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) PetscCall(VecPointwiseMult(out, pc->diagonalscaleleft, in));
    258:   else if (in != out) PetscCall(VecCopy(in, out));
    259:   PetscFunctionReturn(PETSC_SUCCESS);
    260: }

    262: /*@
    263:   PCDiagonalScaleRight - Scales a vector by the right scaling as needed by certain time-stepping codes.

    265:   Logically Collective

    267:   Input Parameters:
    268: + pc  - the `PC` preconditioner context
    269: . in  - input vector
    270: - out - scaled vector (maybe the same as in)

    272:   Level: intermediate

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

    277:   $$
    278:   \begin{align*}
    279:   D M A D^{-1} y = D M b  \\
    280:   D A M D^{-1} z = D b.
    281:   \end{align*}
    282:   $$

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

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

    288: .seealso: [](ch_ksp), `PCCreate()`, `PCSetUp()`, `PCDiagonalScaleLeft()`, `PCSetDiagonalScale()`, `MatDiagonalScale()`
    289: @*/
    290: PetscErrorCode PCDiagonalScaleRight(PC pc, Vec in, Vec out)
    291: {
    292:   PetscFunctionBegin;
    296:   if (pc->diagonalscale) {
    297:     PetscCall(VecPointwiseMult(out, pc->diagonalscaleright, in));
    298:   } else if (in != out) {
    299:     PetscCall(VecCopy(in, out));
    300:   }
    301:   PetscFunctionReturn(PETSC_SUCCESS);
    302: }

    304: /*@
    305:   PCSetUseAmat - Sets a flag to indicate that when the preconditioner needs to apply (part of) the
    306:   operator during the preconditioning process it applies the Amat provided to `TSSetRHSJacobian()`,
    307:   `TSSetIJacobian()`, `SNESSetJacobian()`, `KSPSetOperators()` or `PCSetOperators()` not the Pmat.

    309:   Logically Collective

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

    315:   Options Database Key:
    316: . -pc_use_amat (true|false) - use the amat argument to `KSPSetOperators()` or `PCSetOperators()` to apply the operator

    318:   Level: intermediate

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

    324: .seealso: [](ch_ksp), `PC`, `PCGetUseAmat()`, `PCBJACOBI`, `PCMG`, `PCFIELDSPLIT`, `PCCOMPOSITE`,
    325:           `KSPSetOperators()`, `PCSetOperators()`
    326: @*/
    327: PetscErrorCode PCSetUseAmat(PC pc, PetscBool flg)
    328: {
    329:   PetscFunctionBegin;
    331:   pc->useAmat = flg;
    332:   PetscFunctionReturn(PETSC_SUCCESS);
    333: }

    335: /*@
    336:   PCSetErrorIfFailure - Causes `PC` to generate an error if a floating point exception, for example a zero pivot, is detected.

    338:   Logically Collective

    340:   Input Parameters:
    341: + pc  - iterative context obtained from `PCCreate()`
    342: - flg - `PETSC_TRUE` indicates you want the error generated

    344:   Level: advanced

    346:   Notes:
    347:   Normally PETSc continues if a linear solver fails due to a failed setup of a preconditioner, you can call `KSPGetConvergedReason()` after a `KSPSolve()`
    348:   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
    349:   detected.

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

    353: .seealso: [](ch_ksp), `PC`, `KSPSetErrorIfNotConverged()`, `PCGetInitialGuessNonzero()`, `PCSetInitialGuessKnoll()`, `PCGetInitialGuessKnoll()`
    354: @*/
    355: PetscErrorCode PCSetErrorIfFailure(PC pc, PetscBool flg)
    356: {
    357:   PetscFunctionBegin;
    360:   pc->erroriffailure = flg;
    361:   PetscFunctionReturn(PETSC_SUCCESS);
    362: }

    364: /*@
    365:   PCGetUseAmat - Gets a flag to indicate that when the preconditioner needs to apply (part of) the
    366:   operator during the preconditioning process it applies the Amat provided to `TSSetRHSJacobian()`,
    367:   `TSSetIJacobian()`, `SNESSetJacobian()`, `KSPSetOperators()` or `PCSetOperators()` not the Pmat.

    369:   Logically Collective

    371:   Input Parameter:
    372: . pc - the `PC` preconditioner context

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

    377:   Level: intermediate

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

    383: .seealso: [](ch_ksp), `PC`, `PCSetUseAmat()`, `PCBJACOBI`, `PCMG`, `PCFIELDSPLIT`, `PCCOMPOSITE`
    384: @*/
    385: PetscErrorCode PCGetUseAmat(PC pc, PetscBool *flg)
    386: {
    387:   PetscFunctionBegin;
    389:   *flg = pc->useAmat;
    390:   PetscFunctionReturn(PETSC_SUCCESS);
    391: }

    393: /*@
    394:   PCSetKSPNestLevel - sets the amount of nesting the `KSP` that contains this `PC` has

    396:   Collective

    398:   Input Parameters:
    399: + pc    - the `PC`
    400: - level - the nest level

    402:   Level: developer

    404: .seealso: [](ch_ksp), `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSP`, `KSPGMRES`, `KSPType`, `KSPGetNestLevel()`, `PCGetKSPNestLevel()`, `KSPSetNestLevel()`
    405: @*/
    406: PetscErrorCode PCSetKSPNestLevel(PC pc, PetscInt level)
    407: {
    408:   PetscFunctionBegin;
    411:   pc->kspnestlevel = level;
    412:   PetscFunctionReturn(PETSC_SUCCESS);
    413: }

    415: /*@
    416:   PCGetKSPNestLevel - gets the amount of nesting the `KSP` that contains this `PC` has

    418:   Not Collective

    420:   Input Parameter:
    421: . pc - the `PC`

    423:   Output Parameter:
    424: . level - the nest level

    426:   Level: developer

    428: .seealso: [](ch_ksp), `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSP`, `KSPGMRES`, `KSPType`, `KSPSetNestLevel()`, `PCSetKSPNestLevel()`, `KSPGetNestLevel()`
    429: @*/
    430: PetscErrorCode PCGetKSPNestLevel(PC pc, PetscInt *level)
    431: {
    432:   PetscFunctionBegin;
    434:   PetscAssertPointer(level, 2);
    435:   *level = pc->kspnestlevel;
    436:   PetscFunctionReturn(PETSC_SUCCESS);
    437: }

    439: /*@
    440:   PCCreate - Creates a preconditioner context, `PC`

    442:   Collective

    444:   Input Parameter:
    445: . comm - MPI communicator

    447:   Output Parameter:
    448: . newpc - location to put the `PC` preconditioner context

    450:   Level: developer

    452:   Notes:
    453:   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`.

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

    457:   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`
    458:   in parallel. For dense matrices it is always `PCNONE`.

    460: .seealso: [](ch_ksp), `PC`, `PCType`, `PCSetType`, `PCSetUp()`, `PCApply()`, `PCDestroy()`, `KSP`, `KSPGetPC()`
    461: @*/
    462: PetscErrorCode PCCreate(MPI_Comm comm, PC *newpc)
    463: {
    464:   PC pc;

    466:   PetscFunctionBegin;
    467:   PetscAssertPointer(newpc, 2);
    468:   PetscCall(PCInitializePackage());

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

    480:   pc->modifysubmatrices  = NULL;
    481:   pc->modifysubmatricesP = NULL;

    483:   *newpc = pc;
    484:   PetscFunctionReturn(PETSC_SUCCESS);
    485: }

    487: /*@
    488:   PCApply - Applies the preconditioner to a vector.

    490:   Collective

    492:   Input Parameters:
    493: + pc - the `PC` preconditioner context
    494: - x  - input vector

    496:   Output Parameter:
    497: . y - output vector

    499:   Level: developer

    501: .seealso: [](ch_ksp), `PC`, `PCApplyTranspose()`, `PCApplyBAorAB()`
    502: @*/
    503: PetscErrorCode PCApply(PC pc, Vec x, Vec y)
    504: {
    505:   PetscInt m, n, mv, nv;

    507:   PetscFunctionBegin;
    511:   PetscCheck(x != y, PetscObjectComm((PetscObject)pc), PETSC_ERR_ARG_IDN, "x and y must be different vectors");
    512:   if (pc->erroriffailure) PetscCall(VecValidValues_Internal(x, 2, PETSC_TRUE));
    513:   /* use pmat to check vector sizes since for KSPLSQR the pmat may be of a different size than mat */
    514:   PetscCall(MatGetLocalSize(pc->pmat, &m, &n));
    515:   PetscCall(VecGetLocalSize(x, &mv));
    516:   PetscCall(VecGetLocalSize(y, &nv));
    517:   /* check pmat * y = x is feasible */
    518:   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);
    519:   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);
    520:   PetscCall(VecSetErrorIfLocked(y, 3));

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

    532: static PetscErrorCode PCMatApplyTranspose_Private(PC pc, Mat X, Mat Y, PetscBool transpose)
    533: {
    534:   Mat       A;
    535:   Vec       cy, cx;
    536:   PetscInt  m1, M1, m2, M2, n1, N1, n2, N2, m3, M3, n3, N3;
    537:   PetscBool match;

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

    583: /*@
    584:   PCMatApply - Applies the preconditioner to multiple vectors stored as a `MATDENSE`. Like `PCApply()`, `Y` and `X` must be different matrices.

