Actual source code: petscksp.h

  1: /*
  2:    Defines the interface functions for the Krylov subspace accelerators.
  3: */
  4: #pragma once

  6: #include <petscpc.h>

  8: /* SUBMANSEC = KSP */

 10: PETSC_EXTERN PetscErrorCode KSPInitializePackage(void);
 11: PETSC_EXTERN PetscErrorCode KSPFinalizePackage(void);

 13: /*S
 14:    KSP - Abstract PETSc object that manages the linear solves in PETSc (even those such as direct factorization-based solvers that
 15:          do not use Krylov accelerators).

 17:    Level: beginner

 19:    Notes:
 20:    When a direct solver is used, but no Krylov solver is used, the `KSP` object is still used but with a
 21:    `KSPType` of `KSPPREONLY` (or equivalently `KSPNONE`), meaning that only application of the preconditioner is used as the linear solver.

 23:    Use `KSPSetType()` or the options database key `-ksp_type` to set the specific Krylov solver algorithm to use with a given `KSP` object

 25:    The `PC` object is used to control preconditioners in PETSc.

 27:   `KSP` can also be used to solve some least squares problems (over or under-determined linear systems), using, for example, `KSPLSQR`, see `PETSCREGRESSORLINEAR`
 28:   for additional methods that can be used to solve least squares problems and other linear regressions).

 30: .seealso: [](doc_linsolve), [](ch_ksp), `KSPCreate()`, `KSPSetType()`, `KSPType`, `SNES`, `TS`, `PC`, `KSP`, `KSPDestroy()`, `KSPCG`, `KSPGMRES`
 31: S*/
 32: typedef struct _p_KSP *KSP;

 34: /*J
 35:    KSPType - String with the name of a PETSc Krylov method. These are all the Krylov solvers that PETSc provides.

 37:    Level: beginner

 39: .seealso: [](doc_linsolve), [](ch_ksp), `KSPSetType()`, `KSP`, `KSPRegister()`, `KSPCreate()`, `KSPSetFromOptions()`
 40: J*/
 41: typedef const char *KSPType;
 42: #define KSPRICHARDSON "richardson"
 43: #define KSPCHEBYSHEV  "chebyshev"
 44: #define KSPCG         "cg"
 45: #define KSPGROPPCG    "groppcg"
 46: #define KSPPIPECG     "pipecg"
 47: #define KSPPIPECGRR   "pipecgrr"
 48: #define KSPPIPELCG    "pipelcg"
 49: #define KSPPIPEPRCG   "pipeprcg"
 50: #define KSPPIPECG2    "pipecg2"
 51: #define KSPCGNE       "cgne"
 52: #define KSPNASH       "nash"
 53: #define KSPSTCG       "stcg"
 54: #define KSPGLTR       "gltr"
 55: #define KSPCGNASH     PETSC_DEPRECATED_MACRO(3, 11, 0, "KSPNASH", ) "nash"
 56: #define KSPCGSTCG     PETSC_DEPRECATED_MACRO(3, 11, 0, "KSPSTCG", ) "stcg"
 57: #define KSPCGGLTR     PETSC_DEPRECATED_MACRO(3, 11, 0, "KSPSGLTR", ) "gltr"
 58: #define KSPFCG        "fcg"
 59: #define KSPPIPEFCG    "pipefcg"
 60: #define KSPGMRES      "gmres"
 61: #define KSPPIPEFGMRES "pipefgmres"
 62: #define KSPFGMRES     "fgmres"
 63: #define KSPLGMRES     "lgmres"
 64: #define KSPDGMRES     "dgmres"
 65: #define KSPPGMRES     "pgmres"
 66: #define KSPTCQMR      "tcqmr"
 67: #define KSPBCGS       "bcgs"
 68: #define KSPIBCGS      "ibcgs"
 69: #define KSPQMRCGS     "qmrcgs"
 70: #define KSPFBCGS      "fbcgs"
 71: #define KSPFBCGSR     "fbcgsr"
 72: #define KSPBCGSL      "bcgsl"
 73: #define KSPPIPEBCGS   "pipebcgs"
 74: #define KSPCGS        "cgs"
 75: #define KSPTFQMR      "tfqmr"
 76: #define KSPCR         "cr"
 77: #define KSPPIPECR     "pipecr"
 78: #define KSPLSQR       "lsqr"
 79: #define KSPPREONLY    "preonly"
 80: #define KSPNONE       "none"
 81: #define KSPQCG        "qcg"
 82: #define KSPBICG       "bicg"
 83: #define KSPMINRES     "minres"
 84: #define KSPSYMMLQ     "symmlq"
 85: #define KSPLCD        "lcd"
 86: #define KSPPYTHON     "python"
 87: #define KSPGCR        "gcr"
 88: #define KSPPIPEGCR    "pipegcr"
 89: #define KSPTSIRM      "tsirm"
 90: #define KSPCGLS       "cgls"
 91: #define KSPFETIDP     "fetidp"
 92: #define KSPHPDDM      "hpddm"
 93: #define KSPIDR        "idr"

 95: /* Logging support */
 96: PETSC_EXTERN PetscClassId KSP_CLASSID;
 97: PETSC_EXTERN PetscClassId KSPGUESS_CLASSID;
 98: PETSC_EXTERN PetscClassId DMKSP_CLASSID;

100: PETSC_EXTERN PetscErrorCode KSPCreate(MPI_Comm, KSP *);
101: PETSC_EXTERN PetscErrorCode KSPSetType(KSP, KSPType);
102: PETSC_EXTERN PetscErrorCode KSPGetType(KSP, KSPType *);
103: PETSC_EXTERN PetscErrorCode KSPSetUp(KSP);
104: PETSC_EXTERN PetscErrorCode KSPSetUpOnBlocks(KSP);
105: PETSC_EXTERN PetscErrorCode KSPSolve(KSP, Vec, Vec);
106: PETSC_EXTERN PetscErrorCode KSPSolveTranspose(KSP, Vec, Vec);
107: PETSC_EXTERN PetscErrorCode KSPSetUseExplicitTranspose(KSP, PetscBool);
108: PETSC_EXTERN PetscErrorCode KSPMatSolve(KSP, Mat, Mat);
109: PETSC_EXTERN PetscErrorCode KSPMatSolveTranspose(KSP, Mat, Mat);
110: PETSC_EXTERN PetscErrorCode KSPSetMatSolveBatchSize(KSP, PetscInt);
111: PETSC_DEPRECATED_FUNCTION(3, 15, 0, "KSPSetMatSolveBatchSize()", ) static inline PetscErrorCode KSPSetMatSolveBlockSize(KSP ksp, PetscInt n)
112: {
113:   return KSPSetMatSolveBatchSize(ksp, n);
114: }
115: PETSC_EXTERN PetscErrorCode KSPGetMatSolveBatchSize(KSP, PetscInt *);
116: PETSC_DEPRECATED_FUNCTION(3, 15, 0, "KSPGetMatSolveBatchSize()", ) static inline PetscErrorCode KSPGetMatSolveBlockSize(KSP ksp, PetscInt *n)
117: {
118:   return KSPGetMatSolveBatchSize(ksp, n);
119: }
120: PETSC_EXTERN PetscErrorCode KSPReset(KSP);
121: PETSC_EXTERN PetscErrorCode KSPResetViewers(KSP);
122: PETSC_EXTERN PetscErrorCode KSPDestroy(KSP *);
123: PETSC_EXTERN PetscErrorCode KSPSetReusePreconditioner(KSP, PetscBool);
124: PETSC_EXTERN PetscErrorCode KSPGetReusePreconditioner(KSP, PetscBool *);
125: PETSC_EXTERN PetscErrorCode KSPSetSkipPCSetFromOptions(KSP, PetscBool);
126: PETSC_EXTERN PetscErrorCode KSPCheckSolve(KSP, PC, Vec);

128: PETSC_EXTERN PetscFunctionList KSPList;
129: PETSC_EXTERN PetscFunctionList KSPGuessList;
130: PETSC_EXTERN PetscFunctionList KSPMonitorList;
131: PETSC_EXTERN PetscFunctionList KSPMonitorCreateList;
132: PETSC_EXTERN PetscFunctionList KSPMonitorDestroyList;
133: PETSC_EXTERN PetscErrorCode    KSPRegister(const char[], PetscErrorCode (*)(KSP));

135: /*S
136:   KSPMonitorRegisterFn - A function prototype for functions provided to `KSPMonitorRegister()`

138:   Calling Sequence:
139: + ksp   - iterative solver obtained from `KSPCreate()`
140: . it    - iteration number
141: . rnorm - (estimated) 2-norm of (preconditioned) residual
142: - ctx   - `PetscViewerAndFormat` object

144:   Level: beginner

146:   Note:
147:   This is a `KSPMonitorFn` specialized for a context of `PetscViewerAndFormat`

149: .seealso: [](ch_snes), `KSP`, `KSPMonitorSet()`, `KSPMonitorRegister()`, `KSPMonitorFn`, `KSPMonitorRegisterCreateFn`, `KSPMonitorRegisterDestroyFn`
150: S*/
151: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPMonitorRegisterFn(KSP ksp, PetscInt it, PetscReal rnorm, PetscViewerAndFormat *ctx);

153: /*S
154:   KSPMonitorRegisterCreateFn - A function prototype for functions that do the creation when provided to `KSPMonitorRegister()`

156:   Calling Sequence:
157: + viewer - the viewer to be used with the `KSPMonitorRegisterFn`
158: . format - the format of the viewer
159: . ctx    - a context for the monitor
160: - result - a `PetscViewerAndFormat` object

162:   Level: beginner

164: .seealso: [](ch_snes), `KSPMonitorRegisterFn`, `KSP`, `KSPMonitorSet()`, `KSPMonitorRegister()`, `KSPMonitorFn`, `KSPMonitorRegisterDestroyFn`
165: S*/
166: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPMonitorRegisterCreateFn(PetscViewer viewer, PetscViewerFormat format, PetscCtx ctx, PetscViewerAndFormat **result);

168: /*S
169:   KSPMonitorRegisterDestroyFn - A function prototype for functions that do the after use destruction when provided to `KSPMonitorRegister()`

171:   Calling Sequence:
172: . vf - a `PetscViewerAndFormat` object to be destroyed, including any context

174:   Level: beginner

176: .seealso: [](ch_snes), `KSPMonitorRegisterFn`, `KSP`, `KSPMonitorSet()`, `KSPMonitorRegister()`, `KSPMonitorFn`, `KSPMonitorRegisterCreateFn`
177: S*/
178: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPMonitorRegisterDestroyFn(PetscViewerAndFormat **result);

180: PETSC_EXTERN PetscErrorCode KSPMonitorRegister(const char[], PetscViewerType, PetscViewerFormat, KSPMonitorRegisterFn *, KSPMonitorRegisterCreateFn *, KSPMonitorRegisterDestroyFn *);

182: PETSC_EXTERN PetscErrorCode KSPSetPCSide(KSP, PCSide);
183: PETSC_EXTERN PetscErrorCode KSPGetPCSide(KSP, PCSide *);
184: PETSC_EXTERN PetscErrorCode KSPSetTolerances(KSP, PetscReal, PetscReal, PetscReal, PetscInt);
185: PETSC_EXTERN PetscErrorCode KSPGetTolerances(KSP, PetscReal *, PetscReal *, PetscReal *, PetscInt *);
186: PETSC_EXTERN PetscErrorCode KSPSetMinimumIterations(KSP, PetscInt);
187: PETSC_EXTERN PetscErrorCode KSPGetMinimumIterations(KSP, PetscInt *);
188: PETSC_EXTERN PetscErrorCode KSPSetInitialGuessNonzero(KSP, PetscBool);
189: PETSC_EXTERN PetscErrorCode KSPGetInitialGuessNonzero(KSP, PetscBool *);
190: PETSC_EXTERN PetscErrorCode KSPSetErrorIfNotConverged(KSP, PetscBool);
191: PETSC_EXTERN PetscErrorCode KSPGetErrorIfNotConverged(KSP, PetscBool *);
192: PETSC_EXTERN PetscErrorCode KSPSetComputeEigenvalues(KSP, PetscBool);
193: PETSC_EXTERN PetscErrorCode KSPSetComputeRitz(KSP, PetscBool);
194: PETSC_EXTERN PetscErrorCode KSPGetComputeEigenvalues(KSP, PetscBool *);
195: PETSC_EXTERN PetscErrorCode KSPSetComputeSingularValues(KSP, PetscBool);
196: PETSC_EXTERN PetscErrorCode KSPGetComputeSingularValues(KSP, PetscBool *);
197: PETSC_EXTERN PetscErrorCode KSPGetRhs(KSP, Vec *);
198: PETSC_EXTERN PetscErrorCode KSPGetSolution(KSP, Vec *);
199: PETSC_EXTERN PetscErrorCode KSPGetResidualNorm(KSP, PetscReal *);
200: PETSC_EXTERN PetscErrorCode KSPGetIterationNumber(KSP, PetscInt *);
201: PETSC_EXTERN PetscErrorCode KSPGetTotalIterations(KSP, PetscInt *);
202: PETSC_EXTERN PetscErrorCode KSPCreateVecs(KSP, PetscInt, Vec **, PetscInt, Vec **);
203: PETSC_DEPRECATED_FUNCTION(3, 6, 0, "KSPCreateVecs()", ) static inline PetscErrorCode KSPGetVecs(KSP ksp, PetscInt n, Vec **x, PetscInt m, Vec **y)
204: {
205:   return KSPCreateVecs(ksp, n, x, m, y);
206: }

