    1359:   Not Collective, though parallel `Mat`s are returned if `pc` is parallel

    1361:   Input Parameter:
    1362: . pc - the `PC` preconditioner context

    1364:   Output Parameters:
    1365: + Amat - the matrix defining the linear system
    1366: - Pmat - the matrix from which the preconditioner is constructed, usually the same as Amat.

    1368:   Level: intermediate

    1370:   Note:
    1371:   Does not increase the reference count of the matrices, so you should not destroy them

    1373:   Alternative usage: If the operators have NOT been set with `KSPSetOperators()`/`PCSetOperators()` then the operators
    1374:   are created in `PC` and returned to the user. In this case, if both operators
    1375:   mat and pmat are requested, two DIFFERENT operators will be returned. If
    1376:   only one is requested both operators in the PC will be the same (i.e. as
    1377:   if one had called `KSPSetOperators()`/`PCSetOperators()` with the same argument for both Mats).
    1378:   The user must set the sizes of the returned matrices and their type etc just
    1379:   as if the user created them with `MatCreate()`. For example,

    1381: .vb
    1382:          KSP/PCGetOperators(ksp/pc,&Amat,NULL); is equivalent to
    1383:            set size, type, etc of Amat

    1385:          MatCreate(comm,&mat);
    1386:          KSP/PCSetOperators(ksp/pc,Amat,Amat);
    1387:          PetscObjectDereference((PetscObject)mat);
    1388:            set size, type, etc of Amat
    1389: .ve

    1391:   and

    1393: .vb
    1394:          KSP/PCGetOperators(ksp/pc,&Amat,&Pmat); is equivalent to
    1395:            set size, type, etc of Amat and Pmat

    1397:          MatCreate(comm,&Amat);
    1398:          MatCreate(comm,&Pmat);
    1399:          KSP/PCSetOperators(ksp/pc,Amat,Pmat);
    1400:          PetscObjectDereference((PetscObject)Amat);
    1401:          PetscObjectDereference((PetscObject)Pmat);
    1402:            set size, type, etc of Amat and Pmat
    1403: .ve

    1405:   The rationale for this support is so that when creating a `TS`, `SNES`, or `KSP` the hierarchy
    1406:   of underlying objects (i.e. `SNES`, `KSP`, `PC`, `Mat`) and their lifespans can be completely
    1407:   managed by the top most level object (i.e. the `TS`, `SNES`, or `KSP`). Another way to look
    1408:   at this is when you create a `SNES` you do not NEED to create a `KSP` and attach it to
    1409:   the `SNES` object (the `SNES` object manages it for you). Similarly when you create a KSP
    1410:   you do not need to attach a `PC` to it (the `KSP` object manages the `PC` object for you).
    1411:   Thus, why should YOU have to create the `Mat` and attach it to the `SNES`/`KSP`/`PC`, when
    1412:   it can be created for you?

    1414: .seealso: [](ch_ksp), `PC`, `PCSetOperators()`, `KSPGetOperators()`, `KSPSetOperators()`, `PCGetOperatorsSet()`
    1415: @*/
    1416: PetscErrorCode PCGetOperators(PC pc, Mat *Amat, Mat *Pmat)
    1417: {
    1418:   PetscFunctionBegin;
    1420:   if (Amat) {
    1421:     if (!pc->mat) {
    1422:       if (pc->pmat && !Pmat) { /* Pmat has been set, but user did not request it, so use for Amat */
    1423:         pc->mat = pc->pmat;
    1424:         PetscCall(PetscObjectReference((PetscObject)pc->mat));
    1425:       } else { /* both Amat and Pmat are empty */
    1426:         PetscCall(MatCreate(PetscObjectComm((PetscObject)pc), &pc->mat));
    1427:         if (!Pmat) { /* user did NOT request Pmat, so make same as Amat */
    1428:           pc->pmat = pc->mat;
    1429:           PetscCall(PetscObjectReference((PetscObject)pc->pmat));
    1430:         }
    1431:       }
    1432:     }
    1433:     *Amat = pc->mat;
    1434:   }
    1435:   if (Pmat) {
    1436:     if (!pc->pmat) {
    1437:       if (pc->mat && !Amat) { /* Amat has been set but was not requested, so use for pmat */
    1438:         pc->pmat = pc->mat;
    1439:         PetscCall(PetscObjectReference((PetscObject)pc->pmat));
    1440:       } else {
    1441:         PetscCall(MatCreate(PetscObjectComm((PetscObject)pc), &pc->pmat));
    1442:         if (!Amat) { /* user did NOT request Amat, so make same as Pmat */
    1443:           pc->mat = pc->pmat;
    1444:           PetscCall(PetscObjectReference((PetscObject)pc->mat));
    1445:         }
    1446:       }
    1447:     }
    1448:     *Pmat = pc->pmat;
    1449:   }
    1450:   PetscFunctionReturn(PETSC_SUCCESS);
    1451: }