    586:   Collective

    588:   Input Parameters:
    589: + pc - the `PC` preconditioner context
    590: - X  - block of input vectors

    592:   Output Parameter:
    593: . Y - block of output vectors

    595:   Level: developer

    597: .seealso: [](ch_ksp), `PC`, `PCApply()`, `KSPMatSolve()`
    598: @*/
    599: PetscErrorCode PCMatApply(PC pc, Mat X, Mat Y)
    600: {
    601:   PetscFunctionBegin;
    602:   PetscCall(PCMatApplyTranspose_Private(pc, X, Y, PETSC_FALSE));
    603:   PetscFunctionReturn(PETSC_SUCCESS);
    604: }

    606: /*@
    607:   PCMatApplyTranspose - Applies the transpose of preconditioner to multiple vectors stored as a `MATDENSE`. Like `PCApplyTranspose()`, `Y` and `X` must be different matrices.

    609:   Collective

    611:   Input Parameters:
    612: + pc - the `PC` preconditioner context
    613: - X  - block of input vectors

    615:   Output Parameter:
    616: . Y - block of output vectors

    618:   Level: developer

    620: .seealso: [](ch_ksp), `PC`, `PCApplyTranspose()`, `KSPMatSolveTranspose()`
    621: @*/
    622: PetscErrorCode PCMatApplyTranspose(PC pc, Mat X, Mat Y)
    623: {
    624:   PetscFunctionBegin;
    625:   PetscCall(PCMatApplyTranspose_Private(pc, X, Y, PETSC_TRUE));
    626:   PetscFunctionReturn(PETSC_SUCCESS);
    627: }

    629: /*@
    630:   PCApplySymmetricLeft - Applies the left part of a symmetric preconditioner to a vector.

    632:   Collective

    634:   Input Parameters:
    635: + pc - the `PC` preconditioner context
    636: - x  - input vector

    638:   Output Parameter:
    639: . y - output vector

    641:   Level: developer

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

    646: .seealso: [](ch_ksp), `PC`, `PCApply()`, `PCApplySymmetricRight()`
    647: @*/
    648: PetscErrorCode PCApplySymmetricLeft(PC pc, Vec x, Vec y)
    649: {
    650:   PetscFunctionBegin;
    654:   PetscCheck(x != y, PetscObjectComm((PetscObject)pc), PETSC_ERR_ARG_IDN, "x and y must be different vectors");
    655:   if (pc->erroriffailure) PetscCall(VecValidValues_Internal(x, 2, PETSC_TRUE));
    656:   PetscCall(PCSetUp(pc));
    657:   PetscCall(VecLockReadPush(x));
    658:   PetscCall(PetscLogEventBegin(PC_ApplySymmetricLeft, pc, x, y, 0));
    659:   PetscUseTypeMethod(pc, applysymmetricleft, x, y);
    660:   PetscCall(PetscLogEventEnd(PC_ApplySymmetricLeft, pc, x, y, 0));
    661:   PetscCall(VecLockReadPop(x));
    662:   if (pc->erroriffailure) PetscCall(VecValidValues_Internal(y, 3, PETSC_FALSE));
    663:   PetscFunctionReturn(PETSC_SUCCESS);
    664: }

    666: /*@
    667:   PCApplySymmetricRight - Applies the right part of a symmetric preconditioner to a vector.

    669:   Collective

    671:   Input Parameters:
    672: + pc - the `PC` preconditioner context
    673: - x  - input vector

    675:   Output Parameter:
    676: . y - output vector

    678:   Level: developer

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

    683: .seealso: [](ch_ksp), `PC`, `PCApply()`, `PCApplySymmetricLeft()`
    684: @*/
    685: PetscErrorCode PCApplySymmetricRight(PC pc, Vec x, Vec y)
    686: {
    687:   PetscFunctionBegin;
    691:   PetscCheck(x != y, PetscObjectComm((PetscObject)pc), PETSC_ERR_ARG_IDN, "x and y must be different vectors");
    692:   if (pc->erroriffailure) PetscCall(VecValidValues_Internal(x, 2, PETSC_TRUE));
    693:   PetscCall(PCSetUp(pc));
    694:   PetscCall(VecLockReadPush(x));
    695:   PetscCall(PetscLogEventBegin(PC_ApplySymmetricRight, pc, x, y, 0));
    696:   PetscUseTypeMethod(pc, applysymmetricright, x, y);
    697:   PetscCall(PetscLogEventEnd(PC_ApplySymmetricRight, pc, x, y, 0));
    698:   PetscCall(VecLockReadPop(x));
    699:   if (pc->erroriffailure) PetscCall(VecValidValues_Internal(y, 3, PETSC_FALSE));
    700:   PetscFunctionReturn(PETSC_SUCCESS);
    701: }

    703: /*@
    704:   PCApplyTranspose - Applies the transpose of preconditioner to a vector.

    706:   Collective

    708:   Input Parameters:
    709: + pc - the `PC` preconditioner context
    710: - x  - input vector

    712:   Output Parameter:
    713: . y - output vector

    715:   Level: developer

    717:   Note:
    718:   For complex numbers this applies the non-Hermitian transpose.

    720:   Developer Note:
    721:   We need to implement a `PCApplyHermitianTranspose()`

    723: .seealso: [](ch_ksp), `PC`, `PCApply()`, `PCApplyBAorAB()`, `PCApplyBAorABTranspose()`, `PCApplyTransposeExists()`
    724: @*/
    725: PetscErrorCode PCApplyTranspose(PC pc, Vec x, Vec y)
    726: {
    727:   PetscFunctionBegin;
    731:   PetscCheck(x != y, PetscObjectComm((PetscObject)pc), PETSC_ERR_ARG_IDN, "x and y must be different vectors");
    732:   if (pc->erroriffailure) PetscCall(VecValidValues_Internal(x, 2, PETSC_TRUE));
    733:   PetscCall(PCSetUp(pc));
    734:   PetscCall(VecLockReadPush(x));
    735:   PetscCall(PetscLogEventBegin(PC_Apply, pc, x, y, 0));
    736:   PetscUseTypeMethod(pc, applytranspose, x, y);
    737:   PetscCall(PetscLogEventEnd(PC_Apply, pc, x, y, 0));
    738:   PetscCall(VecLockReadPop(x));
    739:   if (pc->erroriffailure) PetscCall(VecValidValues_Internal(y, 3, PETSC_FALSE));
    740:   PetscFunctionReturn(PETSC_SUCCESS);
    741: }

    743: /*@
    744:   PCApplyTransposeExists - Test whether the preconditioner has a transpose apply operation

    746:   Collective

    748:   Input Parameter:
    749: . pc - the `PC` preconditioner context

    751:   Output Parameter:
    752: . flg - `PETSC_TRUE` if a transpose operation is defined

    754:   Level: developer

    756: .seealso: [](ch_ksp), `PC`, `PCApplyTranspose()`
    757: @*/
    758: PetscErrorCode PCApplyTransposeExists(PC pc, PetscBool *flg)
    759: {
    760:   PetscFunctionBegin;
    762:   PetscAssertPointer(flg, 2);
    763:   if (pc->ops->applytranspose) *flg = PETSC_TRUE;
    764:   else *flg = PETSC_FALSE;
    765:   PetscFunctionReturn(PETSC_SUCCESS);
    766: }

    768: /*@
    769:   PCApplyBAorAB - Applies the preconditioner and operator to a vector. $y = B*A*x $ or $ y = A*B*x$.

    771:   Collective

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

    779:   Output Parameter:
    780: . y - output vector

    782:   Level: developer

    784:   Note:
    785:   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.
    786:   The specific `KSPSolve()` method must also be written to handle the post-solve "correction" for the diagonal scaling.

    788: .seealso: [](ch_ksp), `PC`, `PCApply()`, `PCApplyTranspose()`, `PCApplyBAorABTranspose()`
    789: @*/
    790: PetscErrorCode PCApplyBAorAB(PC pc, PCSide side, Vec x, Vec y, Vec work)
    791: {
    792:   PetscFunctionBegin;
    798:   PetscCheckSameComm(pc, 1, x, 3);
    799:   PetscCheckSameComm(pc, 1, y, 4);
    800:   PetscCheckSameComm(pc, 1, work, 5);
    801:   PetscCheck(x != y, PetscObjectComm((PetscObject)pc), PETSC_ERR_ARG_IDN, "x and y must be different vectors");
    802:   PetscCheck(side == PC_LEFT || side == PC_SYMMETRIC || side == PC_RIGHT, PetscObjectComm((PetscObject)pc), PETSC_ERR_ARG_OUTOFRANGE, "Side must be right, left, or symmetric");
    803:   PetscCheck(!pc->diagonalscale || side != PC_SYMMETRIC, PetscObjectComm((PetscObject)pc), PETSC_ERR_SUP, "Cannot include diagonal scaling with symmetric preconditioner application");
    804:   if (pc->erroriffailure) PetscCall(VecValidValues_Internal(x, 3, PETSC_TRUE));

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

    847: /*@
    848:   PCApplyBAorABTranspose - Applies the transpose of the preconditioner
    849:   and operator to a vector. That is, applies $B^T * A^T$ with left preconditioning,
    850:   NOT $(B*A)^T = A^T*B^T$.