208: /*S
209:   KSPPSolveFn - A function prototype for functions provided to `KSPSetPreSolve()` and `KSPSetPostSolve()`

211:   Calling Sequence:
212: + ksp - the `KSP` context
213: . rhs - the right-hand side vector
214: . x   - the solution vector
215: - ctx - optional context that was provided with `KSPSetPreSolve()` or `KSPSetPostSolve()`

217:   Level: intermediate

219: .seealso: [](ch_snes), `KSP`, `KSPSetPreSolve()`, `KSPSetPostSolve()`, `PCShellPSolveFn`
220: S*/
221: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPPSolveFn(KSP ksp, Vec rhs, Vec x, PetscCtx ctx);

223: PETSC_EXTERN PetscErrorCode KSPSetPreSolve(KSP, KSPPSolveFn *, PetscCtx);
224: PETSC_EXTERN PetscErrorCode KSPSetPostSolve(KSP, KSPPSolveFn *, PetscCtx);
225: PETSC_EXTERN PetscErrorCode KSPPreSolve(KSP, Vec, Vec);
226: PETSC_EXTERN PetscErrorCode KSPPostSolve(KSP, Vec, Vec);

228: PETSC_EXTERN PetscErrorCode KSPSetPC(KSP, PC);
229: PETSC_EXTERN PetscErrorCode KSPGetPC(KSP, PC *);
230: PETSC_EXTERN PetscErrorCode KSPSetNestLevel(KSP, PetscInt);
231: PETSC_EXTERN PetscErrorCode KSPGetNestLevel(KSP, PetscInt *);

233: /*S
234:   KSPMonitorFn - A function prototype for functions provided to `KSPMonitorSet()`

236:   Calling Sequence:
237: + ksp   - iterative solver obtained from `KSPCreate()`
238: . it    - iteration number
239: . rnorm - (estimated) 2-norm of (preconditioned) residual
240: - ctx   - optional monitoring context, as provided with `KSPMonitorSet()`

242:   Level: beginner

244: .seealso: [](ch_snes), `KSP`, `KSPMonitorSet()`
245: S*/
246: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPMonitorFn(KSP ksp, PetscInt it, PetscReal rnorm, PetscCtx ctx);

248: PETSC_EXTERN PetscErrorCode KSPMonitor(KSP, PetscInt, PetscReal);
249: PETSC_EXTERN PetscErrorCode KSPMonitorSet(KSP, KSPMonitorFn *, PetscCtx, PetscCtxDestroyFn *);
250: PETSC_EXTERN PetscErrorCode KSPMonitorCancel(KSP);
251: PETSC_EXTERN PetscErrorCode KSPGetMonitorContext(KSP, PetscCtxRt);
252: PETSC_EXTERN PetscErrorCode KSPGetResidualHistory(KSP, const PetscReal *[], PetscInt *);
253: PETSC_EXTERN PetscErrorCode KSPSetResidualHistory(KSP, PetscReal[], PetscCount, PetscBool);
254: PETSC_EXTERN PetscErrorCode KSPGetErrorHistory(KSP, const PetscReal *[], PetscInt *);
255: PETSC_EXTERN PetscErrorCode KSPSetErrorHistory(KSP, PetscReal[], PetscCount, PetscBool);

257: PETSC_EXTERN PetscErrorCode KSPBuildSolutionDefault(KSP, Vec, Vec *);
258: PETSC_EXTERN PetscErrorCode KSPBuildResidualDefault(KSP, Vec, Vec, Vec *);
259: PETSC_EXTERN PetscErrorCode KSPDestroyDefault(KSP);
260: PETSC_EXTERN PetscErrorCode KSPSetWorkVecs(KSP, PetscInt);

262: PETSC_EXTERN PetscErrorCode PCKSPGetKSP(PC, KSP *);
263: PETSC_EXTERN PetscErrorCode PCKSPSetKSP(PC, KSP);
264: PETSC_EXTERN PetscErrorCode PCBJacobiGetSubKSP(PC, PetscInt *, PetscInt *, KSP *[]);
265: PETSC_EXTERN PetscErrorCode PCASMGetSubKSP(PC, PetscInt *, PetscInt *, KSP *[]);
266: PETSC_EXTERN PetscErrorCode PCGASMGetSubKSP(PC, PetscInt *, PetscInt *, KSP *[]);
267: PETSC_EXTERN PetscErrorCode PCPatchGetSubKSP(PC, PetscInt *, KSP *[]);
268: PETSC_EXTERN PetscErrorCode PCFieldSplitGetSubKSP(PC, PetscInt *, KSP *[]);
269: PETSC_EXTERN PetscErrorCode PCFieldSplitSchurGetSubKSP(PC, PetscInt *, KSP *[]);
270: PETSC_EXTERN PetscErrorCode PCMGGetSmoother(PC, PetscInt, KSP *);
271: PETSC_EXTERN PetscErrorCode PCMGGetSmootherDown(PC, PetscInt, KSP *);
272: PETSC_EXTERN PetscErrorCode PCMGGetSmootherUp(PC, PetscInt, KSP *);
273: PETSC_EXTERN PetscErrorCode PCMGGetCoarseSolve(PC, KSP *);
274: PETSC_EXTERN PetscErrorCode PCGalerkinGetKSP(PC, KSP *);
275: PETSC_EXTERN PetscErrorCode PCDeflationGetCoarseKSP(PC, KSP *);

277: /*S
278:   PCMGCoarseSpaceConstructorFn - A function prototype for functions registered with `PCMGRegisterCoarseSpaceConstructor()`

280:   Calling Sequence:
281: + pc        - The `PC` object
282: . l         - The multigrid level, 0 is the coarse level
283: . dm        - The `DM` for this level
284: . smooth    - The level smoother
285: . Nc        - The size of the coarse space
286: . initGuess - Basis for an initial guess for the space
287: - coarseSp  - A basis for the computed coarse space

289:   Level: beginner

291: .seealso: [](ch_ksp), `PCMGRegisterCoarseSpaceConstructor()`, `PCMGGetCoarseSpaceConstructor()`
292: S*/
293: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode PCMGCoarseSpaceConstructorFn(PC pc, PetscInt l, DM dm, KSP smooth, PetscInt Nc, Mat initGuess, Mat *coarseSp);

295: PETSC_EXTERN PetscFunctionList PCMGCoarseList;
296: PETSC_EXTERN PetscErrorCode    PCMGRegisterCoarseSpaceConstructor(const char[], PCMGCoarseSpaceConstructorFn *);
297: PETSC_EXTERN PetscErrorCode    PCMGGetCoarseSpaceConstructor(const char[], PCMGCoarseSpaceConstructorFn **);

299: PETSC_EXTERN PetscErrorCode KSPBuildSolution(KSP, Vec, Vec *);
300: PETSC_EXTERN PetscErrorCode KSPBuildResidual(KSP, Vec, Vec, Vec *);

302: /*E
303:   KSPChebyshevKind - Which kind of Chebyshev polynomial to use with `KSPCHEBYSHEV`

305:   Values:
306: + `KSP_CHEBYSHEV_FIRST`      - "classic" first-kind Chebyshev polynomial
307: . `KSP_CHEBYSHEV_FOURTH`     - fourth-kind Chebyshev polynomial
308: - `KSP_CHEBYSHEV_OPT_FOURTH` - optimized fourth-kind Chebyshev polynomial

310:   Level: intermediate

312: .seealso: [](ch_ksp), `KSPCHEBYSHEV`, `KSPChebyshevSetKind()`, `KSPChebyshevGetKind()`
313: E*/
314: typedef enum {
315:   KSP_CHEBYSHEV_FIRST,
316:   KSP_CHEBYSHEV_FOURTH,
317:   KSP_CHEBYSHEV_OPT_FOURTH
318: } KSPChebyshevKind;

320: PETSC_EXTERN PetscErrorCode KSPRichardsonSetScale(KSP, PetscReal);
321: PETSC_EXTERN PetscErrorCode KSPRichardsonSetSelfScale(KSP, PetscBool);
322: PETSC_EXTERN PetscErrorCode KSPChebyshevSetEigenvalues(KSP, PetscReal, PetscReal);
323: PETSC_EXTERN PetscErrorCode KSPChebyshevEstEigSet(KSP, PetscReal, PetscReal, PetscReal, PetscReal);
324: PETSC_EXTERN PetscErrorCode KSPChebyshevEstEigSetUseNoisy(KSP, PetscBool);
325: PETSC_EXTERN PetscErrorCode KSPChebyshevSetKind(KSP, KSPChebyshevKind);
326: PETSC_EXTERN PetscErrorCode KSPChebyshevGetKind(KSP, KSPChebyshevKind *);
327: PETSC_EXTERN PetscErrorCode KSPChebyshevEstEigGetKSP(KSP, KSP *);
328: PETSC_EXTERN PetscErrorCode KSPComputeExtremeSingularValues(KSP, PetscReal *, PetscReal *);
329: PETSC_EXTERN PetscErrorCode KSPComputeEigenvalues(KSP, PetscInt, PetscReal[], PetscReal[], PetscInt *);
330: PETSC_EXTERN PetscErrorCode KSPComputeEigenvaluesExplicitly(KSP, PetscInt, PetscReal[], PetscReal[]);
331: PETSC_EXTERN PetscErrorCode KSPComputeRitz(KSP, PetscBool, PetscBool, PetscInt *, Vec[], PetscReal[], PetscReal[]);

333: /*E
334:   KSPFCDTruncationType - Define how stored directions are used to orthogonalize in flexible conjugate directions (FCD) methods

336:   Values:
337: + `KSP_FCD_TRUNC_TYPE_STANDARD` - uses all (up to `mmax`) stored directions
338: - `KSP_FCD_TRUNC_TYPE_NOTAY`    - uses the last `max(1,mod(i,mmax))` stored directions at iteration i = 0, 1, ...

340:    Level: intermediate

342:   Note:
343:   Function such as `KSPFCGSetMmax()`, `KSPPIPEGCRSetNMax()`, `KSPPIPEGCRSetNMax()`, and `KSPPIPEFCGSetNMax()` may be
344:   used to provide `nmax` or they may be provided with the option database.

346: .seealso: [](ch_ksp), `KSP`, `KSPFCG`, `KSPPIPEFCG`, `KSPPIPEGCR`, `KSPFCGSetTruncationType()`, `KSPFCGGetTruncationType()`,
347:           `KSPPIPEGCRSetTruncationType()`, `KSPPIPEGCRGetTruncationType()`,
348:           `KSPFCGSetMmax()`, `KSPPIPEGCRSetNMax()`, `KSPPIPEGCRGetNMax()`, `KSPPIPEFCGGetNMax()`
349: E*/
350: typedef enum {
351:   KSP_FCD_TRUNC_TYPE_STANDARD,
352:   KSP_FCD_TRUNC_TYPE_NOTAY
353: } KSPFCDTruncationType;
354: PETSC_EXTERN const char *const KSPFCDTruncationTypes[];

356: PETSC_EXTERN PetscErrorCode KSPFCGSetMmax(KSP, PetscInt);
357: PETSC_EXTERN PetscErrorCode KSPFCGGetMmax(KSP, PetscInt *);
358: PETSC_EXTERN PetscErrorCode KSPFCGSetNprealloc(KSP, PetscInt);
359: PETSC_EXTERN PetscErrorCode KSPFCGGetNprealloc(KSP, PetscInt *);
360: PETSC_EXTERN PetscErrorCode KSPFCGSetTruncationType(KSP, KSPFCDTruncationType);
361: PETSC_EXTERN PetscErrorCode KSPFCGGetTruncationType(KSP, KSPFCDTruncationType *);

363: PETSC_EXTERN PetscErrorCode KSPPIPEFCGSetMmax(KSP, PetscInt);
364: PETSC_EXTERN PetscErrorCode KSPPIPEFCGGetMmax(KSP, PetscInt *);
365: PETSC_EXTERN PetscErrorCode KSPPIPEFCGSetNprealloc(KSP, PetscInt);
366: PETSC_EXTERN PetscErrorCode KSPPIPEFCGGetNprealloc(KSP, PetscInt *);
367: PETSC_EXTERN PetscErrorCode KSPPIPEFCGSetTruncationType(KSP, KSPFCDTruncationType);
368: PETSC_EXTERN PetscErrorCode KSPPIPEFCGGetTruncationType(KSP, KSPFCDTruncationType *);