    1453: /*@
    1454:   PCGetOperatorsSet - Determines if the matrix associated with the linear system and
    1455:   possibly a different one associated with the preconditioner have been set in the `PC`.

    1457:   Not Collective, though the results on all processes should be the same

    1459:   Input Parameter:
    1460: . pc - the `PC` preconditioner context

    1462:   Output Parameters:
    1463: + mat  - the matrix associated with the linear system was set
    1464: - pmat - matrix associated with the preconditioner was set, usually the same

    1466:   Level: intermediate

    1468: .seealso: [](ch_ksp), `PC`, `PCSetOperators()`, `KSPGetOperators()`, `KSPSetOperators()`, `PCGetOperators()`
    1469: @*/
    1470: PetscErrorCode PCGetOperatorsSet(PC pc, PetscBool *mat, PetscBool *pmat)
    1471: {
    1472:   PetscFunctionBegin;
    1474:   if (mat) *mat = (pc->mat) ? PETSC_TRUE : PETSC_FALSE;
    1475:   if (pmat) *pmat = (pc->pmat) ? PETSC_TRUE : PETSC_FALSE;
    1476:   PetscFunctionReturn(PETSC_SUCCESS);
    1477: }

    1479: /*@
    1480:   PCFactorGetMatrix - Gets the factored matrix from the
    1481:   preconditioner context.  This routine is valid only for the `PCLU`,
    1482:   `PCILU`, `PCCHOLESKY`, and `PCICC` methods.

    1484:   Not Collective though `mat` is parallel if `pc` is parallel

    1486:   Input Parameter:
    1487: . pc - the `PC` preconditioner context

    1489:   Output Parameters:
    1490: . mat - the factored matrix

    1492:   Level: advanced

    1494:   Note:
    1495:   Does not increase the reference count for `mat` so DO NOT destroy it

    1497: .seealso: [](ch_ksp), `PC`, `PCLU`, `PCILU`, `PCCHOLESKY`, `PCICC`
    1498: @*/
    1499: PetscErrorCode PCFactorGetMatrix(PC pc, Mat *mat)
    1500: {
    1501:   PetscFunctionBegin;
    1503:   PetscAssertPointer(mat, 2);
    1504:   PetscCall(PCFactorSetUpMatSolverType(pc));
    1505:   PetscUseTypeMethod(pc, getfactoredmatrix, mat);
    1506:   PetscFunctionReturn(PETSC_SUCCESS);
    1507: }

    1509: /*@
    1510:   PCSetOptionsPrefix - Sets the prefix used for searching for all
    1511:   `PC` options in the database.

    1513:   Logically Collective

    1515:   Input Parameters:
    1516: + pc     - the `PC` preconditioner context
    1517: - prefix - the prefix string to prepend to all `PC` option requests

    1519:   Note:
    1520:   A hyphen (-) must NOT be given at the beginning of the prefix name.
    1521:   The first character of all runtime options is AUTOMATICALLY the
    1522:   hyphen.

    1524:   Level: advanced

    1526: .seealso: [](ch_ksp), `PC`, `PCSetFromOptions`, `PCAppendOptionsPrefix()`, `PCGetOptionsPrefix()`
    1527: @*/
    1528: PetscErrorCode PCSetOptionsPrefix(PC pc, const char prefix[])
    1529: {
    1530:   PetscFunctionBegin;
    1532:   PetscCall(PetscObjectSetOptionsPrefix((PetscObject)pc, prefix));
    1533:   PetscFunctionReturn(PETSC_SUCCESS);
    1534: }

    1536: /*@
    1537:   PCAppendOptionsPrefix - Appends to the prefix used for searching for all
    1538:   `PC` options in the database.