    852:   Collective

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

    860:   Output Parameter:
    861: . y - output vector

    863:   Level: developer

    865:   Note:
    866:   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
    867:   defined by $B^T$. This is why this has the funny form that it computes $B^T * A^T$

    869: .seealso: [](ch_ksp), `PC`, `PCApply()`, `PCApplyTranspose()`, `PCApplyBAorAB()`
    870: @*/
    871: PetscErrorCode PCApplyBAorABTranspose(PC pc, PCSide side, Vec x, Vec y, Vec work)
    872: {
    873:   PetscFunctionBegin;
    878:   PetscCheck(x != y, PetscObjectComm((PetscObject)pc), PETSC_ERR_ARG_IDN, "x and y must be different vectors");
    879:   if (pc->erroriffailure) PetscCall(VecValidValues_Internal(x, 3, PETSC_TRUE));
    880:   if (pc->ops->applyBAtranspose) {
    881:     PetscUseTypeMethod(pc, applyBAtranspose, side, x, y, work);
    882:     if (pc->erroriffailure) PetscCall(VecValidValues_Internal(y, 4, PETSC_FALSE));
    883:     PetscFunctionReturn(PETSC_SUCCESS);
    884:   }
    885:   PetscCheck(side == PC_LEFT || side == PC_RIGHT, PetscObjectComm((PetscObject)pc), PETSC_ERR_ARG_OUTOFRANGE, "Side must be right or left");

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

    900: /*@
    901:   PCApplyRichardsonExists - Determines whether a particular preconditioner has a
    902:   built-in fast application of Richardson's method.

    904:   Not Collective

    906:   Input Parameter:
    907: . pc - the preconditioner

    909:   Output Parameter:
    910: . exists - `PETSC_TRUE` or `PETSC_FALSE`

    912:   Level: developer

    914: .seealso: [](ch_ksp), `PC`, `KSPRICHARDSON`, `PCApplyRichardson()`
    915: @*/
    916: PetscErrorCode PCApplyRichardsonExists(PC pc, PetscBool *exists)
    917: {
    918:   PetscFunctionBegin;
    920:   PetscAssertPointer(exists, 2);
    921:   if (pc->ops->applyrichardson) *exists = PETSC_TRUE;
    922:   else *exists = PETSC_FALSE;
    923:   PetscFunctionReturn(PETSC_SUCCESS);
    924: }

    926: /*@
    927:   PCApplyRichardson - Applies several steps of Richardson iteration with
    928:   the particular preconditioner. This routine is usually used by the
    929:   Krylov solvers and not the application code directly.

    931:   Collective

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

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

    948:   Level: developer

    950:   Notes:
    951:   Most preconditioners do not support this function. Use the command
    952:   `PCApplyRichardsonExists()` to determine if one does.

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

    957: .seealso: [](ch_ksp), `PC`, `PCApplyRichardsonExists()`
    958: @*/
    959: PetscErrorCode PCApplyRichardson(PC pc, Vec b, Vec y, Vec w, PetscReal rtol, PetscReal abstol, PetscReal dtol, PetscInt its, PetscBool guesszero, PetscInt *outits, PCRichardsonConvergedReason *reason)
    960: {
    961:   PetscFunctionBegin;
    966:   PetscCheck(b != y, PetscObjectComm((PetscObject)pc), PETSC_ERR_ARG_IDN, "b and y must be different vectors");
    967:   PetscCall(PCSetUp(pc));
    968:   PetscUseTypeMethod(pc, applyrichardson, b, y, w, rtol, abstol, dtol, its, guesszero, outits, reason);
    969:   PetscFunctionReturn(PETSC_SUCCESS);
    970: }

    972: /*@
    973:   PCSetFailedReason - Sets the reason a `PCSetUp()` failed or `PC_NOERROR` if it did not fail

    975:   Logically Collective

    977:   Input Parameters:
    978: + pc     - the `PC` preconditioner context
    979: - reason - the reason it failed

    981:   Level: advanced

    983: .seealso: [](ch_ksp), `PC`, `PCCreate()`, `PCApply()`, `PCDestroy()`, `PCFailedReason`
    984: @*/
    985: PetscErrorCode PCSetFailedReason(PC pc, PCFailedReason reason)
    986: {
    987:   PetscFunctionBegin;
    989:   pc->failedreason = reason;
    990:   PetscFunctionReturn(PETSC_SUCCESS);
    991: }

    993: /*@
    994:   PCGetFailedReason - Gets the reason a `PCSetUp()` failed or `PC_NOERROR` if it did not fail

    996:   Not Collective

    998:   Input Parameter:
    999: . pc - the `PC` preconditioner context

    1001:   Output Parameter:
    1002: . reason - the reason it failed

    1004:   Level: advanced

    1006:   Note:
    1007:   After a call to `KSPCheckDot()` or  `KSPCheckNorm()` inside a `KSPSolve()` or a call to `PCReduceFailedReason()`
    1008:   this is the maximum reason over all MPI processes in the `PC` communicator and hence logically collective.
    1009:   Otherwise it returns the local value.

    1011: .seealso: [](ch_ksp), `PC`, `PCCreate()`, `PCApply()`, `PCDestroy()`, `PCSetFailedReason()`, `PCFailedReason`
    1012: @*/
    1013: PetscErrorCode PCGetFailedReason(PC pc, PCFailedReason *reason)
    1014: {
    1015:   PetscFunctionBegin;
    1017:   *reason = pc->failedreason;
    1018:   PetscFunctionReturn(PETSC_SUCCESS);
    1019: }

    1021: /*@
    1022:   PCReduceFailedReason - Reduce the failed reason among the MPI processes that share the `PC`

    1024:   Collective

    1026:   Input Parameter:
    1027: . pc - the `PC` preconditioner context

    1029:   Level: advanced

    1031:   Note:
    1032:   Different MPI processes may have different reasons or no reason, see `PCGetFailedReason()`. This routine
    1033:   makes them have a common value (failure if any MPI process had a failure).

    1035: .seealso: [](ch_ksp), `PC`, `PCCreate()`, `PCApply()`, `PCDestroy()`, `PCGetFailedReason()`, `PCSetFailedReason()`, `PCFailedReason`
    1036: @*/
    1037: PetscErrorCode PCReduceFailedReason(PC pc)
    1038: {
    1039:   PetscInt buf;

    1041:   PetscFunctionBegin;
    1043:   buf = (PetscInt)pc->failedreason;
    1044:   PetscCallMPI(MPIU_Allreduce(MPI_IN_PLACE, &buf, 1, MPIU_INT, MPI_MAX, PetscObjectComm((PetscObject)pc)));
    1045:   pc->failedreason = (PCFailedReason)buf;
    1046:   PetscFunctionReturn(PETSC_SUCCESS);
    1047: }

    1049: /*
    1050:       a setupcall of 0 indicates never setup,
    1051:                      1 indicates has been previously setup
    1052:                     -1 indicates a PCSetUp() was attempted and failed
    1053: */
    1054: /*@
    1055:   PCSetUp - Prepares for the use of a preconditioner. Performs all the one-time operations needed before the preconditioner
    1056:   can be used with `PCApply()`

    1058:   Collective

    1060:   Input Parameter:
    1061: . pc - the `PC` preconditioner context

    1063:   Level: developer

    1065:   Notes:
    1066:   For example, for `PCLU` this will compute the factorization.

    1068:   This is called automatically by `KSPSetUp()` or `PCApply()` so rarely needs to be called directly.

    1070:   For nested preconditioners, such as `PCFIELDSPLIT` or `PCBJACOBI` this may not finish the construction of the preconditioner
    1071:   on the inner levels, the routine `PCSetUpOnBlocks()` may compute more of the preconditioner in those situations.

    1073: .seealso: [](ch_ksp), `PC`, `PCCreate()`, `PCApply()`, `PCDestroy()`, `KSPSetUp()`, `PCSetUpOnBlocks()`
    1074: @*/
    1075: PetscErrorCode PCSetUp(PC pc)
    1076: {
    1077:   const char      *def;
    1078:   PetscObjectState matstate, matnonzerostate;

    1080:   PetscFunctionBegin;
    1082:   PetscCheck(pc->mat, PetscObjectComm((PetscObject)pc), PETSC_ERR_ARG_WRONGSTATE, "Matrix must be set first");

    1084:   if (pc->setupcalled && pc->reusepreconditioner) {
    1085:     PetscCall(PetscInfo(pc, "Leaving PC with identical preconditioner since reuse preconditioner is set\n"));
    1086:     PetscFunctionReturn(PETSC_SUCCESS);
    1087:   }

    1089:   PetscCall(PetscObjectStateGet((PetscObject)pc->pmat, &matstate));
    1090:   PetscCall(MatGetNonzeroState(pc->pmat, &matnonzerostate));
    1091:   if (!pc->setupcalled) {
    1092:     //PetscCall(PetscInfo(pc, "Setting up PC for first time\n"));
    1093:     pc->flag = DIFFERENT_NONZERO_PATTERN;
    1094:   } else if (matstate == pc->matstate) PetscFunctionReturn(PETSC_SUCCESS);
    1095:   else {
    1096:     if (matnonzerostate != pc->matnonzerostate) {
    1097:       PetscCall(PetscInfo(pc, "Setting up PC with different nonzero pattern\n"));
    1098:       pc->flag = DIFFERENT_NONZERO_PATTERN;
    1099:     } else {
    1100:       //PetscCall(PetscInfo(pc, "Setting up PC with same nonzero pattern\n"));
    1101:       pc->flag = SAME_NONZERO_PATTERN;
    1102:     }
    1103:   }
    1104:   pc->matstate        = matstate;
    1105:   pc->matnonzerostate = matnonzerostate;