370: PETSC_EXTERN PetscErrorCode KSPPIPEGCRSetMmax(KSP, PetscInt);
371: PETSC_EXTERN PetscErrorCode KSPPIPEGCRGetMmax(KSP, PetscInt *);
372: PETSC_EXTERN PetscErrorCode KSPPIPEGCRSetNprealloc(KSP, PetscInt);
373: PETSC_EXTERN PetscErrorCode KSPPIPEGCRGetNprealloc(KSP, PetscInt *);
374: PETSC_EXTERN PetscErrorCode KSPPIPEGCRSetTruncationType(KSP, KSPFCDTruncationType);
375: PETSC_EXTERN PetscErrorCode KSPPIPEGCRGetTruncationType(KSP, KSPFCDTruncationType *);
376: PETSC_EXTERN PetscErrorCode KSPPIPEGCRSetUnrollW(KSP, PetscBool);
377: PETSC_EXTERN PetscErrorCode KSPPIPEGCRGetUnrollW(KSP, PetscBool *);

379: /*S
380:   KSPFlexibleModifyPCFn - A prototype of a function used to modify the preconditioner during the use of flexible `KSP` methods, such as `KSPFGMRES`

382:   Calling Sequence:
383: + ksp       - the `KSP` context being used.
384: . total_its - the total number of iterations that have occurred.
385: . local_its - the number of iterations since last restart if applicable
386: . res_norm  - the current residual norm
387: - ctx       - optional context variable set with `KSPFlexibleSetModifyPC()`

389:   Level: beginner

391: .seealso: [](ch_ksp), `KSP`, `KSPFlexibleSetModifyPC()`
392: S*/
393: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPFlexibleModifyPCFn(KSP ksp, PetscInt total_its, PetscInt local_its, PetscReal res_norm, PetscCtx ctx);

395: PETSC_EXTERN PetscErrorCode KSPFlexibleSetModifyPC(KSP, KSPFlexibleModifyPCFn *, PetscCtx, PetscCtxDestroyFn *);

397: PETSC_DEPRECATED_FUNCTION(3, 25, 0, "KSPFlexibleSetModifyPC()", ) static inline PetscErrorCode KSPPIPEGCRSetModifyPC(KSP ksp, KSPFlexibleModifyPCFn *fun, PetscCtx ctx, PetscCtxDestroyFn *dfun)
398: {
399:   return KSPFlexibleSetModifyPC(ksp, fun, ctx, dfun);
400: }

402: PETSC_EXTERN PetscErrorCode KSPGMRESSetRestart(KSP, PetscInt);
403: PETSC_EXTERN PetscErrorCode KSPGMRESGetRestart(KSP, PetscInt *);
404: PETSC_EXTERN PetscErrorCode KSPGMRESSetHapTol(KSP, PetscReal);
405: PETSC_EXTERN PetscErrorCode KSPGMRESSetBreakdownTolerance(KSP, PetscReal);

407: PETSC_EXTERN PetscErrorCode KSPGMRESSetPreAllocateVectors(KSP);

409: PETSC_EXTERN PetscErrorCode KSPLGMRESSetAugDim(KSP, PetscInt);
410: PETSC_EXTERN PetscErrorCode KSPLGMRESSetConstant(KSP);

412: PETSC_EXTERN PetscErrorCode KSPPIPEFGMRESSetShift(KSP, PetscScalar);

414: PETSC_EXTERN PetscErrorCode KSPGCRSetRestart(KSP, PetscInt);
415: PETSC_EXTERN PetscErrorCode KSPGCRGetRestart(KSP, PetscInt *);

417: PETSC_EXTERN PetscErrorCode KSPIDRSetS(KSP, PetscInt);
418: PETSC_EXTERN PetscErrorCode KSPIDRGetS(KSP, PetscInt *);
419: PETSC_EXTERN PetscErrorCode KSPIDRSetCosine(KSP, PetscReal);
420: PETSC_EXTERN PetscErrorCode KSPIDRGetCosine(KSP, PetscReal *);
421: PETSC_EXTERN PetscErrorCode KSPIDRSetRandom(KSP, PetscRandom);
422: PETSC_EXTERN PetscErrorCode KSPIDRGetRandom(KSP, PetscRandom *);

424: PETSC_DEPRECATED_FUNCTION(3, 25, 0, "KSPFlexibleSetModifyPC()", ) static inline PetscErrorCode KSPGCRSetModifyPC(KSP ksp, KSPFlexibleModifyPCFn *fun, PetscCtx ctx, PetscCtxDestroyFn *dfun)
425: {
426:   return KSPFlexibleSetModifyPC(ksp, fun, ctx, dfun);
427: }

429: PETSC_EXTERN PetscErrorCode KSPMINRESSetRadius(KSP, PetscReal);
430: PETSC_EXTERN PetscErrorCode KSPMINRESGetUseQLP(KSP, PetscBool *);
431: PETSC_EXTERN PetscErrorCode KSPMINRESSetUseQLP(KSP, PetscBool);

433: PETSC_EXTERN PetscErrorCode KSPFETIDPGetInnerBDDC(KSP, PC *);
434: PETSC_EXTERN PetscErrorCode KSPFETIDPSetInnerBDDC(KSP, PC);
435: PETSC_EXTERN PetscErrorCode KSPFETIDPGetInnerKSP(KSP, KSP *);
436: PETSC_EXTERN PetscErrorCode KSPFETIDPSetPressureOperator(KSP, Mat);

438: PETSC_EXTERN PetscErrorCode KSPHPDDMSetDeflationMat(KSP, Mat);
439: PETSC_EXTERN PetscErrorCode KSPHPDDMGetDeflationMat(KSP, Mat *);
440: #if PetscDefined(HAVE_HPDDM)
441: PETSC_DEPRECATED_FUNCTION(3, 18, 0, "KSPHPDDMSetDeflationMat()", ) static inline PetscErrorCode KSPHPDDMSetDeflationSpace(KSP ksp, Mat U)
442: {
443:   return KSPHPDDMSetDeflationMat(ksp, U);
444: }
445: PETSC_DEPRECATED_FUNCTION(3, 18, 0, "KSPHPDDMGetDeflationMat()", ) static inline PetscErrorCode KSPHPDDMGetDeflationSpace(KSP ksp, Mat *U)
446: {
447:   return KSPHPDDMGetDeflationMat(ksp, U);
448: }
449: #endif
450: PETSC_DEPRECATED_FUNCTION(3, 14, 0, "KSPMatSolve()", ) static inline PetscErrorCode KSPHPDDMMatSolve(KSP ksp, Mat B, Mat X)
451: {
452:   return KSPMatSolve(ksp, B, X);
453: }
454: /*E
455:     KSPHPDDMType - Type of Krylov method used by `KSPHPDDM`

457:     Values:
458: +   `KSP_HPDDM_TYPE_GMRES` (default) - Generalized Minimal Residual method
459: .   `KSP_HPDDM_TYPE_BGMRES`          - block GMRES
460: .   `KSP_HPDDM_TYPE_CG`              - Conjugate Gradient
461: .   `KSP_HPDDM_TYPE_BCG`             - block CG
462: .   `KSP_HPDDM_TYPE_GCRODR`          - Generalized Conjugate Residual method with inner Orthogonalization and Deflated Restarting
463: .   `KSP_HPDDM_TYPE_BGCRODR`         - block GCRODR
464: .   `KSP_HPDDM_TYPE_BFBCG`           - breakdown-free BCG
465: -   `KSP_HPDDM_TYPE_PREONLY`         - apply the preconditioner only

467:     Level: intermediate

469: .seealso: [](ch_ksp), `KSPHPDDM`, `KSPHPDDMSetType()`
470: E*/
471: typedef enum {
472:   KSP_HPDDM_TYPE_GMRES   = 0,
473:   KSP_HPDDM_TYPE_BGMRES  = 1,
474:   KSP_HPDDM_TYPE_CG      = 2,
475:   KSP_HPDDM_TYPE_BCG     = 3,
476:   KSP_HPDDM_TYPE_GCRODR  = 4,
477:   KSP_HPDDM_TYPE_BGCRODR = 5,
478:   KSP_HPDDM_TYPE_BFBCG   = 6,
479:   KSP_HPDDM_TYPE_PREONLY = 7
480: } KSPHPDDMType;
481: PETSC_EXTERN const char *const KSPHPDDMTypes[];

483: PETSC_EXTERN PetscErrorCode KSPHPDDMSetType(KSP, KSPHPDDMType);
484: PETSC_EXTERN PetscErrorCode KSPHPDDMGetType(KSP, KSPHPDDMType *);

486: /*S
487:   KSPOrthogonalizationFn - A function prototype for functions provided to `KSPOrthogonalizationSet()`

489:   Calling Sequence:
490: + ksp - the `KSP` context
491: . V   - array of previously computed orthonormal vectors
492: . n   - number of vectors
493: . x   - vector to be orthogonalized (may be `NULL`)
494: - h   - computed orthogonalization coefficients

496:   Level: intermediate

498:   Note:
499:   If no `x` is given, then the vector to be orthogonalized is assumed to be located at `V[n]`.

501: .seealso: [](ch_ksp), `KSP`, `KSPOrthogonalizationSet()`
502: S*/
503: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPOrthogonalizationFn(KSP ksp, Vec V[], PetscInt n, Vec x, PetscScalar h[]);

505: PETSC_EXTERN PetscErrorCode         KSPOrthogonalizationSet(KSP, KSPOrthogonalizationFn *);
506: PETSC_EXTERN PetscErrorCode         KSPOrthogonalizationGet(KSP, KSPOrthogonalizationFn **);
507: PETSC_EXTERN KSPOrthogonalizationFn KSPOrthogonalizationClassicalGramSchmidt;
508: PETSC_EXTERN KSPOrthogonalizationFn KSPOrthogonalizationModifiedGramSchmidt;

510: #define KSP_GMRES_CGS_REFINE_NEVER_DEPRECATED    KSP_GMRES_CGS_REFINE_NEVER PETSC_DEPRECATED_ENUM(3, 26, 0, "KSP_ORTHOGONALIZATION_CGS_REFINE_NEVER", )
511: #define KSP_GMRES_CGS_REFINE_IFNEEDED_DEPRECATED KSP_GMRES_CGS_REFINE_IFNEEDED PETSC_DEPRECATED_ENUM(3, 26, 0, "KSP_ORTHOGONALIZATION_CGS_REFINE_IFNEEDED", )
512: #define KSP_GMRES_CGS_REFINE_ALWAYS_DEPRECATED   KSP_GMRES_CGS_REFINE_ALWAYS PETSC_DEPRECATED_ENUM(3, 26, 0, "KSP_ORTHOGONALIZATION_CGS_REFINE_ALWAYS", )
513: /*E
514:    KSPOrthogonalizationCGSRefinementType - How the classical (unmodified) Gram-Schmidt is performed in the GMRES solvers

516:    Values:
517: +  `KSP_ORTHOGONALIZATION_CGS_REFINE_NEVER`    - one step of classical Gram-Schmidt
518: .  `KSP_ORTHOGONALIZATION_CGS_REFINE_IFNEEDED` - a second step is performed if the first step does not satisfy some criteria
519: -  `KSP_ORTHOGONALIZATION_CGS_REFINE_ALWAYS`   - always perform two steps

521:    Level: advanced

523: .seealso: [](ch_ksp), `KSP`, `KSPGMRES`, `KSPOrthogonalizationClassicalGramSchmidt()`, `KSPOrthogonalizationSet()`,
524:           `KSPOrthogonalizationGet()`,
525:           `KSPOrthogonalizationSetCGSRefinementType()`, `KSPOrthogonalizationGetCGSRefinementType()`, `KSPOrthogonalizationModifiedGramSchmidt()`
526: E*/
527: typedef enum {
528:   KSP_ORTHOGONALIZATION_CGS_REFINE_NEVER    = 0,
529:   KSP_ORTHOGONALIZATION_CGS_REFINE_IFNEEDED = 1,
530:   KSP_ORTHOGONALIZATION_CGS_REFINE_ALWAYS   = 2,
531:   KSP_GMRES_CGS_REFINE_NEVER_DEPRECATED     = 0,
532:   KSP_GMRES_CGS_REFINE_IFNEEDED_DEPRECATED  = 1,
533:   KSP_GMRES_CGS_REFINE_ALWAYS_DEPRECATED    = 2
534: } KSPOrthogonalizationCGSRefinementType;
535: PETSC_EXTERN const char *const KSPOrthogonalizationCGSRefinementTypes[];

537: /*MC
538:    KSP_ORTHOGONALIZATION_CGS_REFINE_NEVER - Do the classical (unmodified) Gram-Schmidt process

540:    Level: advanced

542:    Note:
543:    Possibly unstable, but the fastest to compute

545: .seealso: [](ch_ksp), `KSPGMRES`, `KSPOrthogonalizationCGSRefinementType`, `KSPOrthogonalizationClassicalGramSchmidt()`, `KSPOrthogonalizationSet()`,
546:           `KSP`, `KSPOrthogonalizationGet()`,
547:           `KSPOrthogonalizationSetCGSRefinementType()`, `KSPOrthogonalizationGetCGSRefinementType()`, `KSP_ORTHOGONALIZATION_CGS_REFINE_IFNEEDED`, `KSP_ORTHOGONALIZATION_CGS_REFINE_ALWAYS`,
548:           `KSPOrthogonalizationModifiedGramSchmidt()`
549: M*/

551: /*MC
552:     KSP_ORTHOGONALIZATION_CGS_REFINE_IFNEEDED - Do the classical (unmodified) Gram-Schmidt process and one step of
553:           iterative refinement if an estimate of the orthogonality of the resulting vectors indicates
554:           poor orthogonality.