    1540:   Logically Collective

    1542:   Input Parameters:
    1543: + pc     - the `PC` preconditioner context
    1544: - prefix - the prefix string to prepend to all `PC` option requests

    1546:   Note:
    1547:   A hyphen (-) must NOT be given at the beginning of the prefix name.
    1548:   The first character of all runtime options is AUTOMATICALLY the
    1549:   hyphen.

    1551:   Level: advanced

    1553: .seealso: [](ch_ksp), `PC`, `PCSetFromOptions`, `PCSetOptionsPrefix()`, `PCGetOptionsPrefix()`
    1554: @*/
    1555: PetscErrorCode PCAppendOptionsPrefix(PC pc, const char prefix[])
    1556: {
    1557:   PetscFunctionBegin;
    1559:   PetscCall(PetscObjectAppendOptionsPrefix((PetscObject)pc, prefix));
    1560:   PetscFunctionReturn(PETSC_SUCCESS);
    1561: }

    1563: /*@
    1564:   PCGetOptionsPrefix - Gets the prefix used for searching for all
    1565:   PC options in the database.

    1567:   Not Collective

    1569:   Input Parameter:
    1570: . pc - the `PC` preconditioner context

    1572:   Output Parameter:
    1573: . prefix - pointer to the prefix string used, is returned

    1575:   Level: advanced

    1577: .seealso: [](ch_ksp), `PC`, `PCSetFromOptions`, `PCSetOptionsPrefix()`, `PCAppendOptionsPrefix()`
    1578: @*/
    1579: PetscErrorCode PCGetOptionsPrefix(PC pc, const char *prefix[])
    1580: {
    1581:   PetscFunctionBegin;
    1583:   PetscAssertPointer(prefix, 2);
    1584:   PetscCall(PetscObjectGetOptionsPrefix((PetscObject)pc, prefix));
    1585:   PetscFunctionReturn(PETSC_SUCCESS);
    1586: }

    1588: /*
    1589:    Indicates the right-hand side will be changed by KSPSolve(), this occurs for a few
    1590:   preconditioners including BDDC and Eisentat that transform the equations before applying
    1591:   the Krylov methods
    1592: */
    1593: PETSC_INTERN PetscErrorCode PCPreSolveChangeRHS(PC pc, PetscBool *change)
    1594: {
    1595:   PetscFunctionBegin;
    1597:   PetscAssertPointer(change, 2);
    1598:   *change = PETSC_FALSE;
    1599:   PetscTryMethod(pc, "PCPreSolveChangeRHS_C", (PC, PetscBool *), (pc, change));
    1600:   PetscFunctionReturn(PETSC_SUCCESS);
    1601: }

    1603: /*@
    1604:   PCPreSolve - Optional pre-solve phase, intended for any preconditioner-specific actions that must be performed before
    1605:   the iterative solve itself. Used in conjunction with `PCPostSolve()`

    1607:   Collective

    1609:   Input Parameters:
    1610: + pc  - the `PC` preconditioner context
    1611: - ksp - the Krylov subspace context

    1613:   Level: developer

    1615:   Notes:
    1616:   `KSPSolve()` calls this directly, so is rarely called by the user.

    1618:   Certain preconditioners, such as the `PCType` of `PCEISENSTAT`, change the formulation of the linear system to be solved iteratively.
    1619:   This function performs that transformation. `PCPostSolve()` then transforms the system back to its original form after the solve.
    1620:   `PCPostSolve()` also transforms the resulting solution of the transformed system to the solution of the original problem.

    1622:   `KSPSetPostSolve()` provides an alternative way to provide such transformations.

