Actual source code: itfunc.c

petsc-3.8.0 2017-09-26
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  2: /*
  3:       Interface KSP routines that the user calls.
  4: */

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

  9: /*@
 10:    KSPComputeExtremeSingularValues - Computes the extreme singular values
 11:    for the preconditioned operator. Called after or during KSPSolve().

 13:    Not Collective

 15:    Input Parameter:
 16: .  ksp - iterative context obtained from KSPCreate()

 18:    Output Parameters:
 19: .  emin, emax - extreme singular values

 21:    Options Database Keys:
 22: .  -ksp_compute_singularvalues - compute extreme singular values and print when KSPSolve completes.

 24:    Notes:
 25:    One must call KSPSetComputeSingularValues() before calling KSPSetUp()
 26:    (or use the option -ksp_compute_eigenvalues) in order for this routine to work correctly.

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

 32:    Estimates of the smallest singular value may be very inaccurate, especially if the Krylov method has not converged.
 33:    The largest singular value is usually accurate to within a few percent if the method has converged, but is still not
 34:    intended for eigenanalysis.

 36:    Disable restarts if using KSPGMRES, otherwise this estimate will only be using those iterations after the last
 37:    restart. See KSPGMRESSetRestart() for more details.

 39:    Level: advanced

 41: .keywords: KSP, compute, extreme, singular, values

 43: .seealso: KSPSetComputeSingularValues(), KSPMonitorSingularValue(), KSPComputeEigenvalues()
 44: @*/
 45: PetscErrorCode  KSPComputeExtremeSingularValues(KSP ksp,PetscReal *emax,PetscReal *emin)
 46: {

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

 55:   if (ksp->ops->computeextremesingularvalues) {
 56:     (*ksp->ops->computeextremesingularvalues)(ksp,emax,emin);
 57:   } else {
 58:     *emin = -1.0;
 59:     *emax = -1.0;
 60:   }
 61:   return(0);
 62: }

 64: /*@
 65:    KSPComputeEigenvalues - Computes the extreme eigenvalues for the
 66:    preconditioned operator. Called after or during KSPSolve().

 68:    Not Collective

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

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

 80:    Options Database Keys:
 81: +  -ksp_compute_eigenvalues - Prints eigenvalues to stdout
 82: -  -ksp_plot_eigenvalues - Plots eigenvalues in an x-window display

 84:    Notes:
 85:    The number of eigenvalues estimated depends on the size of the Krylov space
 86:    generated during the KSPSolve() ; for example, with
 87:    CG it corresponds to the number of CG iterations, for GMRES it is the number
 88:    of GMRES iterations SINCE the last restart. Any extra space in r[] and c[]
 89:    will be ignored.

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

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

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

103:    Level: advanced

105: .keywords: KSP, compute, extreme, singular, values

107: .seealso: KSPSetComputeSingularValues(), KSPMonitorSingularValue(), KSPComputeExtremeSingularValues()
108: @*/
109: PetscErrorCode  KSPComputeEigenvalues(KSP ksp,PetscInt n,PetscReal r[],PetscReal c[],PetscInt *neig)
110: {

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

121:   if (n && ksp->ops->computeeigenvalues) {
122:     (*ksp->ops->computeeigenvalues)(ksp,n,r,c,neig);
123:   } else {
124:     *neig = 0;
125:   }
126:   return(0);
127: }

129: /*@
130:    KSPComputeRitz - Computes the Ritz or harmonic Ritz pairs associated to the
131:    smallest or largest in modulus, for the preconditioned operator.
132:    Called after KSPSolve().

134:    Not Collective

136:    Input Parameter:
137: +  ksp   - iterative context obtained from KSPCreate()
138: .  ritz  - PETSC_TRUE or PETSC_FALSE for ritz pairs or harmonic Ritz pairs, respectively
139: .  small - PETSC_TRUE or PETSC_FALSE for smallest or largest (harmonic) Ritz values, respectively
140: .  nrit  - number of (harmonic) Ritz pairs to compute

142:    Output Parameters:
143: +  nrit  - actual number of computed (harmonic) Ritz pairs 
144: .  S     - multidimensional vector with Ritz vectors
145: .  tetar - real part of the Ritz values        
146: .  tetai - imaginary part of the Ritz values

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

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

163:    Level: advanced

165: .keywords: KSP, compute, ritz, values

167: .seealso: KSPSetComputeRitz()
168: @*/
169: PetscErrorCode  KSPComputeRitz(KSP ksp,PetscBool ritz,PetscBool small,PetscInt *nrit,Vec S[],PetscReal tetar[],PetscReal tetai[])
170: {

175:   if (!ksp->calc_ritz) SETERRQ(PetscObjectComm((PetscObject)ksp),4,"Ritz pairs not requested before KSPSetUp()");
176:   if (ksp->ops->computeritz) {(*ksp->ops->computeritz)(ksp,ritz,small,nrit,S,tetar,tetai);}
177:   return(0);
178: }
179: /*@
180:    KSPSetUpOnBlocks - Sets up the preconditioner for each block in
181:    the block Jacobi, block Gauss-Seidel, and overlapping Schwarz
182:    methods.