556:    Level: advanced

558:    Note:
559:    This is slower than `KSP_ORTHOGONALIZATION_CGS_REFINE_NEVER` because it requires an extra norm computation to
560:    estimate the orthogonality but is more stable.

562: .seealso: [](ch_ksp), `KSPGMRES`, `KSPOrthogonalizationCGSRefinementType`, `KSPOrthogonalizationClassicalGramSchmidt()`, `KSPOrthogonalizationSet()`,
563:           `KSP`, `KSPOrthogonalizationGet()`,
564:           `KSPOrthogonalizationSetCGSRefinementType()`, `KSPOrthogonalizationGetCGSRefinementType()`, `KSP_ORTHOGONALIZATION_CGS_REFINE_NEVER`, `KSP_ORTHOGONALIZATION_CGS_REFINE_ALWAYS`,
565:           `KSPOrthogonalizationModifiedGramSchmidt()`
566: M*/

568: /*MC
569:    KSP_ORTHOGONALIZATION_CGS_REFINE_ALWAYS - Do two steps of the classical (unmodified) Gram-Schmidt process.

571:    Level: advanced

573:    Notes:
574:    This is roughly twice the cost of `KSP_ORTHOGONALIZATION_CGS_REFINE_NEVER` because it performs the process twice
575:    but it saves the extra norm calculation needed by `KSP_ORTHOGONALIZATION_CGS_REFINE_IFNEEDED`.

577:    You should only use this if you absolutely know that the iterative refinement is needed.

579: .seealso: [](ch_ksp), `KSPGMRES`, `KSPOrthogonalizationCGSRefinementType`, `KSPOrthogonalizationClassicalGramSchmidt()`, `KSPOrthogonalizationSet()`,
580:           `KSP`, `KSPOrthogonalizationGet()`,
581:           `KSPOrthogonalizationSetCGSRefinementType()`, `KSPOrthogonalizationGetCGSRefinementType()`, `KSP_ORTHOGONALIZATION_CGS_REFINE_IFNEEDED`, `KSP_ORTHOGONALIZATION_CGS_REFINE_ALWAYS`,
582:           `KSPOrthogonalizationModifiedGramSchmidt()`
583: M*/

585: PETSC_EXTERN PetscErrorCode KSPOrthogonalizationSetCGSRefinementType(KSP, KSPOrthogonalizationCGSRefinementType);
586: PETSC_EXTERN PetscErrorCode KSPOrthogonalizationGetCGSRefinementType(KSP, KSPOrthogonalizationCGSRefinementType *);

588: PETSC_DEPRECATED_FUNCTION(3, 26, 0, "KSPOrthogonalizationModifiedGramSchmidt()", ) static inline PetscErrorCode KSPGMRESModifiedGramSchmidtOrthogonalization(KSP ksp, PETSC_UNUSED PetscInt it)
589: {
590:   SETERRQ(PetscObjectComm((PetscObject)ksp), PETSC_ERR_SUP, "Use KSPOrthogonalizationModifiedGramSchmidt()");
591: }
592: PETSC_DEPRECATED_FUNCTION(3, 26, 0, "KSPOrthogonalizationClassicalGramSchmidt()", ) static inline PetscErrorCode KSPGMRESClassicalGramSchmidtOrthogonalization(KSP ksp, PETSC_UNUSED PetscInt it)
593: {
594:   SETERRQ(PetscObjectComm((PetscObject)ksp), PETSC_ERR_SUP, "Use KSPOrthogonalizationClassicalGramSchmidt()");
595: }
596: PETSC_DEPRECATED_FUNCTION(3, 26, 0, "KSPOrthogonalizationSet()", ) static inline PetscErrorCode KSPGMRESSetOrthogonalization(KSP ksp, PETSC_UNUSED PetscErrorCode (*orthog)(KSP, PetscInt))
597: {
598:   SETERRQ(PetscObjectComm((PetscObject)ksp), PETSC_ERR_SUP, "Use KSPOrthogonalizationSet()");
599: }
600: PETSC_DEPRECATED_FUNCTION(3, 26, 0, "KSPOrthogonalizationGet()", ) static inline PetscErrorCode KSPGMRESGetOrthogonalization(KSP ksp, PETSC_UNUSED PetscErrorCode (**orthog)(KSP, PetscInt))
601: {
602:   SETERRQ(PetscObjectComm((PetscObject)ksp), PETSC_ERR_SUP, "Use KSPOrthogonalizationGet()");
603: }
604: PETSC_DEPRECATED_TYPEDEF(3, 26, 0, "KSPOrthogonalizationCGSRefinementType", ) typedef KSPOrthogonalizationCGSRefinementType KSPGMRESCGSRefinementType;
605: PETSC_DEPRECATED_FUNCTION(3, 26, 0, "KSPOrthogonalizationSetCGSRefinementType()", )
606: static inline PetscErrorCode KSPGMRESSetCGSRefinementType(KSP ksp, KSPOrthogonalizationCGSRefinementType type)
607: {
608:   return KSPOrthogonalizationSetCGSRefinementType(ksp, type);
609: }
610: PETSC_DEPRECATED_FUNCTION(3, 26, 0, "KSPOrthogonalizationGetCGSRefinementType()", )
611: static inline PetscErrorCode KSPGMRESGetCGSRefinementType(KSP ksp, KSPOrthogonalizationCGSRefinementType *type)
612: {
613:   return KSPOrthogonalizationGetCGSRefinementType(ksp, type);
614: }

616: PETSC_EXTERN KSPFlexibleModifyPCFn KSPFlexibleModifyPCNoChange;
617: PETSC_EXTERN KSPFlexibleModifyPCFn KSPFlexibleModifyPCKSP;

619: PETSC_DEPRECATED_FUNCTION(3, 25, 0, "KSPFlexibleModifyPCNoChange()", ) static inline PetscErrorCode KSPFGMRESModifyPCNoChange(KSP ksp, PetscInt total_its, PetscInt loc_its, PetscReal res_norm, PetscCtx ctx)
620: {
621:   return KSPFlexibleModifyPCNoChange(ksp, total_its, loc_its, res_norm, ctx);
622: }

624: PETSC_DEPRECATED_FUNCTION(3, 25, 0, "KSPFlexibleModifyPCKSP()", ) static inline PetscErrorCode KSPFGMRESModifyPCKSP(KSP ksp, PetscInt total_its, PetscInt loc_its, PetscReal res_norm, PetscCtx ctx)
625: {
626:   return KSPFlexibleModifyPCKSP(ksp, total_its, loc_its, res_norm, ctx);
627: }

629: PETSC_EXTERN PetscErrorCode KSPQCGSetTrustRegionRadius(KSP, PetscReal);
630: PETSC_EXTERN PetscErrorCode KSPQCGGetQuadratic(KSP, PetscReal *);
631: PETSC_EXTERN PetscErrorCode KSPQCGGetTrialStepNorm(KSP, PetscReal *);

633: PETSC_EXTERN PetscErrorCode KSPBCGSLSetXRes(KSP, PetscReal);
634: PETSC_EXTERN PetscErrorCode KSPBCGSLSetPol(KSP, PetscBool);
635: PETSC_EXTERN PetscErrorCode KSPBCGSLSetEll(KSP, PetscInt);
636: PETSC_EXTERN PetscErrorCode KSPBCGSLSetUsePseudoinverse(KSP, PetscBool);

638: PETSC_EXTERN PetscErrorCode KSPSetFromOptions(KSP);
639: PETSC_EXTERN PetscErrorCode KSPResetFromOptions(KSP);

641: PETSC_EXTERN PetscErrorCode       KSPMonitorSetFromOptions(KSP, const char[], const char[], PetscCtx);
642: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorResidual;
643: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorResidualView;
644: PETSC_DEPRECATED_FUNCTION(3, 23, 0, "KSPMonitorResidualDraw()", ) static inline PetscErrorCode KSPMonitorResidualDraw(KSP ksp, PetscInt n, PetscReal rnorm, PetscViewerAndFormat *vf)
645: {
646:   return KSPMonitorResidualView(ksp, n, rnorm, vf);
647: }
648: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorResidualDrawLG;
649: PETSC_EXTERN PetscErrorCode       KSPMonitorResidualDrawLGCreate(PetscViewer, PetscViewerFormat, PetscCtx, PetscViewerAndFormat **);
650: PETSC_DEPRECATED_FUNCTION(3, 26, 0, "KSPMonitorResidual()", ) static inline PetscErrorCode KSPMonitorResidualShort(KSP ksp, PetscInt n, PetscReal rnorm, PetscViewerAndFormat *vf)
651: {
652:   return KSPMonitorResidual(ksp, n, rnorm, vf);
653: }
654: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorResidualRange;
655: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorTrueResidual;
656: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorTrueResidualView;
657: PETSC_DEPRECATED_FUNCTION(3, 23, 0, "KSPMonitorTrueResidualDraw()", ) static inline PetscErrorCode KSPMonitorTrueResidualDraw(KSP ksp, PetscInt n, PetscReal rnorm, PetscViewerAndFormat *vf)
658: {
659:   return KSPMonitorTrueResidualView(ksp, n, rnorm, vf);
660: }
661: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorTrueResidualDrawLG;
662: PETSC_EXTERN PetscErrorCode       KSPMonitorTrueResidualDrawLGCreate(PetscViewer, PetscViewerFormat, PetscCtx, PetscViewerAndFormat **);
663: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorTrueResidualMax;
664: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorError;
665: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorErrorDraw;
666: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorErrorDrawLG;
667: PETSC_EXTERN PetscErrorCode       KSPMonitorErrorDrawLGCreate(PetscViewer, PetscViewerFormat, PetscCtx, PetscViewerAndFormat **);
668: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorSolution;
669: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorSolutionDraw;
670: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorSolutionDrawLG;
671: PETSC_EXTERN PetscErrorCode       KSPMonitorSolutionDrawLGCreate(PetscViewer, PetscViewerFormat, PetscCtx, PetscViewerAndFormat **);
672: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorSingularValue;
673: PETSC_EXTERN PetscErrorCode       KSPMonitorSingularValueCreate(PetscViewer, PetscViewerFormat, PetscCtx, PetscViewerAndFormat **);
674: PETSC_DEPRECATED_FUNCTION(3, 15, 0, "KSPMonitorResidual()", ) static inline PetscErrorCode KSPMonitorDefault(KSP ksp, PetscInt n, PetscReal rnorm, PetscViewerAndFormat *vf)
675: {
676:   return KSPMonitorResidual(ksp, n, rnorm, vf);
677: }
678: PETSC_DEPRECATED_FUNCTION(3, 15, 0, "KSPMonitorTrueResidual()", ) static inline PetscErrorCode KSPMonitorTrueResidualNorm(KSP ksp, PetscInt n, PetscReal rnorm, PetscViewerAndFormat *vf)
679: {
680:   return KSPMonitorTrueResidual(ksp, n, rnorm, vf);
681: }
682: PETSC_DEPRECATED_FUNCTION(3, 15, 0, "KSPMonitorTrueResidualMax()", ) static inline PetscErrorCode KSPMonitorTrueResidualMaxNorm(KSP ksp, PetscInt n, PetscReal rnorm, PetscViewerAndFormat *vf)
683: {
684:   return KSPMonitorTrueResidualMax(ksp, n, rnorm, vf);
685: }

687: PETSC_EXTERN PetscErrorCode KSPGMRESMonitorKrylov(KSP, PetscInt, PetscReal, void *);
688: PETSC_EXTERN PetscErrorCode KSPMonitorDynamicTolerance(KSP, PetscInt, PetscReal, PetscCtx);
689: PETSC_EXTERN PetscErrorCode KSPMonitorDynamicToleranceDestroy(PetscCtxRt);
690: PETSC_EXTERN PetscErrorCode KSPMonitorDynamicToleranceCreate(void *);
691: PETSC_EXTERN PetscErrorCode KSPMonitorDynamicToleranceSetCoefficient(void *, PetscReal);
692: PETSC_EXTERN PetscErrorCode KSPMonitorSAWs(KSP, PetscInt, PetscReal, void *);
693: PETSC_EXTERN PetscErrorCode KSPMonitorSAWsCreate(KSP, void **);
694: PETSC_EXTERN PetscErrorCode KSPMonitorSAWsDestroy(PetscCtxRt);