    1624: .seealso: [](ch_ksp), `PC`, `PCPostSolve()`, `KSP`, `PCSetPostSetUp()`, `KSPSetPreSolve()`, `KSPSetPostSolve()`
    1625: @*/
    1626: PetscErrorCode PCPreSolve(PC pc, KSP ksp)
    1627: {
    1628:   Vec x, rhs;

    1630:   PetscFunctionBegin;
    1633:   pc->presolvedone++;
    1634:   PetscCheck(pc->presolvedone <= 2, PetscObjectComm((PetscObject)pc), PETSC_ERR_SUP, "Cannot embed PCPreSolve() more than twice");
    1635:   PetscCall(KSPGetSolution(ksp, &x));
    1636:   PetscCall(KSPGetRhs(ksp, &rhs));
    1637:   PetscTryTypeMethod(pc, presolve, ksp, rhs, x);
    1638:   PetscFunctionReturn(PETSC_SUCCESS);
    1639: }

    1641: /*@C
    1642:   PCSetPostSetUp - Sets function called at the end of `PCSetUp()` to adjust the computed preconditioner

    1644:   Logically Collective

    1646:   Input Parameters:
    1647: + pc        - the preconditioner object
    1648: - postsetup - the function to call after `PCSetUp()`

    1650:   Calling sequence of `postsetup`:
    1651: . pc - the `PC` context

    1653:   Level: developer

    1655: .seealso: [](ch_ksp), `PC`, `PCSetUp()`
    1656: @*/
    1657: PetscErrorCode PCSetPostSetUp(PC pc, PetscErrorCode (*postsetup)(PC pc))
    1658: {
    1659:   PetscFunctionBegin;
    1661:   pc->postsetup = postsetup;
    1662:   PetscFunctionReturn(PETSC_SUCCESS);
    1663: }

    1665: /*@
    1666:   PCPostSolve - Optional post-solve phase, intended for any
    1667:   preconditioner-specific actions that must be performed after
    1668:   the iterative solve itself.

    1670:   Collective

    1672:   Input Parameters:
    1673: + pc  - the `PC` preconditioner context
    1674: - ksp - the `KSP` Krylov subspace context

    1676:   Example Usage:
    1677: .vb
    1678:     PCPreSolve(pc,ksp);
    1679:     KSPSolve(ksp,b,x);
    1680:     PCPostSolve(pc,ksp);
    1681: .ve

    1683:   Level: developer

    1685:   Note:
    1686:   `KSPSolve()` calls this routine directly, so it is rarely called by the user.

    1688: .seealso: [](ch_ksp), `PC`, `KSPSetPostSolve()`, `KSPSetPreSolve()`, `PCPreSolve()`, `KSPSolve()`
    1689: @*/
    1690: PetscErrorCode PCPostSolve(PC pc, KSP ksp)
    1691: {
    1692:   Vec x, rhs;

    1694:   PetscFunctionBegin;
    1697:   pc->presolvedone--;
    1698:   PetscCall(KSPGetSolution(ksp, &x));
    1699:   PetscCall(KSPGetRhs(ksp, &rhs));
    1700:   PetscTryTypeMethod(pc, postsolve, ksp, rhs, x);
    1701:   PetscFunctionReturn(PETSC_SUCCESS);
    1702: }

    1704: /*@
    1705:   PCLoad - Loads a `PC` that has been stored in binary  with `PCView()`.

    1707:   Collective

    1709:   Input Parameters:
    1710: + newdm  - the newly loaded `PC`, this needs to have been created with `PCCreate()` or
    1711:            some related function before a call to `PCLoad()`.
    1712: - viewer - binary file viewer `PETSCVIEWERBINARY`, obtained from `PetscViewerBinaryOpen()`

    1714:   Level: intermediate

    1716:   Note:
    1717:   The type is determined by the data in the file, any `PCType` set into the `PC` before this call is ignored.

    1719: .seealso: [](ch_ksp), `PC`, `PetscViewerBinaryOpen()`, `PCView()`, `MatLoad()`, `VecLoad()`, `PETSCVIEWERBINARY`
    1720: @*/
    1721: PetscErrorCode PCLoad(PC newdm, PetscViewer viewer)
    1722: {
    1723:   PetscBool isbinary;
    1724:   PetscInt  classid;
    1725:   char      type[256];

    1727:   PetscFunctionBegin;
    1730:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary));
    1731:   PetscCheck(isbinary, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Invalid viewer; open viewer with PetscViewerBinaryOpen()");

    1733:   PetscCall(PetscViewerBinaryRead(viewer, &classid, 1, NULL, PETSC_INT));
    1734:   PetscCheck(classid == PC_FILE_CLASSID, PetscObjectComm((PetscObject)newdm), PETSC_ERR_ARG_WRONG, "Not PC next in file");
    1735:   PetscCall(PetscViewerBinaryRead(viewer, type, 256, NULL, PETSC_CHAR));
    1736:   PetscCall(PCSetType(newdm, type));
    1737:   PetscTryTypeMethod(newdm, load, viewer);
    1738:   PetscFunctionReturn(PETSC_SUCCESS);
    1739: }