    1107:   if (!((PetscObject)pc)->type_name) {
    1108:     PetscCall(PCGetDefaultType_Private(pc, &def));
    1109:     PetscCall(PCSetType(pc, def));
    1110:   }

    1112:   PetscCall(MatSetErrorIfFailure(pc->pmat, pc->erroriffailure));
    1113:   PetscCall(MatSetErrorIfFailure(pc->mat, pc->erroriffailure));
    1114:   PetscCall(PetscLogEventBegin(PC_SetUp, pc, 0, 0, 0));
    1115:   if (pc->ops->setup) {
    1116:     PetscCall(PCLogEventsDeactivatePush());
    1117:     PetscUseTypeMethod(pc, setup);
    1118:     PetscCall(PCLogEventsDeactivatePop());
    1119:   }
    1120:   PetscCall(PetscLogEventEnd(PC_SetUp, pc, 0, 0, 0));
    1121:   if (pc->postsetup) PetscCall((*pc->postsetup)(pc));
    1122:   if (!pc->setupcalled) pc->setupcalled = PETSC_TRUE;
    1123:   PetscFunctionReturn(PETSC_SUCCESS);
    1124: }

    1126: /*@
    1127:   PCSetUpOnBlocks - Sets up the preconditioner for each block in
    1128:   the block Jacobi, overlapping Schwarz, and fieldsplit methods.

    1130:   Collective

    1132:   Input Parameter:
    1133: . pc - the `PC` preconditioner context

    1135:   Level: developer

    1137:   Notes:
    1138:   For nested preconditioners such as `PCBJACOBI`, `PCSetUp()` is not called on each sub-`KSP` when `PCSetUp()` is
    1139:   called on the outer `PC`, this routine ensures it is called.

    1141:   It calls `PCSetUp()` if not yet called.

    1143: .seealso: [](ch_ksp), `PC`, `PCSetUp()`, `PCCreate()`, `PCApply()`, `PCDestroy()`
    1144: @*/
    1145: PetscErrorCode PCSetUpOnBlocks(PC pc)
    1146: {
    1147:   PetscFunctionBegin;
    1149:   if (!pc->setupcalled) PetscCall(PCSetUp(pc)); /* "if" to prevent -info extra prints */
    1150:   if (!pc->ops->setuponblocks) PetscFunctionReturn(PETSC_SUCCESS);
    1151:   PetscCall(MatSetErrorIfFailure(pc->pmat, pc->erroriffailure));
    1152:   PetscCall(PetscLogEventBegin(PC_SetUpOnBlocks, pc, 0, 0, 0));
    1153:   PetscCall(PCLogEventsDeactivatePush());
    1154:   PetscUseTypeMethod(pc, setuponblocks);
    1155:   PetscCall(PCLogEventsDeactivatePop());
    1156:   PetscCall(PetscLogEventEnd(PC_SetUpOnBlocks, pc, 0, 0, 0));
    1157:   PetscFunctionReturn(PETSC_SUCCESS);
    1158: }

    1160: /*@C
    1161:   PCSetModifySubMatrices - Sets a user-defined routine for modifying the
    1162:   submatrices that arise within certain subdomain-based preconditioners such as `PCASM`

    1164:   Logically Collective

    1166:   Input Parameters:
    1167: + pc   - the `PC` preconditioner context
    1168: . func - routine for modifying the submatrices, see `PCModifySubMatricesFn`
    1169: - ctx  - optional user-defined context (may be `NULL`)

    1171:   Level: advanced

    1173:   Notes:
    1174:   The basic submatrices are extracted from the matrix used to construct the preconditioner as
    1175:   usual; the user can then alter these (for example, to set different boundary
    1176:   conditions for each submatrix) before they are used for the local solves.

    1178:   `PCSetModifySubMatrices()` MUST be called before `KSPSetUp()` and
    1179:   `KSPSolve()`.

    1181:   A routine set by `PCSetModifySubMatrices()` is currently called within
    1182:   `PCBJACOBI`, `PCASM`, `PCGASM`, and `PCHPDDM`.
    1183:   All other preconditioners ignore this routine.

    1185: .seealso: [](ch_ksp), `PC`, `PCModifySubMatricesFn`, `PCBJACOBI`, `PCASM`, `PCModifySubMatrices()`
    1186: @*/
    1187: PetscErrorCode PCSetModifySubMatrices(PC pc, PCModifySubMatricesFn *func, PetscCtx ctx)
    1188: {
    1189:   PetscFunctionBegin;
    1191:   pc->modifysubmatrices  = func;
    1192:   pc->modifysubmatricesP = ctx;
    1193:   PetscFunctionReturn(PETSC_SUCCESS);
    1194: }

    1196: /*@C
    1197:   PCModifySubMatrices - Calls an optional user-defined routine within
    1198:   certain preconditioners if one has been set with `PCSetModifySubMatrices()`.

    1200:   Collective

    1202:   Input Parameters:
    1203: + pc     - the `PC` preconditioner context
    1204: . nsub   - the number of local submatrices
    1205: . row    - an array of index sets that contain the global row numbers
    1206:          that comprise each local submatrix
    1207: . col    - an array of index sets that contain the global column numbers
    1208:          that comprise each local submatrix
    1209: . submat - array of local submatrices
    1210: - ctx    - optional user-defined context for private data for the
    1211:          user-defined routine (may be `NULL`)

    1213:   Output Parameter:
    1214: . submat - array of local submatrices (the entries of which may
    1215:             have been modified)

    1217:   Level: developer

    1219:   Note:
    1220:   The user should NOT generally call this routine, as it will
    1221:   automatically be called within certain preconditioners.

    1223: .seealso: [](ch_ksp), `PC`, `PCModifySubMatricesFn`, `PCSetModifySubMatrices()`
    1224: @*/
    1225: PetscErrorCode PCModifySubMatrices(PC pc, PetscInt nsub, const IS row[], const IS col[], Mat submat[], PetscCtx ctx)
    1226: {
    1227:   PetscFunctionBegin;
    1229:   if (!pc->modifysubmatrices) PetscFunctionReturn(PETSC_SUCCESS);
    1230:   PetscCall(PetscLogEventBegin(PC_ModifySubMatrices, pc, 0, 0, 0));
    1231:   PetscCall((*pc->modifysubmatrices)(pc, nsub, row, col, submat, ctx));
    1232:   PetscCall(PetscLogEventEnd(PC_ModifySubMatrices, pc, 0, 0, 0));
    1233:   PetscFunctionReturn(PETSC_SUCCESS);
    1234: }

    1236: /*@
    1237:   PCSetOperators - Sets the matrix associated with the linear system and
    1238:   a (possibly) different one from which the preconditioner will be constructed.

    1240:   Logically Collective

    1242:   Input Parameters:
    1243: + pc   - the `PC` preconditioner context
    1244: . Amat - the matrix that defines the linear system
    1245: - Pmat - the matrix to be used in constructing the preconditioner, usually the same as Amat.

    1247:   Level: advanced

    1249:   Notes:
    1250:   Using this routine directly is rarely needed, the preferred, and equivalent, usage is `KSPSetOperators()`.

    1252:   Passing a `NULL` for `Amat` or `Pmat` removes the matrix that is currently used.

    1254:   If you wish to replace either `Amat` or `Pmat` but leave the other one untouched then
    1255:   first call `KSPGetOperators()` to get the one you wish to keep, call `PetscObjectReference()`
    1256:   on it and then pass it back in in your call to `KSPSetOperators()`.

    1258:   More Notes about Repeated Solution of Linear Systems:
    1259:   PETSc does NOT reset the matrix entries of either `Amat` or `Pmat`
    1260:   to zero after a linear solve; the user is completely responsible for
    1261:   matrix assembly.  See the routine `MatZeroEntries()` if desiring to
    1262:   zero all elements of a matrix.