696: PETSC_EXTERN PetscErrorCode KSPUnwindPreconditioner(KSP, Vec, Vec);
697: PETSC_EXTERN PetscErrorCode KSPInitialResidual(KSP, Vec, Vec, Vec, Vec, Vec);

699: PETSC_EXTERN PetscErrorCode KSPSetOperators(KSP, Mat, Mat);
700: PETSC_EXTERN PetscErrorCode KSPGetOperators(KSP, Mat *, Mat *);
701: PETSC_EXTERN PetscErrorCode KSPGetOperatorsSet(KSP, PetscBool *, PetscBool *);
702: PETSC_EXTERN PetscErrorCode KSPSetOptionsPrefix(KSP, const char[]);
703: PETSC_EXTERN PetscErrorCode KSPAppendOptionsPrefix(KSP, const char[]);
704: PETSC_EXTERN PetscErrorCode KSPGetOptionsPrefix(KSP, const char *[]);

706: /*S
707:   KSPConvergedReasonViewFn - A prototype of a function used with `KSPConvergedReasonViewSet()`

709:   Calling Sequence:
710: + ksp - the `KSP` object whose `KSPConvergedReason` is to be viewed
711: - ctx - context used by the function, set with `KSPConvergedReasonViewSet()`

713:   Level: beginner

715: .seealso: [](ch_ksp), `KSP`, `KSPConvergedReasonView()`, `KSPConvergedReasonViewSet()`, `KSPConvergedReasonViewFromOptions()`, `KSPView()`
716: S*/
717: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPConvergedReasonViewFn(KSP ksp, PetscCtx ctx);

719: PETSC_EXTERN PetscErrorCode KSPView(KSP, PetscViewer);
720: PETSC_EXTERN PetscErrorCode KSPLoad(KSP, PetscViewer);
721: PETSC_EXTERN PetscErrorCode KSPViewFromOptions(KSP, PetscObject, const char[]);
722: PETSC_EXTERN PetscErrorCode KSPConvergedReasonView(KSP, PetscViewer);
723: PETSC_EXTERN PetscErrorCode KSPConvergedReasonViewSet(KSP, KSPConvergedReasonViewFn *, void *, PetscCtxDestroyFn *);
724: PETSC_EXTERN PetscErrorCode KSPConvergedReasonViewFromOptions(KSP);
725: PETSC_EXTERN PetscErrorCode KSPConvergedReasonViewCancel(KSP);
726: PETSC_EXTERN PetscErrorCode KSPConvergedRateView(KSP, PetscViewer);

728: PETSC_DEPRECATED_FUNCTION(3, 14, 0, "KSPConvergedReasonView()", ) static inline PetscErrorCode KSPReasonView(KSP ksp, PetscViewer v)
729: {
730:   return KSPConvergedReasonView(ksp, v);
731: }
732: PETSC_DEPRECATED_FUNCTION(3, 14, 0, "KSPConvergedReasonViewFromOptions()", ) static inline PetscErrorCode KSPReasonViewFromOptions(KSP ksp)
733: {
734:   return KSPConvergedReasonViewFromOptions(ksp);
735: }

737: #define KSP_FILE_CLASSID 1211223

739: PETSC_EXTERN PetscErrorCode       KSPLSQRSetExactMatNorm(KSP, PetscBool);
740: PETSC_EXTERN PetscErrorCode       KSPLSQRSetComputeStandardErrorVec(KSP, PetscBool);
741: PETSC_EXTERN PetscErrorCode       KSPLSQRGetStandardErrorVec(KSP, Vec *);
742: PETSC_EXTERN PetscErrorCode       KSPLSQRGetNorms(KSP, PetscReal *, PetscReal *);
743: PETSC_EXTERN KSPMonitorRegisterFn KSPLSQRMonitorResidual;
744: PETSC_EXTERN KSPMonitorRegisterFn KSPLSQRMonitorResidualDrawLG;
745: PETSC_EXTERN PetscErrorCode       KSPLSQRMonitorResidualDrawLGCreate(PetscViewer, PetscViewerFormat, void *, PetscViewerAndFormat **);

747: PETSC_EXTERN PetscErrorCode PCRedundantGetKSP(PC, KSP *);
748: PETSC_EXTERN PetscErrorCode PCRedistributeGetKSP(PC, KSP *);
749: PETSC_EXTERN PetscErrorCode PCTelescopeGetKSP(PC, KSP *);
750: PETSC_EXTERN PetscErrorCode PCMPIGetKSP(PC, KSP *);

752: /*E
753:    KSPNormType - Norm calculated by the `KSP` and passed in the Krylov convergence
754:        test routines.

756:    Values:
757: +  `KSP_NORM_DEFAULT`          - use the default for the current `KSPType`
758: .  `KSP_NORM_NONE`             - use no norm calculation
759: .  `KSP_NORM_PRECONDITIONED`   - use the preconditioned residual norm
760: .  `KSP_NORM_UNPRECONDITIONED` - use the unpreconditioned residual norm
761: -  `KSP_NORM_NATURAL`          - use the natural norm (the norm induced by the linear operator)

763:    Level: advanced

765:    Note:
766:    Each solver only supports a subset of these and some may support different ones
767:    depending on whether left or right preconditioning is used, see `KSPSetPCSide()`

769: .seealso: [](ch_ksp), `KSP`, `PCSide`, `KSPSolve()`, `KSPGetConvergedReason()`, `KSPSetNormType()`,
770:           `KSPSetConvergenceTest()`, `KSPSetPCSide()`, `KSP_NORM_DEFAULT`, `KSP_NORM_NONE`, `KSP_NORM_PRECONDITIONED`, `KSP_NORM_UNPRECONDITIONED`, `KSP_NORM_NATURAL`
771: E*/
772: typedef enum {
773:   KSP_NORM_DEFAULT          = -1,
774:   KSP_NORM_NONE             = 0,
775:   KSP_NORM_PRECONDITIONED   = 1,
776:   KSP_NORM_UNPRECONDITIONED = 2,
777:   KSP_NORM_NATURAL          = 3
778: } KSPNormType;
779: #define KSP_NORM_MAX (KSP_NORM_NATURAL + 1)
780: PETSC_EXTERN const char *const *const KSPNormTypes;

782: /*MC
783:    KSP_NORM_NONE - Do not compute a norm during the Krylov process. This will
784:    possibly save some computation but means the convergence test cannot
785:    be based on a norm of a residual etc.

787:    Level: advanced

789:    Note:
790:    Some Krylov methods need to compute a residual norm (such as `KPSGMRES`) and then this option is ignored

792: .seealso: [](ch_ksp), `KSPNormType`, `KSP`, `KSPSetNormType()`, `KSP_NORM_PRECONDITIONED`, `KSP_NORM_UNPRECONDITIONED`, `KSP_NORM_NATURAL`
793: M*/

795: /*MC
796:    KSP_NORM_PRECONDITIONED - Compute the norm of the preconditioned residual B*(b - A*x), if left preconditioning, and pass that to the
797:    convergence test routine.

799:    Level: advanced

801: .seealso: [](ch_ksp), `KSPNormType`, `KSP`, `KSPSetNormType()`, `KSP_NORM_NONE`, `KSP_NORM_UNPRECONDITIONED`, `KSP_NORM_NATURAL`, `KSPSetConvergenceTest()`
802: M*/

804: /*MC
805:    KSP_NORM_UNPRECONDITIONED - Compute the norm of the true residual (b - A*x) and pass that to the
806:    convergence test routine.

808:    Level: advanced

810: .seealso: [](ch_ksp), `KSPNormType`, `KSP`, `KSPSetNormType()`, `KSP_NORM_NONE`, `KSP_NORM_PRECONDITIONED`, `KSP_NORM_NATURAL`, `KSPSetConvergenceTest()`
811: M*/

813: /*MC
814:    KSP_NORM_NATURAL - Compute the 'natural norm' of residual sqrt((b - A*x)*B*(b - A*x)) and pass that to the
815:    convergence test routine. This is only supported by  `KSPCG`, `KSPCR`, `KSPCGNE`, `KSPCGS`, `KSPFCG`, `KSPPIPEFCG`, `KSPPIPEGCR`

817:    Level: advanced

819: .seealso: [](ch_ksp), `KSPNormType`, `KSP`, `KSPSetNormType()`, `KSP_NORM_NONE`, `KSP_NORM_PRECONDITIONED`, `KSP_NORM_UNPRECONDITIONED`, `KSPSetConvergenceTest()`
820: M*/

822: PETSC_EXTERN PetscErrorCode KSPSetNormType(KSP, KSPNormType);
823: PETSC_EXTERN PetscErrorCode KSPGetNormType(KSP, KSPNormType *);
824: PETSC_EXTERN PetscErrorCode KSPSetSupportedNorm(KSP, KSPNormType, PCSide, PetscInt);
825: PETSC_EXTERN PetscErrorCode KSPSetCheckNormIteration(KSP, PetscInt);
826: PETSC_EXTERN PetscErrorCode KSPSetLagNorm(KSP, PetscBool);

828: #define KSP_CONVERGED_CG_NEG_CURVE_DEPRECATED   KSP_CONVERGED_CG_NEG_CURVE PETSC_DEPRECATED_ENUM(3, 19, 0, "KSP_CONVERGED_NEG_CURVE", )
829: #define KSP_CONVERGED_CG_CONSTRAINED_DEPRECATED KSP_CONVERGED_CG_CONSTRAINED PETSC_DEPRECATED_ENUM(3, 19, 0, "KSP_CONVERGED_STEP_LENGTH", )
830: #define KSP_CONVERGED_RTOL_NORMAL_DEPRECATED    KSP_CONVERGED_RTOL_NORMAL PETSC_DEPRECATED_ENUM(3, 24, 0, "KSP_CONVERGED_RTOL_NORMAL_EQUATIONS", )
831: #define KSP_CONVERGED_ATOL_NORMAL_DEPRECATED    KSP_CONVERGED_ATOL_NORMAL PETSC_DEPRECATED_ENUM(3, 24, 0, "KSP_CONVERGED_ATOL_NORMAL_EQUATIONS", )
832: /*E
833:    KSPConvergedReason - reason a Krylov method was determined to have converged or diverged

835:    Values:
836: +  `KSP_CONVERGED_RTOL_NORMAL_EQUATIONS` - requested decrease in the residual of the normal equations, for `KSPLSQR`
837: .  `KSP_CONVERGED_ATOL_NORMAL_EQUATIONS` - requested absolute value in the residual of the normal equations, for `KSPLSQR`
838: .  `KSP_CONVERGED_RTOL`                  - requested decrease in the residual
839: .  `KSP_CONVERGED_ATOL`                  - requested absolute value in the residual
840: .  `KSP_CONVERGED_ITS`                   - requested number of iterations
841: .  `KSP_CONVERGED_NEG_CURVE`             - see note below
842: .  `KSP_CONVERGED_STEP_LENGTH`           - see note below
843: .  `KSP_CONVERGED_HAPPY_BREAKDOWN`       - happy breakdown (meaning early convergence of the `KSPType` occurred).
844: .  `KSP_CONVERGED_USER`                  - the user has indicated convergence for an arbitrary reason
845: .  `KSP_DIVERGED_NULL`                   - breakdown when solving the Hessenberg system within `KSPGMRES`
846: .  `KSP_DIVERGED_ITS`                    - requested number of iterations
847: .  `KSP_DIVERGED_DTOL`                   - large increase in the residual norm indicating the solution is diverging
848: .  `KSP_DIVERGED_BREAKDOWN`              - breakdown in the Krylov method
849: .  `KSP_DIVERGED_BREAKDOWN_BICG`         - breakdown in the `KSPBCGS` Krylov method
850: .  `KSP_DIVERGED_NONSYMMETRIC`           - the operator or preonditioner was not symmetric for a `KSPType` that requires symmetry
851: .  `KSP_DIVERGED_INDEFINITE_PC`          - the preconditioner was indefinite for a `KSPType` that requires it be definite, such as `KSPCG`
852: .  `KSP_DIVERGED_NANORINF`               - a not a number of infinity was detected in a vector during the computation
853: .  `KSP_DIVERGED_INDEFINITE_MAT`         - the operator was indefinite for a `KSPType` that requires it be definite, such as `KSPCG`
854: .  `KSP_DIVERGED_PC_FAILED`              - the action of the preconditioner failed for some reason
855: -  `KSP_DIVERGED_USER`                   - the user has indicated divergence for an arbitrary reason

857:    Level: beginner

859:    Note:
860:    The values `KSP_CONVERGED_NEG_CURVE`, and `KSP_CONVERGED_STEP_LENGTH` are returned only by `KSPCG`, `KSPMINRES` and by
861:    the special `KSPNASH`, `KSPSTCG`, and `KSPGLTR` solvers which are used by the `SNESNEWTONTR` (trust region) solver.