    1741: #include <petscdraw.h>
    1742: #if defined(PETSC_HAVE_SAWS)
    1743: #include <petscviewersaws.h>
    1744: #endif

    1746: /*@
    1747:   PCViewFromOptions - View (print or provide information about) the `PC`, based on options in the options database

    1749:   Collective

    1751:   Input Parameters:
    1752: + A    - the `PC` context
    1753: . obj  - Optional object that provides the options prefix
    1754: - name - command line option name

    1756:   Level: developer

    1758: .seealso: [](ch_ksp), `PC`, `PCView`, `PetscObjectViewFromOptions()`, `PCCreate()`
    1759: @*/
    1760: PetscErrorCode PCViewFromOptions(PC A, PetscObject obj, const char name[])
    1761: {
    1762:   PetscFunctionBegin;
    1764:   PetscCall(PetscObjectViewFromOptions((PetscObject)A, obj, name));
    1765:   PetscFunctionReturn(PETSC_SUCCESS);
    1766: }

    1768: /*@
    1769:   PCView - Prints information about the `PC`

    1771:   Collective

    1773:   Input Parameters:
    1774: + pc     - the `PC` preconditioner context
    1775: - viewer - optional `PetscViewer` visualization context

    1777:   Level: intermediate

    1779:   Notes:
    1780:   The available visualization contexts include
    1781: +     `PETSC_VIEWER_STDOUT_SELF` - standard output (default)
    1782: -     `PETSC_VIEWER_STDOUT_WORLD` - synchronized standard
    1783:   output where only the first processor opens
    1784:   the file. All other processors send their
    1785:   data to the first processor to print.

    1787:   The user can open an alternative visualization contexts with
    1788:   `PetscViewerASCIIOpen()` (output to a specified file).

    1790: .seealso: [](ch_ksp), `PC`, `PetscViewer`, `PetscViewerType`, `KSPView()`, `PetscViewerASCIIOpen()`
    1791: @*/
    1792: PetscErrorCode PCView(PC pc, PetscViewer viewer)
    1793: {
    1794:   PCType            cstr;
    1795:   PetscViewerFormat format;
    1796:   PetscBool         isascii, isstring, isbinary, isdraw, pop = PETSC_FALSE;
    1797: #if defined(PETSC_HAVE_SAWS)
    1798:   PetscBool issaws;
    1799: #endif

    1801:   PetscFunctionBegin;
    1803:   if (!viewer) PetscCall(PetscViewerASCIIGetStdout(PetscObjectComm((PetscObject)pc), &viewer));
    1805:   PetscCheckSameComm(pc, 1, viewer, 2);

    1807:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &isascii));
    1808:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERSTRING, &isstring));
    1809:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary));
    1810:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERDRAW, &isdraw));
    1811: #if defined(PETSC_HAVE_SAWS)
    1812:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERSAWS, &issaws));
    1813: #endif