    1264: .seealso: [](ch_ksp), `PC`, `PCGetOperators()`, `MatZeroEntries()`
    1265:  @*/
    1266: PetscErrorCode PCSetOperators(PC pc, Mat Amat, Mat Pmat)
    1267: {
    1268:   PetscInt m1, n1, m2, n2;

    1270:   PetscFunctionBegin;
    1274:   if (Amat) PetscCheckSameComm(pc, 1, Amat, 2);
    1275:   if (Pmat) PetscCheckSameComm(pc, 1, Pmat, 3);
    1276:   if (pc->setupcalled && pc->mat && pc->pmat && Amat && Pmat) {
    1277:     PetscCall(MatGetLocalSize(Amat, &m1, &n1));
    1278:     PetscCall(MatGetLocalSize(pc->mat, &m2, &n2));
    1279:     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);
    1280:     PetscCall(MatGetLocalSize(Pmat, &m1, &n1));
    1281:     PetscCall(MatGetLocalSize(pc->pmat, &m2, &n2));
    1282:     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);
    1283:   }

    1285:   if (Pmat != pc->pmat) {
    1286:     /* changing the operator that defines the preconditioner thus reneed to clear current states so new preconditioner is built */
    1287:     pc->matnonzerostate = -1;
    1288:     pc->matstate        = -1;
    1289:   }

    1291:   /* reference first in case the matrices are the same */
    1292:   PetscCall(PetscObjectReference((PetscObject)Amat));
    1293:   PetscCall(MatDestroy(&pc->mat));
    1294:   PetscCall(PetscObjectReference((PetscObject)Pmat));
    1295:   PetscCall(MatDestroy(&pc->pmat));
    1296:   pc->mat  = Amat;
    1297:   pc->pmat = Pmat;
    1298:   PetscFunctionReturn(PETSC_SUCCESS);
    1299: }

    1301: /*@
    1302:   PCSetReusePreconditioner - reuse the current preconditioner even if the operator in the preconditioner `PC` has changed.

    1304:   Logically Collective

    1306:   Input Parameters:
    1307: + pc   - the `PC` preconditioner context
    1308: - flag - `PETSC_TRUE` do not compute a new preconditioner, `PETSC_FALSE` do compute a new preconditioner

    1310:   Level: intermediate

    1312:   Note:
    1313:   Normally if a matrix inside a `PC` changes the `PC` automatically updates itself using information from the changed matrix. This option
    1314:   prevents this.

    1316: .seealso: [](ch_ksp), `PC`, `PCGetOperators()`, `MatZeroEntries()`, `PCGetReusePreconditioner()`, `KSPSetReusePreconditioner()`
    1317:  @*/
    1318: PetscErrorCode PCSetReusePreconditioner(PC pc, PetscBool flag)
    1319: {
    1320:   PetscFunctionBegin;
    1323:   pc->reusepreconditioner = flag;
    1324:   PetscTryMethod(pc, "PCSetReusePreconditioner_C", (PC, PetscBool), (pc, flag));
    1325:   PetscFunctionReturn(PETSC_SUCCESS);
    1326: }

    1328: /*@
    1329:   PCGetReusePreconditioner - Determines if the `PC` reuses the current preconditioner even if the operator in the preconditioner has changed.

    1331:   Not Collective

    1333:   Input Parameter:
    1334: . pc - the `PC` preconditioner context

    1336:   Output Parameter:
    1337: . flag - `PETSC_TRUE` do not compute a new preconditioner, `PETSC_FALSE` do compute a new preconditioner

    1339:   Level: intermediate

    1341: .seealso: [](ch_ksp), `PC`, `PCGetOperators()`, `MatZeroEntries()`, `PCSetReusePreconditioner()`
    1342:  @*/
    1343: PetscErrorCode PCGetReusePreconditioner(PC pc, PetscBool *flag)
    1344: {
    1345:   PetscFunctionBegin;
    1347:   PetscAssertPointer(flag, 2);
    1348:   *flag = pc->reusepreconditioner;
    1349:   PetscFunctionReturn(PETSC_SUCCESS);
    1350: }

    1352: /*@
    1353:   PCGetOperators - Gets the matrix associated with the linear system and
    1354:   possibly a different one which is used to construct the preconditioner.

    1356:   Not Collective, though parallel `Mat`s are returned if `pc` is parallel

    1358:   Input Parameter:
    1359: . pc - the `PC` preconditioner context

    1361:   Output Parameters:
    1362: + Amat - the matrix defining the linear system
    1363: - Pmat - the matrix from which the preconditioner is constructed, usually the same as Amat.

    1365:   Level: intermediate

    1367:   Note:
    1368:   Does not increase the reference count of the matrices, so you should not destroy them

    1370:   Alternative usage: If the operators have NOT been set with `KSPSetOperators()`/`PCSetOperators()` then the operators
    1371:   are created in `PC` and returned to the user. In this case, if both operators
    1372:   mat and pmat are requested, two DIFFERENT operators will be returned. If
    1373:   only one is requested both operators in the PC will be the same (i.e. as
    1374:   if one had called `KSPSetOperators()`/`PCSetOperators()` with the same argument for both Mats).
    1375:   The user must set the sizes of the returned matrices and their type etc just
    1376:   as if the user created them with `MatCreate()`. For example,

    1378: .vb
    1379:          KSP/PCGetOperators(ksp/pc,&Amat,NULL); is equivalent to
    1380:            set size, type, etc of Amat

    1382:          MatCreate(comm,&mat);
    1383:          KSP/PCSetOperators(ksp/pc,Amat,Amat);
    1384:          PetscObjectDereference((PetscObject)mat);
    1385:            set size, type, etc of Amat
    1386: .ve

    1388:   and

    1390: .vb
    1391:          KSP/PCGetOperators(ksp/pc,&Amat,&Pmat); is equivalent to
    1392:            set size, type, etc of Amat and Pmat

    1394:          MatCreate(comm,&Amat);
    1395:          MatCreate(comm,&Pmat);
    1396:          KSP/PCSetOperators(ksp/pc,Amat,Pmat);
    1397:          PetscObjectDereference((PetscObject)Amat);
    1398:          PetscObjectDereference((PetscObject)Pmat);
    1399:            set size, type, etc of Amat and Pmat
    1400: .ve

    1402:   The rationale for this support is so that when creating a `TS`, `SNES`, or `KSP` the hierarchy
    1403:   of underlying objects (i.e. `SNES`, `KSP`, `PC`, `Mat`) and their lifespans can be completely
    1404:   managed by the top most level object (i.e. the `TS`, `SNES`, or `KSP`). Another way to look
    1405:   at this is when you create a `SNES` you do not NEED to create a `KSP` and attach it to
    1406:   the `SNES` object (the `SNES` object manages it for you). Similarly when you create a KSP
    1407:   you do not need to attach a `PC` to it (the `KSP` object manages the `PC` object for you).
    1408:   Thus, why should YOU have to create the `Mat` and attach it to the `SNES`/`KSP`/`PC`, when
    1409:   it can be created for you?

    1411: .seealso: [](ch_ksp), `PC`, `PCSetOperators()`, `KSPGetOperators()`, `KSPSetOperators()`, `PCGetOperatorsSet()`
    1412: @*/
    1413: PetscErrorCode PCGetOperators(PC pc, Mat *Amat, Mat *Pmat)
    1414: {
    1415:   PetscFunctionBegin;
    1417:   if (Amat) {
    1418:     if (!pc->mat) {
    1419:       if (pc->pmat && !Pmat) { /* Pmat has been set, but user did not request it, so use for Amat */
    1420:         pc->mat = pc->pmat;
    1421:         PetscCall(PetscObjectReference((PetscObject)pc->mat));
    1422:       } else { /* both Amat and Pmat are empty */
    1423:         PetscCall(MatCreate(PetscObjectComm((PetscObject)pc), &pc->mat));
    1424:         if (!Pmat) { /* user did NOT request Pmat, so make same as Amat */
    1425:           pc->pmat = pc->mat;
    1426:           PetscCall(PetscObjectReference((PetscObject)pc->pmat));
    1427:         }
    1428:       }
    1429:     }
    1430:     *Amat = pc->mat;
    1431:   }
    1432:   if (Pmat) {
    1433:     if (!pc->pmat) {
    1434:       if (pc->mat && !Amat) { /* Amat has been set but was not requested, so use for pmat */
    1435:         pc->pmat = pc->mat;
    1436:         PetscCall(PetscObjectReference((PetscObject)pc->pmat));
    1437:       } else {
    1438:         PetscCall(MatCreate(PetscObjectComm((PetscObject)pc), &pc->pmat));
    1439:         if (!Amat) { /* user did NOT request Amat, so make same as Pmat */
    1440:           pc->mat = pc->pmat;
    1441:           PetscCall(PetscObjectReference((PetscObject)pc->mat));
    1442:         }
    1443:       }
    1444:     }
    1445:     *Pmat = pc->pmat;
    1446:   }
    1447:   PetscFunctionReturn(PETSC_SUCCESS);
    1448: }

    1450: /*@
    1451:   PCGetOperatorsSet - Determines if the matrix associated with the linear system and
    1452:   possibly a different one associated with the preconditioner have been set in the `PC`.

    1454:   Not Collective, though the results on all processes should be the same

    1456:   Input Parameter:
    1457: . pc - the `PC` preconditioner context

    1459:   Output Parameters:
    1460: + mat  - the matrix associated with the linear system was set
    1461: - pmat - matrix associated with the preconditioner was set, usually the same

    1463:   Level: intermediate

    1465: .seealso: [](ch_ksp), `PC`, `PCSetOperators()`, `KSPGetOperators()`, `KSPSetOperators()`, `PCGetOperators()`
    1466: @*/
    1467: PetscErrorCode PCGetOperatorsSet(PC pc, PetscBool *mat, PetscBool *pmat)
    1468: {
    1469:   PetscFunctionBegin;
    1471:   if (mat) *mat = (pc->mat) ? PETSC_TRUE : PETSC_FALSE;
    1472:   if (pmat) *pmat = (pc->pmat) ? PETSC_TRUE : PETSC_FALSE;
    1473:   PetscFunctionReturn(PETSC_SUCCESS);
    1474: }

    1476: /*@
    1477:   PCFactorGetMatrix - Gets the factored matrix from the
    1478:   preconditioner context.  This routine is valid only for the `PCLU`,
    1479:   `PCILU`, `PCCHOLESKY`, and `PCICC` methods.