863:    Developer Note:
864:    The string versions of these are `KSPConvergedReasons`; if you change
865:    any of the values here also change them that array of names.

867: .seealso: [](ch_ksp), `KSP`, `KSPSolve()`, `KSPGetConvergedReason()`, `KSPSetTolerances()`, `KSPConvergedReasonView()`
868: E*/
869: typedef enum { /* converged */
870:   KSP_CONVERGED_RTOL_NORMAL_DEPRECATED    = 1,
871:   KSP_CONVERGED_RTOL_NORMAL_EQUATIONS     = 1,
872:   KSP_CONVERGED_ATOL_NORMAL_DEPRECATED    = 9,
873:   KSP_CONVERGED_ATOL_NORMAL_EQUATIONS     = 9,
874:   KSP_CONVERGED_RTOL                      = 2,
875:   KSP_CONVERGED_ATOL                      = 3,
876:   KSP_CONVERGED_ITS                       = 4,
877:   KSP_CONVERGED_NEG_CURVE                 = 5,
878:   KSP_CONVERGED_CG_NEG_CURVE_DEPRECATED   = 5,
879:   KSP_CONVERGED_CG_CONSTRAINED_DEPRECATED = 6,
880:   KSP_CONVERGED_STEP_LENGTH               = 6,
881:   KSP_CONVERGED_HAPPY_BREAKDOWN           = 7,
882:   KSP_CONVERGED_USER                      = 8,
883:   /* diverged */
884:   KSP_DIVERGED_NULL                      = -2,
885:   KSP_DIVERGED_ITS                       = -3,
886:   KSP_DIVERGED_DTOL                      = -4,
887:   KSP_DIVERGED_BREAKDOWN                 = -5,
888:   KSP_DIVERGED_BREAKDOWN_BICG            = -6,
889:   KSP_DIVERGED_NONSYMMETRIC              = -7,
890:   KSP_DIVERGED_INDEFINITE_PC             = -8,
891:   KSP_DIVERGED_NANORINF                  = -9,
892:   KSP_DIVERGED_INDEFINITE_MAT            = -10,
893:   KSP_DIVERGED_PC_FAILED                 = -11,
894:   KSP_DIVERGED_PCSETUP_FAILED_DEPRECATED = -11,
895:   KSP_DIVERGED_USER                      = -12,

897:   KSP_CONVERGED_ITERATING = 0
898: } KSPConvergedReason;
899: PETSC_EXTERN const char *const *KSPConvergedReasons;

901: /*MC
902:    KSP_CONVERGED_RTOL - $||r|| \le rtol*||b||$ or $rtol*||b - A*x_0||$ if `KSPConvergedDefaultSetUIRNorm()` was called

904:    Level: beginner

906:    Notes:
907:    See `KSPNormType` and `KSPSetNormType()` for possible norms that may be used. By default
908:    for left preconditioning it is the 2-norm of the preconditioned residual, and the
909:    2-norm of the residual for right preconditioning

911:    See also `KSP_CONVERGED_ATOL` which may apply before this tolerance.

913: .seealso: [](ch_ksp), `KSPNormType`, `KSP_CONVERGED_ATOL`, `KSP_DIVERGED_DTOL`, `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
914: M*/

916: /*MC
917:    KSP_CONVERGED_ATOL - $||r|| \le atol$

919:    Level: beginner

921:    Notes:
922:    See `KSPNormType` and `KSPSetNormType()` for possible norms that may be used. By default
923:    for left preconditioning it is the 2-norm of the preconditioned residual, and the
924:    2-norm of the residual for right preconditioning

926:    See also `KSP_CONVERGED_RTOL` which may apply before this tolerance.

928: .seealso: [](ch_ksp), `KSPNormType`, `KSP_CONVERGED_RTOL`, `KSP_DIVERGED_DTOL`, `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
929: M*/

931: /*MC
932:    KSP_DIVERGED_DTOL - $||r|| \ge dtol*||b||$

934:    Level: beginner

936:    Note:
937:    See `KSPNormType` and `KSPSetNormType()` for possible norms that may be used. By default
938:    for left preconditioning it is the 2-norm of the preconditioned residual, and the
939:    2-norm of the residual for right preconditioning

941: .seealso: [](ch_ksp), `KSPNormType`, `KSP_CONVERGED_ATOL`, `KSP_CONVERGED_RTOL`, `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
942: M*/

944: /*MC
945:    KSP_DIVERGED_ITS - Ran out of iterations before any convergence criteria was
946:    reached

948:    Level: beginner

950: .seealso: [](ch_ksp), `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
951: M*/

953: /*MC
954:    KSP_CONVERGED_ITS - Used by the `KSPPREONLY` solver after the single iteration of
955:    the preconditioner is applied. Also used when the `KSPConvergedSkip()` convergence
956:    test routine is set in `KSP`.

958:    Level: beginner

960: .seealso: [](ch_ksp), `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
961: M*/

963: /*MC
964:    KSP_DIVERGED_BREAKDOWN - A breakdown in the Krylov method was detected so the
965:    method could not continue to enlarge the Krylov space. Could be due to a singular matrix or
966:    preconditioner. In `KSPHPDDM`, this is also returned when some search directions within a block
967:    are collinear.

969:    Level: beginner

971: .seealso: [](ch_ksp), `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
972: M*/

974: /*MC
975:    KSP_DIVERGED_BREAKDOWN_BICG - A breakdown in the `KSPBICG` method was detected so the
976:    method could not continue to enlarge the Krylov space.

978:    Level: beginner

980: .seealso: [](ch_ksp), `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
981: M*/

983: /*MC
984:    KSP_DIVERGED_NONSYMMETRIC - It appears the operator or preconditioner is not
985:    symmetric and this Krylov method (`KSPCG`, `KSPMINRES`, `KSPCR`) requires symmetry

987:    Level: beginner

989: .seealso: [](ch_ksp), `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
990: M*/

992: /*MC
993:    KSP_DIVERGED_INDEFINITE_PC - It appears the preconditioner is indefinite (has both
994:    positive and negative eigenvalues) and this Krylov method (`KSPCG`) requires it to
995:    be symmetric positive definite (SPD).

997:    Level: beginner

999:    Note:
1000:    This can happen with the `PCICC` preconditioner, use the options database option `-pc_factor_shift_positive_definite` to force
1001:    the `PCICC` preconditioner to generate a positive definite preconditioner

1003: .seealso: [](ch_ksp), `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
1004: M*/

1006: /*MC
1007:    KSP_DIVERGED_PC_FAILED - It was not possible to build or use the requested preconditioner. This is usually due to a
1008:    zero pivot in a factorization. It can also result from a failure in a subpreconditioner inside a nested preconditioner
1009:    such as `PCFIELDSPLIT`.

1011:    Level: beginner

1013:    Note:
1014:    Run with `-ksp_error_if_not_converged` to stop the program when the error is detected and print an error message with details.

1016: .seealso: [](ch_ksp), `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
1017: M*/

1019: /*MC
1020:    KSP_CONVERGED_ITERATING - This flag is returned if `KSPGetConvergedReason()` is called
1021:    while `KSPSolve()` is still running.

1023:    Level: beginner

1025: .seealso: [](ch_ksp), `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
1026: M*/

1028: /*S
1029:   KSPConvergenceTestFn - A prototype of a function used with `KSPSetConvergenceTest()`

1031:   Calling Sequence:
1032: + ksp    - iterative solver obtained from `KSPCreate()`
1033: . it     - iteration number
1034: . rnorm  - (estimated) 2-norm of (preconditioned) residual
1035: . reason - the reason why it has converged or diverged
1036: - ctx    - optional convergence context, as set by `KSPSetConvergenceTest()`

1038:   Level: beginner

1040: .seealso: [](ch_ksp), `KSP`, `KSPSetConvergenceTest()`, `KSPGetConvergenceTest()`
1041: S*/
1042: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPConvergenceTestFn(KSP ksp, PetscInt it, PetscReal rnorm, KSPConvergedReason *reason, PetscCtx ctx);

1044: PETSC_EXTERN PetscErrorCode       KSPSetConvergenceTest(KSP, KSPConvergenceTestFn *, void *, PetscCtxDestroyFn *);
1045: PETSC_EXTERN PetscErrorCode       KSPGetConvergenceTest(KSP, KSPConvergenceTestFn **, PetscCtxRt, PetscCtxDestroyFn **);
1046: PETSC_EXTERN PetscErrorCode       KSPGetAndClearConvergenceTest(KSP, KSPConvergenceTestFn **, PetscCtxRt, PetscCtxDestroyFn **);
1047: PETSC_EXTERN PetscErrorCode       KSPGetConvergenceContext(KSP, PetscCtxRt);
1048: PETSC_EXTERN KSPConvergenceTestFn KSPConvergedDefault;
1049: PETSC_EXTERN KSPConvergenceTestFn KSPLSQRConvergedDefault;
1050: PETSC_EXTERN PetscCtxDestroyFn    KSPConvergedDefaultDestroy;
1051: PETSC_EXTERN PetscErrorCode       KSPConvergedDefaultCreate(void **);
1052: PETSC_EXTERN PetscErrorCode       KSPConvergedDefaultSetUIRNorm(KSP);
1053: PETSC_EXTERN PetscErrorCode       KSPConvergedDefaultSetUMIRNorm(KSP);
1054: PETSC_EXTERN PetscErrorCode       KSPConvergedDefaultSetConvergedMaxits(KSP, PetscBool);
1055: PETSC_EXTERN PetscErrorCode       KSPConvergedSkip(KSP, PetscInt, PetscReal, KSPConvergedReason *, void *);
1056: PETSC_EXTERN PetscErrorCode       KSPGetConvergedReason(KSP, KSPConvergedReason *);
1057: PETSC_EXTERN PetscErrorCode       KSPGetConvergedReasonString(KSP, const char *[]);
1058: PETSC_EXTERN PetscErrorCode       KSPComputeConvergenceRate(KSP, PetscReal *, PetscReal *, PetscReal *, PetscReal *);
1059: PETSC_EXTERN PetscErrorCode       KSPSetConvergedNegativeCurvature(KSP, PetscBool);
1060: PETSC_EXTERN PetscErrorCode       KSPGetConvergedNegativeCurvature(KSP, PetscBool *);

1062: PETSC_DEPRECATED_FUNCTION(3, 5, 0, "KSPConvergedDefault()", ) static inline void KSPDefaultConverged(void)
1063: { /* never called */
1064: }
1065: #define KSPDefaultConverged (KSPDefaultConverged, KSPConvergedDefault)
1066: PETSC_DEPRECATED_FUNCTION(3, 5, 0, "KSPConvergedDefaultDestroy()", ) static inline void KSPDefaultConvergedDestroy(void)
1067: { /* never called */
1068: }
1069: #define KSPDefaultConvergedDestroy (KSPDefaultConvergedDestroy, KSPConvergedDefaultDestroy)
1070: PETSC_DEPRECATED_FUNCTION(3, 5, 0, "KSPConvergedDefaultCreate()", ) static inline void KSPDefaultConvergedCreate(void)
1071: { /* never called */
1072: }
1073: #define KSPDefaultConvergedCreate (KSPDefaultConvergedCreate, KSPConvergedDefaultCreate)
1074: PETSC_DEPRECATED_FUNCTION(3, 5, 0, "KSPConvergedDefaultSetUIRNorm()", ) static inline void KSPDefaultConvergedSetUIRNorm(void)
1075: { /* never called */
1076: }
1077: #define KSPDefaultConvergedSetUIRNorm (KSPDefaultConvergedSetUIRNorm, KSPConvergedDefaultSetUIRNorm)
1078: PETSC_DEPRECATED_FUNCTION(3, 5, 0, "KSPConvergedDefaultSetUMIRNorm()", ) static inline void KSPDefaultConvergedSetUMIRNorm(void)
1079: { /* never called */
1080: }
1081: #define KSPDefaultConvergedSetUMIRNorm (KSPDefaultConvergedSetUMIRNorm, KSPConvergedDefaultSetUMIRNorm)
1082: PETSC_DEPRECATED_FUNCTION(3, 5, 0, "KSPConvergedSkip()", ) static inline void KSPSkipConverged(void)
1083: { /* never called */
1084: }
1085: #define KSPSkipConverged (KSPSkipConverged, KSPConvergedSkip)

1087: PETSC_EXTERN PetscErrorCode KSPComputeOperator(KSP, MatType, Mat *);
1088: PETSC_DEPRECATED_FUNCTION(3, 12, 0, "KSPComputeOperator()", ) static inline PetscErrorCode KSPComputeExplicitOperator(KSP A, Mat *B)
1089: {
1090:   return KSPComputeOperator(A, PETSC_NULLPTR, B);
1091: }