184:    Collective on KSP

186:    Input Parameter:
187: .  ksp - the KSP context

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

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

198:    Level: advanced

200: .keywords: KSP, setup, blocks

202: .seealso: PCSetUpOnBlocks(), KSPSetUp(), PCSetUp()
203: @*/
204: PetscErrorCode  KSPSetUpOnBlocks(KSP ksp)
205: {
207:   PCFailedReason pcreason;

211:   if (!ksp->pc) {KSPGetPC(ksp,&ksp->pc);}
212:   PCSetUpOnBlocks(ksp->pc);
213:   PCGetSetUpFailedReason(ksp->pc,&pcreason);
214:   if (pcreason) {
215:     ksp->reason = KSP_DIVERGED_PCSETUP_FAILED;
216:   }
217:   return(0);
218: }

220: /*@
221:    KSPSetReusePreconditioner - reuse the current preconditioner, do not construct a new one even if the operator changes

223:    Collective on KSP

225:    Input Parameters:
226: +  ksp   - iterative context obtained from KSPCreate()
227: -  flag - PETSC_TRUE to reuse the current preconditioner

229:    Level: intermediate

231: .keywords: KSP, setup

233: .seealso: KSPCreate(), KSPSolve(), KSPDestroy(), PCSetReusePreconditioner()
234: @*/
235: PetscErrorCode  KSPSetReusePreconditioner(KSP ksp,PetscBool flag)
236: {

241:   PCSetReusePreconditioner(ksp->pc,flag);
242:   return(0);
243: }

245: /*@
246:    KSPSetSkipPCSetFromOptions - prevents KSPSetFromOptions() from call PCSetFromOptions(). This is used if the same PC is shared by more than one KSP so its options are not resetable for each KSP

248:    Collective on KSP

250:    Input Parameters:
251: +  ksp   - iterative context obtained from KSPCreate()
252: -  flag - PETSC_TRUE to skip calling the PCSetFromOptions()

254:    Level: intermediate

256: .keywords: KSP, setup

258: .seealso: KSPCreate(), KSPSolve(), KSPDestroy(), PCSetReusePreconditioner()
259: @*/
260: PetscErrorCode  KSPSetSkipPCSetFromOptions(KSP ksp,PetscBool flag)
261: {
264:   ksp->skippcsetfromoptions = flag;
265:   return(0);
266: }

268: /*@
269:    KSPSetUp - Sets up the internal data structures for the
270:    later use of an iterative solver.

272:    Collective on KSP

274:    Input Parameter:
275: .  ksp   - iterative context obtained from KSPCreate()

277:    Level: developer

279: .keywords: KSP, setup

281: .seealso: KSPCreate(), KSPSolve(), KSPDestroy()
282: @*/
283: PetscErrorCode KSPSetUp(KSP ksp)
284: {
286:   Mat            A,B;
287:   Mat            mat,pmat;
288:   MatNullSpace   nullsp;
289:   PCFailedReason pcreason;
290: 

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

297:   if (!((PetscObject)ksp)->type_name) {
298:     KSPSetType(ksp,KSPGMRES);
299:   }
300:   KSPSetUpNorms_Private(ksp,PETSC_TRUE,&ksp->normtype,&ksp->pc_side);

302:   if (ksp->dmActive && !ksp->setupstage) {
303:     /* first time in so build matrix and vector data structures using DM */
304:     if (!ksp->vec_rhs) {DMCreateGlobalVector(ksp->dm,&ksp->vec_rhs);}
305:     if (!ksp->vec_sol) {DMCreateGlobalVector(ksp->dm,&ksp->vec_sol);}
306:     DMCreateMatrix(ksp->dm,&A);
307:     KSPSetOperators(ksp,A,A);
308:     PetscObjectDereference((PetscObject)A);
309:   }