    1481:   Not Collective though `mat` is parallel if `pc` is parallel

    1483:   Input Parameter:
    1484: . pc - the `PC` preconditioner context

    1486:   Output Parameters:
    1487: . mat - the factored matrix

    1489:   Level: advanced

    1491:   Note:
    1492:   Does not increase the reference count for `mat` so DO NOT destroy it

    1494: .seealso: [](ch_ksp), `PC`, `PCLU`, `PCILU`, `PCCHOLESKY`, `PCICC`
    1495: @*/
    1496: PetscErrorCode PCFactorGetMatrix(PC pc, Mat *mat)
    1497: {
    1498:   PetscFunctionBegin;
    1500:   PetscAssertPointer(mat, 2);
    1501:   PetscCall(PCFactorSetUpMatSolverType(pc));
    1502:   PetscUseTypeMethod(pc, getfactoredmatrix, mat);
    1503:   PetscFunctionReturn(PETSC_SUCCESS);
    1504: }

    1506: /*@
    1507:   PCSetOptionsPrefix - Sets the prefix used for searching for all
    1508:   `PC` options in the database.

    1510:   Logically Collective

    1512:   Input Parameters:
    1513: + pc     - the `PC` preconditioner context
    1514: - prefix - the prefix string to prepend to all `PC` option requests

    1516:   Note:
    1517:   A hyphen (-) must NOT be given at the beginning of the prefix name.
    1518:   The first character of all runtime options is AUTOMATICALLY the
    1519:   hyphen.

    1521:   Level: advanced

    1523: .seealso: [](ch_ksp), `PC`, `PCSetFromOptions`, `PCAppendOptionsPrefix()`, `PCGetOptionsPrefix()`
    1524: @*/
    1525: PetscErrorCode PCSetOptionsPrefix(PC pc, const char prefix[])
    1526: {
    1527:   PetscFunctionBegin;
    1529:   PetscCall(PetscObjectSetOptionsPrefix((PetscObject)pc, prefix));
    1530:   PetscFunctionReturn(PETSC_SUCCESS);
    1531: }

    1533: /*@
    1534:   PCAppendOptionsPrefix - Appends to the prefix used for searching for all
    1535:   `PC` options in the database.

    1537:   Logically Collective

    1539:   Input Parameters:
    1540: + pc     - the `PC` preconditioner context
    1541: - prefix - the prefix string to prepend to all `PC` option requests

    1543:   Note:
    1544:   A hyphen (-) must NOT be given at the beginning of the prefix name.
    1545:   The first character of all runtime options is AUTOMATICALLY the
    1546:   hyphen.

    1548:   Level: advanced

    1550: .seealso: [](ch_ksp), `PC`, `PCSetFromOptions`, `PCSetOptionsPrefix()`, `PCGetOptionsPrefix()`
    1551: @*/
    1552: PetscErrorCode PCAppendOptionsPrefix(PC pc, const char prefix[])
    1553: {
    1554:   PetscFunctionBegin;
    1556:   PetscCall(PetscObjectAppendOptionsPrefix((PetscObject)pc, prefix));
    1557:   PetscFunctionReturn(PETSC_SUCCESS);
    1558: }

    1560: /*@
    1561:   PCGetOptionsPrefix - Gets the prefix used for searching for all
    1562:   PC options in the database.

    1564:   Not Collective

    1566:   Input Parameter:
    1567: . pc - the `PC` preconditioner context

    1569:   Output Parameter:
    1570: . prefix - pointer to the prefix string used, is returned

    1572:   Level: advanced

    1574: .seealso: [](ch_ksp), `PC`, `PCSetFromOptions`, `PCSetOptionsPrefix()`, `PCAppendOptionsPrefix()`
    1575: @*/
    1576: PetscErrorCode PCGetOptionsPrefix(PC pc, const char *prefix[])
    1577: {
    1578:   PetscFunctionBegin;
    1580:   PetscAssertPointer(prefix, 2);
    1581:   PetscCall(PetscObjectGetOptionsPrefix((PetscObject)pc, prefix));
    1582:   PetscFunctionReturn(PETSC_SUCCESS);
    1583: }

    1585: /*
    1586:    Indicates the right-hand side will be changed by KSPSolve(), this occurs for a few
    1587:   preconditioners including BDDC and Eisentat that transform the equations before applying
    1588:   the Krylov methods
    1589: */
    1590: PETSC_INTERN PetscErrorCode PCPreSolveChangeRHS(PC pc, PetscBool *change)
    1591: {
    1592:   PetscFunctionBegin;
    1594:   PetscAssertPointer(change, 2);
    1595:   *change = PETSC_FALSE;
    1596:   PetscTryMethod(pc, "PCPreSolveChangeRHS_C", (PC, PetscBool *), (pc, change));
    1597:   PetscFunctionReturn(PETSC_SUCCESS);
    1598: }

    1600: /*@
    1601:   PCPreSolve - Optional pre-solve phase, intended for any preconditioner-specific actions that must be performed before
    1602:   the iterative solve itself. Used in conjunction with `PCPostSolve()`

    1604:   Collective

    1606:   Input Parameters:
    1607: + pc  - the `PC` preconditioner context
    1608: - ksp - the Krylov subspace context

    1610:   Level: developer

    1612:   Notes:
    1613:   `KSPSolve()` calls this directly, so is rarely called by the user.

    1615:   Certain preconditioners, such as the `PCType` of `PCEISENSTAT`, change the formulation of the linear system to be solved iteratively.
    1616:   This function performs that transformation. `PCPostSolve()` then transforms the system back to its original form after the solve.
    1617:   `PCPostSolve()` also transforms the resulting solution of the transformed system to the solution of the original problem.

    1619:   `KSPSetPostSolve()` provides an alternative way to provide such transformations.

    1621: .seealso: [](ch_ksp), `PC`, `PCPostSolve()`, `KSP`, `PCSetPostSetUp()`, `KSPSetPreSolve()`, `KSPSetPostSolve()`
    1622: @*/
    1623: PetscErrorCode PCPreSolve(PC pc, KSP ksp)
    1624: {
    1625:   Vec x, rhs;

    1627:   PetscFunctionBegin;
    1630:   pc->presolvedone++;
    1631:   PetscCheck(pc->presolvedone <= 2, PetscObjectComm((PetscObject)pc), PETSC_ERR_SUP, "Cannot embed PCPreSolve() more than twice");
    1632:   PetscCall(KSPGetSolution(ksp, &x));
    1633:   PetscCall(KSPGetRhs(ksp, &rhs));
    1634:   PetscTryTypeMethod(pc, presolve, ksp, rhs, x);
    1635:   PetscFunctionReturn(PETSC_SUCCESS);
    1636: }

    1638: /*@C
    1639:   PCSetPostSetUp - Sets function called at the end of `PCSetUp()` to adjust the computed preconditioner

    1641:   Logically Collective

    1643:   Input Parameters:
    1644: + pc        - the preconditioner object
    1645: - postsetup - the function to call after `PCSetUp()`

    1647:   Calling sequence of `postsetup`:
    1648: . pc - the `PC` context

    1650:   Level: developer

    1652: .seealso: [](ch_ksp), `PC`, `PCSetUp()`
    1653: @*/
    1654: PetscErrorCode PCSetPostSetUp(PC pc, PetscErrorCode (*postsetup)(PC pc))
    1655: {
    1656:   PetscFunctionBegin;
    1658:   pc->postsetup = postsetup;
    1659:   PetscFunctionReturn(PETSC_SUCCESS);
    1660: }

    1662: /*@
    1663:   PCPostSolve - Optional post-solve phase, intended for any
    1664:   preconditioner-specific actions that must be performed after
    1665:   the iterative solve itself.

    1667:   Collective

    1669:   Input Parameters:
    1670: + pc  - the `PC` preconditioner context
    1671: - ksp - the `KSP` Krylov subspace context

    1673:   Example Usage:
    1674: .vb
    1675:     PCPreSolve(pc,ksp);
    1676:     KSPSolve(ksp,b,x);
    1677:     PCPostSolve(pc,ksp);
    1678: .ve

    1680:   Level: developer

    1682:   Note:
    1683:   `KSPSolve()` calls this routine directly, so it is rarely called by the user.

    1685: .seealso: [](ch_ksp), `PC`, `KSPSetPostSolve()`, `KSPSetPreSolve()`, `PCPreSolve()`, `KSPSolve()`
    1686: @*/
    1687: PetscErrorCode PCPostSolve(PC pc, KSP ksp)
    1688: {
    1689:   Vec x, rhs;

    1691:   PetscFunctionBegin;
    1694:   pc->presolvedone--;
    1695:   PetscCall(KSPGetSolution(ksp, &x));
    1696:   PetscCall(KSPGetRhs(ksp, &rhs));
    1697:   PetscTryTypeMethod(pc, postsolve, ksp, rhs, x);
    1698:   PetscFunctionReturn(PETSC_SUCCESS);
    1699: }

    1701: /*@
    1702:   PCLoad - Loads a `PC` that has been stored in binary  with `PCView()`.