1093: /*E
1094:    KSPCGType - Determines what type of `KSPCG` to use

1096:    Values:
1097:  + `KSP_CG_SYMMETRIC` - the matrix is complex symmetric
1098:  - `KSP_CG_HERMITIAN` - the matrix is complex Hermitian

1100:    Level: beginner

1102: .seealso: [](ch_ksp), `KSPCG`, `KSP`, `KSPCGSetType()`
1103: E*/
1104: typedef enum {
1105:   KSP_CG_SYMMETRIC = 0,
1106:   KSP_CG_HERMITIAN = 1
1107: } KSPCGType;
1108: PETSC_EXTERN const char *const KSPCGTypes[];

1110: PETSC_EXTERN PetscErrorCode KSPCGSetType(KSP, KSPCGType);
1111: PETSC_EXTERN PetscErrorCode KSPCGUseSingleReduction(KSP, PetscBool);

1113: PETSC_EXTERN PetscErrorCode KSPCGSetRadius(KSP, PetscReal);
1114: PETSC_EXTERN PetscErrorCode KSPCGSetObjectiveTarget(KSP, PetscReal);
1115: PETSC_EXTERN PetscErrorCode KSPCGGetNormD(KSP, PetscReal *);
1116: PETSC_EXTERN PetscErrorCode KSPCGGetObjFcn(KSP, PetscReal *);

1118: PETSC_EXTERN PetscErrorCode KSPGLTRGetMinEig(KSP, PetscReal *);
1119: PETSC_EXTERN PetscErrorCode KSPGLTRGetLambda(KSP, PetscReal *);
1120: PETSC_DEPRECATED_FUNCTION(3, 12, 0, "KSPGLTRGetMinEig()", ) static inline PetscErrorCode KSPCGGLTRGetMinEig(KSP ksp, PetscReal *x)
1121: {
1122:   return KSPGLTRGetMinEig(ksp, x);
1123: }
1124: PETSC_DEPRECATED_FUNCTION(3, 12, 0, "KSPGLTRGetLambda()", ) static inline PetscErrorCode KSPCGGLTRGetLambda(KSP ksp, PetscReal *x)
1125: {
1126:   return KSPGLTRGetLambda(ksp, x);
1127: }

1129: PETSC_EXTERN PetscErrorCode KSPPythonSetType(KSP, const char[]);
1130: PETSC_EXTERN PetscErrorCode KSPPythonGetType(KSP, const char *[]);

1132: PETSC_EXTERN PetscErrorCode PCPreSolve(PC, KSP);
1133: PETSC_EXTERN PetscErrorCode PCPostSolve(PC, KSP);

1135: PETSC_EXTERN PetscErrorCode KSPMonitorLGRange(KSP, PetscInt, PetscReal, void *);

1137: /*S
1138:   PCShellPSolveFn - A function prototype for functions provided to `PCShellSetPreSolve()` and `PCShellSetPostSolve()`

1140:   Calling Sequence:
1141: + pc  - the preconditioner `PC` context
1142: . ksp - the `KSP` context
1143: . xin  - input vector
1144: - xout - output vector

1146:   Level: intermediate

1148: .seealso: [](ch_snes), `KSPPSolveFn`, `KSP`, `PCShellSetPreSolve()`, `PCShellSetPostSolve()`
1149: S*/
1150: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode PCShellPSolveFn(PC pc, KSP ksp, Vec xim, Vec xout);

1152: PETSC_EXTERN PetscErrorCode PCShellSetPreSolve(PC, PCShellPSolveFn *);
1153: PETSC_EXTERN PetscErrorCode PCShellSetPostSolve(PC, PCShellPSolveFn *);

1155: /*S
1156:    KSPGuess - Abstract PETSc object that manages all initial guess generation methods for Krylov methods.

1158:    Level: intermediate

1160:    Note:
1161:    These methods generate initial guesses based on a series of previous, related, linear solves. For example,
1162:    in implicit time-stepping with `TS`.

1164: .seealso: [](ch_ksp), `KSPCreate()`, `KSPGuessSetType()`, `KSPGuessType`
1165: S*/
1166: typedef struct _p_KSPGuess *KSPGuess;

1168: /*J
1169:   KSPGuessType - String with the name of a PETSc initial guess approach for Krylov methods.

1171:   Values:
1172: + `KSPGUESSFISCHER` - methodology developed by Paul Fischer
1173: - `KSPGUESSPOD`     - methodology based on proper orthogonal decomposition (POD)

1175:   Options Database Key:
1176: . -ksp_guess_type (fischer|pod) - set the type

1178:   Level: intermediate

1180: .seealso: [](ch_ksp), `KSP`, `KSPGuess`, `KSPGuessSetType()`
1181: J*/
1182: typedef const char *KSPGuessType;
1183: #define KSPGUESSFISCHER "fischer"
1184: #define KSPGUESSPOD     "pod"

1186: PETSC_EXTERN PetscErrorCode KSPGuessRegister(const char[], PetscErrorCode (*)(KSPGuess));
1187: PETSC_EXTERN PetscErrorCode KSPSetGuess(KSP, KSPGuess);
1188: PETSC_EXTERN PetscErrorCode KSPGetGuess(KSP, KSPGuess *);
1189: PETSC_EXTERN PetscErrorCode KSPGuessView(KSPGuess, PetscViewer);
1190: PETSC_EXTERN PetscErrorCode KSPGuessDestroy(KSPGuess *);
1191: PETSC_EXTERN PetscErrorCode KSPGuessCreate(MPI_Comm, KSPGuess *);
1192: PETSC_EXTERN PetscErrorCode KSPGuessSetType(KSPGuess, KSPGuessType);
1193: PETSC_EXTERN PetscErrorCode KSPGuessGetType(KSPGuess, KSPGuessType *);
1194: PETSC_EXTERN PetscErrorCode KSPGuessSetTolerance(KSPGuess, PetscReal);
1195: PETSC_EXTERN PetscErrorCode KSPGuessSetUp(KSPGuess);
1196: PETSC_EXTERN PetscErrorCode KSPGuessUpdate(KSPGuess, Vec, Vec);
1197: PETSC_EXTERN PetscErrorCode KSPGuessFormGuess(KSPGuess, Vec, Vec);
1198: PETSC_EXTERN PetscErrorCode KSPGuessSetFromOptions(KSPGuess);
1199: PETSC_EXTERN PetscErrorCode KSPGuessFischerSetModel(KSPGuess, PetscInt, PetscInt);
1200: PETSC_EXTERN PetscErrorCode KSPSetUseFischerGuess(KSP, PetscInt, PetscInt);
1201: PETSC_EXTERN PetscErrorCode KSPSetInitialGuessKnoll(KSP, PetscBool);
1202: PETSC_EXTERN PetscErrorCode KSPGetInitialGuessKnoll(KSP, PetscBool *);

1204: /*E
1205:     MatSchurComplementAinvType - Determines how to approximate the inverse of the (0,0) block in Schur complement matrix assembly routines

1207:     Level: intermediate

1209: .seealso: `MatSchurComplementGetAinvType()`, `MatSchurComplementSetAinvType()`, `MatSchurComplementGetPmat()`, `MatGetSchurComplement()`,
1210:           `MatCreateSchurComplementPmat()`, `MatCreateSchurComplement()`
1211: E*/
1212: typedef enum {
1213:   MAT_SCHUR_COMPLEMENT_AINV_DIAG,
1214:   MAT_SCHUR_COMPLEMENT_AINV_LUMP,
1215:   MAT_SCHUR_COMPLEMENT_AINV_BLOCK_DIAG,
1216:   MAT_SCHUR_COMPLEMENT_AINV_FULL
1217: } MatSchurComplementAinvType;
1218: PETSC_EXTERN const char *const MatSchurComplementAinvTypes[];

1220: PETSC_EXTERN PetscErrorCode MatCreateSchurComplement(Mat, Mat, Mat, Mat, Mat, Mat *);
1221: PETSC_EXTERN PetscErrorCode MatSchurComplementGetKSP(Mat, KSP *);
1222: PETSC_EXTERN PetscErrorCode MatSchurComplementSetKSP(Mat, KSP);
1223: PETSC_EXTERN PetscErrorCode MatSchurComplementSetSubMatrices(Mat, Mat, Mat, Mat, Mat, Mat);
1224: PETSC_EXTERN PetscErrorCode MatSchurComplementUpdateSubMatrices(Mat, Mat, Mat, Mat, Mat, Mat);
1225: PETSC_EXTERN PetscErrorCode MatSchurComplementGetSubMatrices(Mat, Mat *, Mat *, Mat *, Mat *, Mat *);
1226: PETSC_EXTERN PetscErrorCode MatSchurComplementSetAinvType(Mat, MatSchurComplementAinvType);
1227: PETSC_EXTERN PetscErrorCode MatSchurComplementGetAinvType(Mat, MatSchurComplementAinvType *);
1228: PETSC_EXTERN PetscErrorCode MatSchurComplementGetPmat(Mat, MatReuse, Mat *);
1229: PETSC_EXTERN PetscErrorCode MatSchurComplementComputeExplicitOperator(Mat, Mat *);
1230: PETSC_EXTERN PetscErrorCode MatGetSchurComplement(Mat, IS, IS, IS, IS, MatReuse, Mat *, MatSchurComplementAinvType, MatReuse, Mat *);
1231: PETSC_EXTERN PetscErrorCode MatCreateSchurComplementPmat(Mat, Mat, Mat, Mat, MatSchurComplementAinvType, MatReuse, Mat *);

1233: PETSC_EXTERN PetscErrorCode MatCreateLMVMDFP(MPI_Comm, PetscInt, PetscInt, Mat *);
1234: PETSC_EXTERN PetscErrorCode MatCreateLMVMBFGS(MPI_Comm, PetscInt, PetscInt, Mat *);
1235: PETSC_EXTERN PetscErrorCode MatCreateLMVMDBFGS(MPI_Comm, PetscInt, PetscInt, Mat *);
1236: PETSC_EXTERN PetscErrorCode MatCreateLMVMDDFP(MPI_Comm, PetscInt, PetscInt, Mat *);
1237: PETSC_EXTERN PetscErrorCode MatCreateLMVMDQN(MPI_Comm, PetscInt, PetscInt, Mat *);
1238: PETSC_EXTERN PetscErrorCode MatCreateLMVMSR1(MPI_Comm, PetscInt, PetscInt, Mat *);
1239: PETSC_EXTERN PetscErrorCode MatCreateLMVMBroyden(MPI_Comm, PetscInt, PetscInt, Mat *);
1240: PETSC_EXTERN PetscErrorCode MatCreateLMVMBadBroyden(MPI_Comm, PetscInt, PetscInt, Mat *);
1241: PETSC_EXTERN PetscErrorCode MatCreateLMVMSymBroyden(MPI_Comm, PetscInt, PetscInt, Mat *);
1242: PETSC_EXTERN PetscErrorCode MatCreateLMVMSymBadBroyden(MPI_Comm, PetscInt, PetscInt, Mat *);
1243: PETSC_EXTERN PetscErrorCode MatCreateLMVMDiagBroyden(MPI_Comm, PetscInt, PetscInt, Mat *);

1245: PETSC_EXTERN PetscErrorCode MatLMVMUpdate(Mat, Vec, Vec);
1246: PETSC_EXTERN PetscErrorCode MatLMVMIsAllocated(Mat, PetscBool *);
1247: PETSC_EXTERN PetscErrorCode MatLMVMAllocate(Mat, Vec, Vec);
1248: PETSC_EXTERN PetscErrorCode MatLMVMReset(Mat, PetscBool);
1249: PETSC_EXTERN PetscErrorCode MatLMVMResetShift(Mat);
1250: PETSC_EXTERN PetscErrorCode MatLMVMClearJ0(Mat);
1251: PETSC_EXTERN PetscErrorCode MatLMVMSetJ0(Mat, Mat);
1252: PETSC_EXTERN PetscErrorCode MatLMVMSetJ0Scale(Mat, PetscReal);
1253: PETSC_EXTERN PetscErrorCode MatLMVMSetJ0Diag(Mat, Vec);
1254: PETSC_EXTERN PetscErrorCode MatLMVMSetJ0PC(Mat, PC);
1255: PETSC_EXTERN PetscErrorCode MatLMVMSetJ0KSP(Mat, KSP);
1256: PETSC_EXTERN PetscErrorCode MatLMVMApplyJ0Fwd(Mat, Vec, Vec);
1257: PETSC_EXTERN PetscErrorCode MatLMVMApplyJ0Inv(Mat, Vec, Vec);
1258: PETSC_EXTERN PetscErrorCode MatLMVMGetLastUpdate(Mat, Vec *, Vec *);
1259: PETSC_EXTERN PetscErrorCode MatLMVMGetJ0(Mat, Mat *);
1260: PETSC_EXTERN PetscErrorCode MatLMVMGetJ0PC(Mat, PC *);
1261: PETSC_EXTERN PetscErrorCode MatLMVMGetJ0KSP(Mat, KSP *);
1262: PETSC_EXTERN PetscErrorCode MatLMVMSetHistorySize(Mat, PetscInt);
1263: PETSC_EXTERN PetscErrorCode MatLMVMGetHistorySize(Mat, PetscInt *);
1264: PETSC_EXTERN PetscErrorCode MatLMVMGetUpdateCount(Mat, PetscInt *);
1265: PETSC_EXTERN PetscErrorCode MatLMVMGetRejectCount(Mat, PetscInt *);
1266: PETSC_EXTERN PetscErrorCode MatLMVMSymBroydenSetDelta(Mat, PetscScalar);