    1815:   if (isascii) {
    1816:     PetscCall(PetscObjectPrintClassNamePrefixType((PetscObject)pc, viewer));
    1817:     if (!pc->setupcalled) PetscCall(PetscViewerASCIIPrintf(viewer, "  PC has not been set up so information may be incomplete\n"));
    1818:     PetscCall(PetscViewerASCIIPushTab(viewer));
    1819:     PetscTryTypeMethod(pc, view, viewer);
    1820:     PetscCall(PetscViewerASCIIPopTab(viewer));
    1821:     if (pc->mat) {
    1822:       PetscCall(PetscViewerGetFormat(viewer, &format));
    1823:       if (format != PETSC_VIEWER_ASCII_INFO_DETAIL) {
    1824:         PetscCall(PetscViewerPushFormat(viewer, PETSC_VIEWER_ASCII_INFO));
    1825:         pop = PETSC_TRUE;
    1826:       }
    1827:       if (pc->pmat == pc->mat) {
    1828:         PetscCall(PetscViewerASCIIPrintf(viewer, "  linear system matrix = precond matrix:\n"));
    1829:         PetscCall(PetscViewerASCIIPushTab(viewer));
    1830:         PetscCall(MatView(pc->mat, viewer));
    1831:         PetscCall(PetscViewerASCIIPopTab(viewer));
    1832:       } else {
    1833:         if (pc->pmat) {
    1834:           PetscCall(PetscViewerASCIIPrintf(viewer, "  linear system matrix followed by preconditioner matrix:\n"));
    1835:         } else {
    1836:           PetscCall(PetscViewerASCIIPrintf(viewer, "  linear system matrix:\n"));
    1837:         }
    1838:         PetscCall(PetscViewerASCIIPushTab(viewer));
    1839:         PetscCall(MatView(pc->mat, viewer));
    1840:         if (pc->pmat) PetscCall(MatView(pc->pmat, viewer));
    1841:         PetscCall(PetscViewerASCIIPopTab(viewer));
    1842:       }
    1843:       if (pop) PetscCall(PetscViewerPopFormat(viewer));
    1844:     }
    1845:   } else if (isstring) {
    1846:     PetscCall(PCGetType(pc, &cstr));
    1847:     PetscCall(PetscViewerStringSPrintf(viewer, " PCType: %-7.7s", cstr));
    1848:     PetscTryTypeMethod(pc, view, viewer);
    1849:     if (pc->mat) PetscCall(MatView(pc->mat, viewer));
    1850:     if (pc->pmat && pc->pmat != pc->mat) PetscCall(MatView(pc->pmat, viewer));
    1851:   } else if (isbinary) {
    1852:     PetscInt    classid = PC_FILE_CLASSID;
    1853:     MPI_Comm    comm;
    1854:     PetscMPIInt rank;
    1855:     char        type[256];

    1857:     PetscCall(PetscObjectGetComm((PetscObject)pc, &comm));
    1858:     PetscCallMPI(MPI_Comm_rank(comm, &rank));
    1859:     if (rank == 0) {
    1860:       PetscCall(PetscViewerBinaryWrite(viewer, &classid, 1, PETSC_INT));
    1861:       PetscCall(PetscStrncpy(type, ((PetscObject)pc)->type_name, 256));
    1862:       PetscCall(PetscViewerBinaryWrite(viewer, type, 256, PETSC_CHAR));
    1863:     }
    1864:     PetscTryTypeMethod(pc, view, viewer);
    1865:   } else if (isdraw) {
    1866:     PetscDraw draw;
    1867:     char      str[25];
    1868:     PetscReal x, y, bottom, h;
    1869:     PetscInt  n;

    1871:     PetscCall(PetscViewerDrawGetDraw(viewer, 0, &draw));
    1872:     PetscCall(PetscDrawGetCurrentPoint(draw, &x, &y));
    1873:     if (pc->mat) {
    1874:       PetscCall(MatGetSize(pc->mat, &n, NULL));
    1875:       PetscCall(PetscSNPrintf(str, 25, "PC: %s (%" PetscInt_FMT ")", ((PetscObject)pc)->type_name, n));
    1876:     } else {
    1877:       PetscCall(PetscSNPrintf(str, 25, "PC: %s", ((PetscObject)pc)->type_name));
    1878:     }
    1879:     PetscCall(PetscDrawStringBoxed(draw, x, y, PETSC_DRAW_RED, PETSC_DRAW_BLACK, str, NULL, &h));
    1880:     bottom = y - h;
    1881:     PetscCall(PetscDrawPushCurrentPoint(draw, x, bottom));
    1882:     PetscTryTypeMethod(pc, view, viewer);
    1883:     PetscCall(PetscDrawPopCurrentPoint(draw));
    1884: #if defined(PETSC_HAVE_SAWS)
    1885:   } else if (issaws) {
    1886:     PetscMPIInt rank;

    1888:     PetscCall(PetscObjectName((PetscObject)pc));
    1889:     PetscCallMPI(MPI_Comm_rank(PETSC_COMM_WORLD, &rank));
    1890:     if (!((PetscObject)pc)->amsmem && rank == 0) PetscCall(PetscObjectViewSAWs((PetscObject)pc, viewer));
    1891:     if (pc->mat) PetscCall(MatView(pc->mat, viewer));
    1892:     if (pc->pmat && pc->pmat != pc->mat) PetscCall(MatView(pc->pmat, viewer));
    1893: #endif
    1894:   }
    1895:   PetscFunctionReturn(PETSC_SUCCESS);
    1896: }

    1898: /*@C
    1899:   PCRegister -  Adds a method (`PCType`) to the PETSc preconditioner package.