    1704:   Collective

    1706:   Input Parameters:
    1707: + newdm  - the newly loaded `PC`, this needs to have been created with `PCCreate()` or
    1708:            some related function before a call to `PCLoad()`.
    1709: - viewer - binary file viewer `PETSCVIEWERBINARY`, obtained from `PetscViewerBinaryOpen()`

    1711:   Level: intermediate

    1713:   Note:
    1714:   The type is determined by the data in the file, any `PCType` set into the `PC` before this call is ignored.

    1716: .seealso: [](ch_ksp), `PC`, `PetscViewerBinaryOpen()`, `PCView()`, `MatLoad()`, `VecLoad()`, `PETSCVIEWERBINARY`
    1717: @*/
    1718: PetscErrorCode PCLoad(PC newdm, PetscViewer viewer)
    1719: {
    1720:   PetscBool isbinary;
    1721:   PetscInt  classid;
    1722:   char      type[256];

    1724:   PetscFunctionBegin;
    1727:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary));
    1728:   PetscCheck(isbinary, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Invalid viewer; open viewer with PetscViewerBinaryOpen()");

    1730:   PetscCall(PetscViewerBinaryRead(viewer, &classid, 1, NULL, PETSC_INT));
    1731:   PetscCheck(classid == PC_FILE_CLASSID, PetscObjectComm((PetscObject)newdm), PETSC_ERR_ARG_WRONG, "Not PC next in file");
    1732:   PetscCall(PetscViewerBinaryRead(viewer, type, 256, NULL, PETSC_CHAR));
    1733:   PetscCall(PCSetType(newdm, type));
    1734:   PetscTryTypeMethod(newdm, load, viewer);
    1735:   PetscFunctionReturn(PETSC_SUCCESS);
    1736: }

    1738: #include <petscdraw.h>
    1739: #if defined(PETSC_HAVE_SAWS)
    1740: #include <petscviewersaws.h>
    1741: #endif

    1743: /*@
    1744:   PCViewFromOptions - View (print or provide information about) the `PC`, based on options in the options database

    1746:   Collective

    1748:   Input Parameters:
    1749: + A    - the `PC` context
    1750: . obj  - Optional object that provides the options prefix
    1751: - name - command line option name

    1753:   Level: developer

    1755: .seealso: [](ch_ksp), `PC`, `PCView`, `PetscObjectViewFromOptions()`, `PCCreate()`
    1756: @*/
    1757: PetscErrorCode PCViewFromOptions(PC A, PetscObject obj, const char name[])
    1758: {
    1759:   PetscFunctionBegin;
    1761:   PetscCall(PetscObjectViewFromOptions((PetscObject)A, obj, name));
    1762:   PetscFunctionReturn(PETSC_SUCCESS);
    1763: }

    1765: /*@
    1766:   PCView - Prints information about the `PC`

    1768:   Collective

    1770:   Input Parameters:
    1771: + pc     - the `PC` preconditioner context
    1772: - viewer - optional `PetscViewer` visualization context

    1774:   Level: intermediate

    1776:   Notes:
    1777:   The available visualization contexts include
    1778: +     `PETSC_VIEWER_STDOUT_SELF` - standard output (default)
    1779: -     `PETSC_VIEWER_STDOUT_WORLD` - synchronized standard
    1780:   output where only the first processor opens
    1781:   the file. All other processors send their
    1782:   data to the first processor to print.

    1784:   The user can open an alternative visualization contexts with
    1785:   `PetscViewerASCIIOpen()` (output to a specified file).

    1787: .seealso: [](ch_ksp), `PC`, `PetscViewer`, `PetscViewerType`, `KSPView()`, `PetscViewerASCIIOpen()`
    1788: @*/
    1789: PetscErrorCode PCView(PC pc, PetscViewer viewer)
    1790: {
    1791:   PCType            cstr;
    1792:   PetscViewerFormat format;
    1793:   PetscBool         isascii, isstring, isbinary, isdraw, pop = PETSC_FALSE;
    1794: #if defined(PETSC_HAVE_SAWS)
    1795:   PetscBool issaws;
    1796: #endif

    1798:   PetscFunctionBegin;
    1800:   if (!viewer) PetscCall(PetscViewerASCIIGetStdout(PetscObjectComm((PetscObject)pc), &viewer));
    1802:   PetscCheckSameComm(pc, 1, viewer, 2);

    1804:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &isascii));
    1805:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERSTRING, &isstring));
    1806:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary));
    1807:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERDRAW, &isdraw));
    1808: #if defined(PETSC_HAVE_SAWS)
    1809:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERSAWS, &issaws));
    1810: #endif

    1812:   if (isascii) {
    1813:     PetscCall(PetscObjectPrintClassNamePrefixType((PetscObject)pc, viewer));
    1814:     if (!pc->setupcalled) PetscCall(PetscViewerASCIIPrintf(viewer, "  PC has not been set up so information may be incomplete\n"));
    1815:     PetscCall(PetscViewerASCIIPushTab(viewer));
    1816:     PetscTryTypeMethod(pc, view, viewer);
    1817:     PetscCall(PetscViewerASCIIPopTab(viewer));
    1818:     if (pc->mat) {
    1819:       PetscCall(PetscViewerGetFormat(viewer, &format));
    1820:       if (format != PETSC_VIEWER_ASCII_INFO_DETAIL) {
    1821:         PetscCall(PetscViewerPushFormat(viewer, PETSC_VIEWER_ASCII_INFO));
    1822:         pop = PETSC_TRUE;
    1823:       }
    1824:       if (pc->pmat == pc->mat) {
    1825:         PetscCall(PetscViewerASCIIPrintf(viewer, "  linear system matrix, which is also used to construct the preconditioner:\n"));
    1826:         PetscCall(PetscViewerASCIIPushTab(viewer));
    1827:         PetscCall(MatView(pc->mat, viewer));
    1828:         PetscCall(PetscViewerASCIIPopTab(viewer));
    1829:       } else {
    1830:         if (pc->pmat) {
    1831:           PetscCall(PetscViewerASCIIPrintf(viewer, "  linear system matrix, followed by the matrix used to construct the preconditioner:\n"));
    1832:         } else {
    1833:           PetscCall(PetscViewerASCIIPrintf(viewer, "  linear system matrix:\n"));
    1834:         }
    1835:         PetscCall(PetscViewerASCIIPushTab(viewer));
    1836:         PetscCall(MatView(pc->mat, viewer));
    1837:         if (pc->pmat) PetscCall(MatView(pc->pmat, viewer));
    1838:         PetscCall(PetscViewerASCIIPopTab(viewer));
    1839:       }
    1840:       if (pop) PetscCall(PetscViewerPopFormat(viewer));
    1841:     }
    1842:   } else if (isstring) {
    1843:     PetscCall(PCGetType(pc, &cstr));
    1844:     PetscCall(PetscViewerStringSPrintf(viewer, " PCType: %-7.7s", cstr));
    1845:     PetscTryTypeMethod(pc, view, viewer);
    1846:     if (pc->mat) PetscCall(MatView(pc->mat, viewer));
    1847:     if (pc->pmat && pc->pmat != pc->mat) PetscCall(MatView(pc->pmat, viewer));
    1848:   } else if (isbinary) {
    1849:     PetscInt    classid = PC_FILE_CLASSID;
    1850:     MPI_Comm    comm;
    1851:     PetscMPIInt rank;
    1852:     char        type[256];

    1854:     PetscCall(PetscObjectGetComm((PetscObject)pc, &comm));
    1855:     PetscCallMPI(MPI_Comm_rank(comm, &rank));
    1856:     if (rank == 0) {
    1857:       PetscCall(PetscViewerBinaryWrite(viewer, &classid, 1, PETSC_INT));
    1858:       PetscCall(PetscStrncpy(type, ((PetscObject)pc)->type_name, 256));
    1859:       PetscCall(PetscViewerBinaryWrite(viewer, type, 256, PETSC_CHAR));
    1860:     }
    1861:     PetscTryTypeMethod(pc, view, viewer);
    1862:   } else if (isdraw) {
    1863:     PetscDraw draw;
    1864:     char      str[25];
    1865:     PetscReal x, y, bottom, h;
    1866:     PetscInt  n;

    1868:     PetscCall(PetscViewerDrawGetDraw(viewer, 0, &draw));
    1869:     PetscCall(PetscDrawGetCurrentPoint(draw, &x, &y));
    1870:     if (pc->mat) {
    1871:       PetscCall(MatGetSize(pc->mat, &n, NULL));
    1872:       PetscCall(PetscSNPrintf(str, 25, "PC: %s (%" PetscInt_FMT ")", ((PetscObject)pc)->type_name, n));
    1873:     } else {
    1874:       PetscCall(PetscSNPrintf(str, 25, "PC: %s", ((PetscObject)pc)->type_name));
    1875:     }
    1876:     PetscCall(PetscDrawStringBoxed(draw, x, y, PETSC_DRAW_RED, PETSC_DRAW_BLACK, str, NULL, &h));
    1877:     bottom = y - h;
    1878:     PetscCall(PetscDrawPushCurrentPoint(draw, x, bottom));
    1879:     PetscTryTypeMethod(pc, view, viewer);
    1880:     PetscCall(PetscDrawPopCurrentPoint(draw));
    1881: #if defined(PETSC_HAVE_SAWS)
    1882:   } else if (issaws) {
    1883:     PetscMPIInt rank;

    1885:     PetscCall(PetscObjectName((PetscObject)pc));
    1886:     PetscCallMPI(MPI_Comm_rank(PETSC_COMM_WORLD, &rank));
    1887:     if (!((PetscObject)pc)->amsmem && rank == 0) PetscCall(PetscObjectViewSAWs((PetscObject)pc, viewer));
    1888:     if (pc->mat) PetscCall(MatView(pc->mat, viewer));
    1889:     if (pc->pmat && pc->pmat != pc->mat) PetscCall(MatView(pc->pmat, viewer));
    1890: #endif
    1891:   }
    1892:   PetscFunctionReturn(PETSC_SUCCESS);
    1893: }

    1895: /*@C
    1896:   PCRegister -  Adds a method (`PCType`) to the PETSc preconditioner package.