1268: /*E
1269:   MatLMVMMultAlgorithm - The type of algorithm used for matrix-vector products and solves used internally by a `MatLMVM` matrix

1271:   Values:
1272: + `MAT_LMVM_MULT_RECURSIVE`     - Use recursive formulas for products and solves
1273: . `MAT_LMVM_MULT_DENSE`         - Use dense formulas for products and solves when possible
1274: - `MAT_LMVM_MULT_COMPACT_DENSE` - The same as `MATLMVM_MULT_DENSE`, but go further and ensure products and solves are computed in compact low-rank update form

1276:   Level: advanced

1278:   Options Database Keys:
1279: . -mat_lmvm_mult_algorithm (recursive|dense|compact_dense) - the algorithm to use for multiplication

1281: .seealso: [](ch_matrices), `MATLMVM`, `MatLMVMSetMultAlgorithm()`, `MatLMVMGetMultAlgorithm()`
1282: E*/
1283: typedef enum {
1284:   MAT_LMVM_MULT_RECURSIVE,
1285:   MAT_LMVM_MULT_DENSE,
1286:   MAT_LMVM_MULT_COMPACT_DENSE,
1287: } MatLMVMMultAlgorithm;

1289: PETSC_EXTERN const char *const MatLMVMMultAlgorithms[];

1291: PETSC_EXTERN PetscErrorCode MatLMVMSetMultAlgorithm(Mat, MatLMVMMultAlgorithm);
1292: PETSC_EXTERN PetscErrorCode MatLMVMGetMultAlgorithm(Mat, MatLMVMMultAlgorithm *);

1294: /*E
1295:   MatLMVMSymBroydenScaleType - Rescaling type for the initial Hessian of a symmetric Broyden matrix.

1297:   Values:
1298: + `MAT_LMVM_SYMBROYDEN_SCALE_NONE`     - no rescaling
1299: . `MAT_LMVM_SYMBROYDEN_SCALE_SCALAR`   - scalar rescaling
1300: . `MAT_LMVM_SYMBROYDEN_SCALE_DIAGONAL` - diagonal rescaling
1301: . `MAT_LMVM_SYMBROYDEN_SCALE_USER`     - same as `MAT_LMVM_SYMBROYDN_SCALE_NONE`
1302: - `MAT_LMVM_SYMBROYDEN_SCALE_DECIDE`   - let PETSc decide rescaling

1304:   Level: intermediate

1306: .seealso: [](ch_matrices), `MATLMVM`, `MatLMVMSymBroydenSetScaleType()`
1307: E*/
1308: typedef enum {
1309:   MAT_LMVM_SYMBROYDEN_SCALE_NONE     = 0,
1310:   MAT_LMVM_SYMBROYDEN_SCALE_SCALAR   = 1,
1311:   MAT_LMVM_SYMBROYDEN_SCALE_DIAGONAL = 2,
1312:   MAT_LMVM_SYMBROYDEN_SCALE_USER     = 3,
1313:   MAT_LMVM_SYMBROYDEN_SCALE_DECIDE   = 4
1314: } MatLMVMSymBroydenScaleType;
1315: PETSC_EXTERN const char *const MatLMVMSymBroydenScaleTypes[];

1317: PETSC_EXTERN PetscErrorCode MatLMVMSymBroydenSetScaleType(Mat, MatLMVMSymBroydenScaleType);
1318: PETSC_EXTERN PetscErrorCode MatLMVMSymBroydenGetPhi(Mat, PetscReal *);
1319: PETSC_EXTERN PetscErrorCode MatLMVMSymBroydenSetPhi(Mat, PetscReal);
1320: PETSC_EXTERN PetscErrorCode MatLMVMSymBadBroydenGetPsi(Mat, PetscReal *);
1321: PETSC_EXTERN PetscErrorCode MatLMVMSymBadBroydenSetPsi(Mat, PetscReal);

1323: /*E
1324:   MatLMVMDenseType - Memory storage strategy for dense variants of `MATLMVM`.

1326:   Values:
1327: + `MAT_LMVM_DENSE_REORDER` - reorders memory to minimize kernel launch
1328: - `MAT_LMVM_DENSE_INPLACE` - computes inplace to minimize memory movement

1330:   Level: intermediate

1332: .seealso: [](ch_matrices), `MatLMVM`, `MatLMVMDenseSetType()`
1333: E*/
1334: typedef enum {
1335:   MAT_LMVM_DENSE_REORDER,
1336:   MAT_LMVM_DENSE_INPLACE
1337: } MatLMVMDenseType;
1338: PETSC_EXTERN const char *const MatLMVMDenseTypes[];

1340: PETSC_EXTERN PetscErrorCode MatLMVMDenseSetType(Mat, MatLMVMDenseType);

1342: PETSC_EXTERN PetscErrorCode KSPSetDM(KSP, DM);

1344: /*E
1345:   KSPDMActive - Indicates if the `DM` attached to the `KSP` should be used to compute the operator, the right-hand side, or the initial guess

1347:   Values:
1348: + `KSP_DMACTIVE_OPERATOR`      - compute the operator
1349: . `KSP_DMACTIVE_RHS`           - compute the right-hand side
1350: . `KSP_DMACTIVE_INITIAL_GUESS` - compute the initial guess
1351: - `KSP_DMACTIVE_ALL`           - compute all of them

1353:   Level: intermediate

1355: .seealso: [](ch_ksp), `KSP`, `KSPSetDMActive()`, `KSPSetDM()`
1356: E*/
1357: typedef enum {
1358:   KSP_DMACTIVE_OPERATOR      = 1,
1359:   KSP_DMACTIVE_RHS           = 2,
1360:   KSP_DMACTIVE_INITIAL_GUESS = 4,
1361:   KSP_DMACTIVE_ALL           = 1 + 2 + 4
1362: } KSPDMActive;
1363: PETSC_EXTERN PetscErrorCode KSPSetDMActive(KSP, KSPDMActive, PetscBool);

1365: PETSC_EXTERN PetscErrorCode KSPGetDM(KSP, DM *);
1366: PETSC_EXTERN PetscErrorCode KSPSetApplicationContext(KSP, PetscCtx);
1367: PETSC_EXTERN PetscErrorCode KSPGetApplicationContext(KSP, PetscCtxRt);

1369: /*S
1370:   KSPComputeRHSFn - A prototype of a `KSP` evaluation function that would be passed to `KSPSetComputeRHS()`

1372:   Calling Sequence:
1373: + ksp  - `ksp` context
1374: . b    - output vector
1375: - ctx - [optional] user-defined function context

1377:   Level: beginner

1379: .seealso: [](ch_ksp), `KSP`, `KSPSetComputeRHS()`, `SNESGetFunction()`, `KSPComputeInitialGuessFn`, `KSPComputeOperatorsFn`
1380: S*/
1381: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPComputeRHSFn(KSP ksp, Vec b, PetscCtx ctx);

1383: PETSC_EXTERN PetscErrorCode KSPSetComputeRHS(KSP, KSPComputeRHSFn *, void *);

1385: /*S
1386:   KSPComputeOperatorsFn - A prototype of a `KSP` evaluation function that would be passed to `KSPSetComputeOperators()`

1388:   Calling Sequence:
1389: + ksp - `KSP` context
1390: . A   - the operator that defines the linear system
1391: . P   - an operator from which to build the preconditioner (often the same as `A`)
1392: - ctx - [optional] user-defined function context

1394:   Level: beginner

1396: .seealso: [](ch_ksp), `KSP`, `KSPSetComputeRHS()`, `SNESGetFunction()`, `KSPComputeRHSFn`, `KSPComputeInitialGuessFn`
1397: S*/
1398: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPComputeOperatorsFn(KSP ksp, Mat A, Mat P, PetscCtx ctx);

1400: PETSC_EXTERN PetscErrorCode KSPSetComputeOperators(KSP, KSPComputeOperatorsFn, void *);

1402: /*S
1403:   KSPCreateOperatorsFn - A prototype of a `KSP` operator creation function that would be passed to `DMKSPSetCreateOperators()`

1405:   Calling Sequence:
1406: + ksp - `KSP` context
1407: . A   - the created operator that defines the linear system
1408: . P   - the created operator from which to build the preconditioner, often the same as `A`
1409: - ctx - [optional] user-defined function context

1411:   Level: developer

1413:   Notes:
1414:   The returned matrices are owned by the caller, similar to `DMCreateMatrix()`.

1416:   `A` and `P` may be the same object. In such a case, users do not need to increase the reference count of `A`. If `P` is not returned, then we assume it is the same of `A`.

1418: .seealso: [](ch_ksp), `DMKSPSetCreateOperators()`, `DMKSPGetCreateOperators()`, `KSPComputeOperatorsFn`, `KSPSetOperators()`
1419: S*/
1420: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPCreateOperatorsFn(KSP ksp, Mat *A, Mat *P, PetscCtx ctx);

1422: /*S
1423:   KSPComputeInitialGuessFn - A prototype of a `KSP` evaluation function that would be passed to `KSPSetComputeInitialGuess()`

1425:   Calling Sequence:
1426: + ksp  - `ksp` context
1427: . x    - output vector
1428: - ctx - [optional] user-defined function context

1430:   Level: beginner

1432: .seealso: [](ch_ksp), `KSP`, `KSPSetComputeInitialGuess()`, `SNESGetFunction()`, `KSPComputeRHSFn`, `KSPComputeOperatorsFn`
1433: S*/
1434: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPComputeInitialGuessFn(KSP ksp, Vec x, PetscCtx ctx);

1436: PETSC_EXTERN PetscErrorCode KSPSetComputeInitialGuess(KSP, KSPComputeInitialGuessFn *, void *);
1437: PETSC_EXTERN PetscErrorCode DMKSPSetComputeOperators(DM, KSPComputeOperatorsFn *, void *);
1438: PETSC_EXTERN PetscErrorCode DMKSPGetComputeOperators(DM, KSPComputeOperatorsFn **, void *);
1439: PETSC_EXTERN PetscErrorCode DMKSPSetCreateOperators(DM, KSPCreateOperatorsFn *, void *);
1440: PETSC_EXTERN PetscErrorCode DMKSPGetCreateOperators(DM, KSPCreateOperatorsFn **, void *);
1441: PETSC_EXTERN PetscErrorCode DMKSPSetComputeRHS(DM, KSPComputeRHSFn *, void *);
1442: PETSC_EXTERN PetscErrorCode DMKSPGetComputeRHS(DM, KSPComputeRHSFn **, void *);
1443: PETSC_EXTERN PetscErrorCode DMKSPSetComputeInitialGuess(DM, KSPComputeInitialGuessFn *, void *);
1444: PETSC_EXTERN PetscErrorCode DMKSPGetComputeInitialGuess(DM, KSPComputeInitialGuessFn **, void *);

1446: PETSC_EXTERN PetscErrorCode DMGlobalToLocalSolve(DM, Vec, Vec);
1447: PETSC_EXTERN PetscErrorCode DMSwarmProjectFields(DM, DM, PetscInt, const char *[], Vec[], ScatterMode);
1448: PETSC_EXTERN PetscErrorCode DMSwarmProjectGradientFields(DM, DM, PetscInt, const char *[], Vec[], ScatterMode);

1450: PETSC_EXTERN PetscErrorCode DMAdaptInterpolator(DM, DM, Mat, KSP, Mat, Mat, Mat *, void *);
1451: PETSC_EXTERN PetscErrorCode DMCheckInterpolator(DM, Mat, Mat, Mat, PetscReal);

1453: PETSC_EXTERN PetscErrorCode PCBJKOKKOSSetKSP(PC, KSP);
1454: PETSC_EXTERN PetscErrorCode PCBJKOKKOSGetKSP(PC, KSP *);

1456: PETSC_EXTERN PetscErrorCode DMCopyDMKSP(DM, DM);

1458: #include <petscdstypes.h>
1459: PETSC_EXTERN PetscErrorCode DMProjectField(DM, PetscReal, Vec, PetscPointFn **, InsertMode, Vec);