    1901:   Not collective. No Fortran Support

    1903:   Input Parameters:
    1904: + sname    - name of a new user-defined solver
    1905: - function - routine to create the method context which will be stored in a `PC` when `PCSetType()` is called

    1907:   Example Usage:
    1908: .vb
    1909:    PCRegister("my_solver", MySolverCreate);
    1910: .ve

    1912:   Then, your solver can be chosen with the procedural interface via
    1913: .vb
    1914:   PCSetType(pc, "my_solver")
    1915: .ve
    1916:   or at runtime via the option
    1917: .vb
    1918:   -pc_type my_solver
    1919: .ve

    1921:   Level: advanced

    1923:   Note:
    1924:   A simpler alternative to using `PCRegister()` for an application specific preconditioner is to use a `PC` of `PCType` `PCSHELL` and
    1925:   provide your customizations with `PCShellSetContext()` and `PCShellSetApply()`

    1927:   `PCRegister()` may be called multiple times to add several user-defined preconditioners.

    1929: .seealso: [](ch_ksp), `PC`, `PCType`, `PCRegisterAll()`, `PCSetType()`, `PCShellSetContext()`, `PCShellSetApply()`, `PCSHELL`
    1930: @*/
    1931: PetscErrorCode PCRegister(const char sname[], PetscErrorCode (*function)(PC))
    1932: {
    1933:   PetscFunctionBegin;
    1934:   PetscCall(PCInitializePackage());
    1935:   PetscCall(PetscFunctionListAdd(&PCList, sname, function));
    1936:   PetscFunctionReturn(PETSC_SUCCESS);
    1937: }

    1939: static PetscErrorCode MatMult_PC(Mat A, Vec X, Vec Y)
    1940: {
    1941:   PC pc;

    1943:   PetscFunctionBegin;
    1944:   PetscCall(MatShellGetContext(A, &pc));
    1945:   PetscCall(PCApply(pc, X, Y));
    1946:   PetscFunctionReturn(PETSC_SUCCESS);
    1947: }

    1949: /*@
    1950:   PCComputeOperator - Computes the explicit preconditioned operator as a matrix `Mat`.

    1952:   Collective

    1954:   Input Parameters:
    1955: + pc      - the `PC` preconditioner object
    1956: - mattype - the `MatType` to be used for the operator

    1958:   Output Parameter:
    1959: . mat - the explicit preconditioned operator

    1961:   Level: advanced

    1963:   Note:
    1964:   This computation is done by applying the operators to columns of the identity matrix.
    1965:   This routine is costly in general, and is recommended for use only with relatively small systems.
    1966:   Currently, this routine uses a dense matrix format when `mattype` == `NULL`

    1968:   Developer Note:
    1969:   This should be called `PCCreateExplicitOperator()`

    1971: .seealso: [](ch_ksp), `PC`, `KSPComputeOperator()`, `MatType`
    1972: @*/
    1973: PetscErrorCode PCComputeOperator(PC pc, MatType mattype, Mat *mat)
    1974: {
    1975:   PetscInt N, M, m, n;
    1976:   Mat      A, Apc;

    1978:   PetscFunctionBegin;
    1980:   PetscAssertPointer(mat, 3);
    1981:   PetscCall(PCGetOperators(pc, &A, NULL));
    1982:   PetscCall(MatGetLocalSize(A, &m, &n));
    1983:   PetscCall(MatGetSize(A, &M, &N));
    1984:   PetscCall(MatCreateShell(PetscObjectComm((PetscObject)pc), m, n, M, N, pc, &Apc));
    1985:   PetscCall(MatShellSetOperation(Apc, MATOP_MULT, (PetscErrorCodeFn *)MatMult_PC));
    1986:   PetscCall(MatComputeOperator(Apc, mattype, mat));
    1987:   PetscCall(MatDestroy(&Apc));
    1988:   PetscFunctionReturn(PETSC_SUCCESS);
    1989: }

    1991: /*@
    1992:   PCSetCoordinates - sets the coordinates of all the nodes (degrees of freedom in the vector) on the local process