    1898:   Not collective. No Fortran Support

    1900:   Input Parameters:
    1901: + sname    - name of a new user-defined solver
    1902: - function - routine to create the method context which will be stored in a `PC` when `PCSetType()` is called

    1904:   Example Usage:
    1905: .vb
    1906:    PCRegister("my_solver", MySolverCreate);
    1907: .ve

    1909:   Then, your solver can be chosen with the procedural interface via
    1910: .vb
    1911:   PCSetType(pc, "my_solver")
    1912: .ve
    1913:   or at runtime via the option
    1914: .vb
    1915:   -pc_type my_solver
    1916: .ve

    1918:   Level: advanced

    1920:   Note:
    1921:   A simpler alternative to using `PCRegister()` for an application specific preconditioner is to use a `PC` of `PCType` `PCSHELL` and
    1922:   provide your customizations with `PCShellSetContext()` and `PCShellSetApply()`

    1924:   `PCRegister()` may be called multiple times to add several user-defined preconditioners.

    1926: .seealso: [](ch_ksp), `PC`, `PCType`, `PCRegisterAll()`, `PCSetType()`, `PCShellSetContext()`, `PCShellSetApply()`, `PCSHELL`
    1927: @*/
    1928: PetscErrorCode PCRegister(const char sname[], PetscErrorCode (*function)(PC))
    1929: {
    1930:   PetscFunctionBegin;
    1931:   PetscCall(PCInitializePackage());
    1932:   PetscCall(PetscFunctionListAdd(&PCList, sname, function));
    1933:   PetscFunctionReturn(PETSC_SUCCESS);
    1934: }

    1936: static PetscErrorCode MatMult_PC(Mat A, Vec X, Vec Y)
    1937: {
    1938:   PC pc;

    1940:   PetscFunctionBegin;
    1941:   PetscCall(MatShellGetContext(A, &pc));
    1942:   PetscCall(PCApply(pc, X, Y));
    1943:   PetscFunctionReturn(PETSC_SUCCESS);
    1944: }

    1946: /*@
    1947:   PCComputeOperator - Computes the explicit preconditioned operator as a matrix `Mat`.

    1949:   Collective

    1951:   Input Parameters:
    1952: + pc      - the `PC` preconditioner object
    1953: - mattype - the `MatType` to be used for the operator

    1955:   Output Parameter:
    1956: . mat - the explicit preconditioned operator

    1958:   Level: advanced

    1960:   Note:
    1961:   This computation is done by applying the operators to columns of the identity matrix.
    1962:   This routine is costly in general, and is recommended for use only with relatively small systems.
    1963:   Currently, this routine uses a dense matrix format when `mattype` == `NULL`

    1965:   Developer Note:
    1966:   This should be called `PCCreateExplicitOperator()`

    1968: .seealso: [](ch_ksp), `PC`, `KSPComputeOperator()`, `MatType`
    1969: @*/
    1970: PetscErrorCode PCComputeOperator(PC pc, MatType mattype, Mat *mat)
    1971: {
    1972:   PetscInt N, M, m, n;
    1973:   Mat      A, Apc;

    1975:   PetscFunctionBegin;
    1977:   PetscAssertPointer(mat, 3);
    1978:   PetscCall(PCGetOperators(pc, &A, NULL));
    1979:   PetscCall(MatGetLocalSize(A, &m, &n));
    1980:   PetscCall(MatGetSize(A, &M, &N));
    1981:   PetscCall(MatCreateShell(PetscObjectComm((PetscObject)pc), m, n, M, N, pc, &Apc));
    1982:   PetscCall(MatShellSetOperation(Apc, MATOP_MULT, (PetscErrorCodeFn *)MatMult_PC));
    1983:   PetscCall(MatComputeOperator(Apc, mattype, mat));
    1984:   PetscCall(MatDestroy(&Apc));
    1985:   PetscFunctionReturn(PETSC_SUCCESS);
    1986: }

    1988: /*@
    1989:   PCSetCoordinates - sets the coordinates of all the nodes (degrees of freedom in the vector) on the local process

    1991:   Collective

    1993:   Input Parameters:
    1994: + pc     - the `PC` preconditioner context
    1995: . dim    - the dimension of the coordinates 1, 2, or 3
    1996: . nloc   - the blocked size of the coordinates array
    1997: - coords - the coordinates array

    1999:   Level: intermediate

    2001:   Notes:
    2002:   `coords` is an array of the dim coordinates for the nodes on
    2003:   the local processor, of size `dim`*`nloc`.
    2004:   If there are 108 equations (dofs) on a processor
    2005:   for a 3d displacement finite element discretization of elasticity (so
    2006:   that there are nloc = 36 = 108/3 nodes) then the array must have 108
    2007:   double precision values (ie, 3 * 36).  These x y z coordinates
    2008:   should be ordered for nodes 0 to N-1 like so: [ 0.x, 0.y, 0.z, 1.x,
    2009:   ... , N-1.z ].

    2011:   The information provided here can be used by some preconditioners, such as `PCGAMG`, to produce a better preconditioner.
    2012:   See also  `MatSetNearNullSpace()`.

    2014: .seealso: [](ch_ksp), `PC`, `MatSetNearNullSpace()`
    2015: @*/
    2016: PetscErrorCode PCSetCoordinates(PC pc, PetscInt dim, PetscInt nloc, PetscReal coords[])
    2017: {
    2018:   PetscFunctionBegin;
    2021:   PetscTryMethod(pc, "PCSetCoordinates_C", (PC, PetscInt, PetscInt, PetscReal[]), (pc, dim, nloc, coords));
    2022:   PetscFunctionReturn(PETSC_SUCCESS);
    2023: }

    2025: /*@
    2026:   PCGetInterpolations - Gets interpolation matrices for all levels (except level 0)

    2028:   Logically Collective

    2030:   Input Parameter:
    2031: . pc - the precondition context

    2033:   Output Parameters:
    2034: + num_levels     - the number of levels
    2035: - interpolations - the interpolation matrices (size of `num_levels`-1)

    2037:   Level: advanced

    2039:   Developer Note:
    2040:   Why is this here instead of in `PCMG` etc?

    2042: .seealso: [](ch_ksp), `PC`, `PCMG`, `PCMGGetRestriction()`, `PCMGSetInterpolation()`, `PCMGGetInterpolation()`, `PCGetCoarseOperators()`
    2043: @*/
    2044: PetscErrorCode PCGetInterpolations(PC pc, PetscInt *num_levels, Mat *interpolations[])
    2045: {
    2046:   PetscFunctionBegin;
    2048:   PetscAssertPointer(num_levels, 2);
    2049:   PetscAssertPointer(interpolations, 3);
    2050:   PetscUseMethod(pc, "PCGetInterpolations_C", (PC, PetscInt *, Mat *[]), (pc, num_levels, interpolations));
    2051:   PetscFunctionReturn(PETSC_SUCCESS);
    2052: }

    2054: /*@
    2055:   PCGetCoarseOperators - Gets coarse operator matrices for all levels (except the finest level)

    2057:   Logically Collective

    2059:   Input Parameter:
    2060: . pc - the precondition context

    2062:   Output Parameters:
    2063: + num_levels      - the number of levels
    2064: - coarseOperators - the coarse operator matrices (size of `num_levels`-1)

    2066:   Level: advanced

    2068:   Developer Note:
    2069:   Why is this here instead of in `PCMG` etc?

    2071: .seealso: [](ch_ksp), `PC`, `PCMG`, `PCMGGetRestriction()`, `PCMGSetInterpolation()`, `PCMGGetRScale()`, `PCMGGetInterpolation()`, `PCGetInterpolations()`
    2072: @*/
    2073: PetscErrorCode PCGetCoarseOperators(PC pc, PetscInt *num_levels, Mat *coarseOperators[])
    2074: {
    2075:   PetscFunctionBegin;
    2077:   PetscAssertPointer(num_levels, 2);
    2078:   PetscAssertPointer(coarseOperators, 3);
    2079:   PetscUseMethod(pc, "PCGetCoarseOperators_C", (PC, PetscInt *, Mat *[]), (pc, num_levels, coarseOperators));
    2080:   PetscFunctionReturn(PETSC_SUCCESS);
    2081: }