    1994:   Collective

    1996:   Input Parameters:
    1997: + pc     - the `PC` preconditioner context
    1998: . dim    - the dimension of the coordinates 1, 2, or 3
    1999: . nloc   - the blocked size of the coordinates array
    2000: - coords - the coordinates array

    2002:   Level: intermediate

    2004:   Notes:
    2005:   `coords` is an array of the dim coordinates for the nodes on
    2006:   the local processor, of size `dim`*`nloc`.
    2007:   If there are 108 equations (dofs) on a processor
    2008:   for a 3d displacement finite element discretization of elasticity (so
    2009:   that there are nloc = 36 = 108/3 nodes) then the array must have 108
    2010:   double precision values (ie, 3 * 36).  These x y z coordinates
    2011:   should be ordered for nodes 0 to N-1 like so: [ 0.x, 0.y, 0.z, 1.x,
    2012:   ... , N-1.z ].

    2014:   The information provided here can be used by some preconditioners, such as `PCGAMG`, to produce a better preconditioner.
    2015:   See also  `MatSetNearNullSpace()`.

    2017: .seealso: [](ch_ksp), `PC`, `MatSetNearNullSpace()`
    2018: @*/
    2019: PetscErrorCode PCSetCoordinates(PC pc, PetscInt dim, PetscInt nloc, PetscReal coords[])
    2020: {
    2021:   PetscFunctionBegin;
    2024:   PetscTryMethod(pc, "PCSetCoordinates_C", (PC, PetscInt, PetscInt, PetscReal[]), (pc, dim, nloc, coords));
    2025:   PetscFunctionReturn(PETSC_SUCCESS);
    2026: }

    2028: /*@
    2029:   PCGetInterpolations - Gets interpolation matrices for all levels (except level 0)

    2031:   Logically Collective

    2033:   Input Parameter:
    2034: . pc - the precondition context

    2036:   Output Parameters:
    2037: + num_levels     - the number of levels
    2038: - interpolations - the interpolation matrices (size of `num_levels`-1)

    2040:   Level: advanced

    2042:   Developer Note:
    2043:   Why is this here instead of in `PCMG` etc?

    2045: .seealso: [](ch_ksp), `PC`, `PCMG`, `PCMGGetRestriction()`, `PCMGSetInterpolation()`, `PCMGGetInterpolation()`, `PCGetCoarseOperators()`
    2046: @*/
    2047: PetscErrorCode PCGetInterpolations(PC pc, PetscInt *num_levels, Mat *interpolations[])
    2048: {
    2049:   PetscFunctionBegin;
    2051:   PetscAssertPointer(num_levels, 2);
    2052:   PetscAssertPointer(interpolations, 3);
    2053:   PetscUseMethod(pc, "PCGetInterpolations_C", (PC, PetscInt *, Mat *[]), (pc, num_levels, interpolations));
    2054:   PetscFunctionReturn(PETSC_SUCCESS);
    2055: }

    2057: /*@
    2058:   PCGetCoarseOperators - Gets coarse operator matrices for all levels (except the finest level)

    2060:   Logically Collective

    2062:   Input Parameter:
    2063: . pc - the precondition context

    2065:   Output Parameters:
    2066: + num_levels      - the number of levels
    2067: - coarseOperators - the coarse operator matrices (size of `num_levels`-1)

    2069:   Level: advanced

    2071:   Developer Note:
    2072:   Why is this here instead of in `PCMG` etc?

    2074: .seealso: [](ch_ksp), `PC`, `PCMG`, `PCMGGetRestriction()`, `PCMGSetInterpolation()`, `PCMGGetRScale()`, `PCMGGetInterpolation()`, `PCGetInterpolations()`
    2075: @*/
    2076: PetscErrorCode PCGetCoarseOperators(PC pc, PetscInt *num_levels, Mat *coarseOperators[])
    2077: {
    2078:   PetscFunctionBegin;
    2080:   PetscAssertPointer(num_levels, 2);
    2081:   PetscAssertPointer(coarseOperators, 3);
    2082:   PetscUseMethod(pc, "PCGetCoarseOperators_C", (PC, PetscInt *, Mat *[]), (pc, num_levels, coarseOperators));
    2083:   PetscFunctionReturn(PETSC_SUCCESS);
    2084: }