311:   if (ksp->dmActive) {
312:     DMKSP kdm;
313:     DMGetDMKSP(ksp->dm,&kdm);

315:     if (kdm->ops->computeinitialguess && ksp->setupstage != KSP_SETUP_NEWRHS) {
316:       /* only computes initial guess the first time through */
317:       (*kdm->ops->computeinitialguess)(ksp,ksp->vec_sol,kdm->initialguessctx);
318:       KSPSetInitialGuessNonzero(ksp,PETSC_TRUE);
319:     }
320:     if (kdm->ops->computerhs) {
321:       (*kdm->ops->computerhs)(ksp,ksp->vec_rhs,kdm->rhsctx);
322:     }

324:     if (ksp->setupstage != KSP_SETUP_NEWRHS) {
325:       if (kdm->ops->computeoperators) {
326:         KSPGetOperators(ksp,&A,&B);
327:         (*kdm->ops->computeoperators)(ksp,A,B,kdm->operatorsctx);
328:       } else SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_WRONGSTATE,"You called KSPSetDM() but did not use DMKSPSetComputeOperators() or KSPSetDMActive(ksp,PETSC_FALSE);");
329:     }
330:   }

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

335:   switch (ksp->setupstage) {
336:   case KSP_SETUP_NEW:
337:     (*ksp->ops->setup)(ksp);
338:     break;
339:   case KSP_SETUP_NEWMATRIX: {   /* This should be replaced with a more general mechanism */
340:     if (ksp->setupnewmatrix) {
341:       (*ksp->ops->setup)(ksp);
342:     }
343:   } break;
344:   default: break;
345:   }

347:   PCGetOperators(ksp->pc,&mat,&pmat);
348:   /* scale the matrix if requested */
349:   if (ksp->dscale) {
350:     PetscScalar *xx;
351:     PetscInt    i,n;
352:     PetscBool   zeroflag = PETSC_FALSE;
353:     if (!ksp->pc) {KSPGetPC(ksp,&ksp->pc);}
354:     if (!ksp->diagonal) { /* allocate vector to hold diagonal */
355:       MatCreateVecs(pmat,&ksp->diagonal,0);
356:     }
357:     MatGetDiagonal(pmat,ksp->diagonal);
358:     VecGetLocalSize(ksp->diagonal,&n);
359:     VecGetArray(ksp->diagonal,&xx);
360:     for (i=0; i<n; i++) {
361:       if (xx[i] != 0.0) xx[i] = 1.0/PetscSqrtReal(PetscAbsScalar(xx[i]));
362:       else {
363:         xx[i]    = 1.0;
364:         zeroflag = PETSC_TRUE;
365:       }
366:     }
367:     VecRestoreArray(ksp->diagonal,&xx);
368:     if (zeroflag) {
369:       PetscInfo(ksp,"Zero detected in diagonal of matrix, using 1 at those locations\n");
370:     }
371:     MatDiagonalScale(pmat,ksp->diagonal,ksp->diagonal);
372:     if (mat != pmat) {MatDiagonalScale(mat,ksp->diagonal,ksp->diagonal);}
373:     ksp->dscalefix2 = PETSC_FALSE;
374:   }
375:   PetscLogEventEnd(KSP_SetUp,ksp,ksp->vec_rhs,ksp->vec_sol,0);
376:   if (!ksp->pc) {KSPGetPC(ksp,&ksp->pc);}
377:   PCSetErrorIfFailure(ksp->pc,ksp->errorifnotconverged);
378:   PCSetUp(ksp->pc);
379:   PCGetSetUpFailedReason(ksp->pc,&pcreason);
380:   if (pcreason) {
381:     ksp->reason = KSP_DIVERGED_PCSETUP_FAILED;
382:   }

384:   MatGetNullSpace(mat,&nullsp);
385:   if (nullsp) {
386:     PetscBool test = PETSC_FALSE;
387:     PetscOptionsGetBool(((PetscObject)ksp)->options,((PetscObject)ksp)->prefix,"-ksp_test_null_space",&test,NULL);
388:     if (test) {
389:       MatNullSpaceTest(nullsp,mat,NULL);
390:     }
391:   }
392:   ksp->setupstage = KSP_SETUP_NEWRHS;
393:   return(0);
394: }

396: /*@
397:    KSPReasonView - Displays the reason a KSP solve converged or diverged to a viewer

399:    Collective on KSP

401:    Parameter:
402: +  ksp - iterative context obtained from KSPCreate()
403: -  viewer - the viewer to display the reason


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

409:    Level: beginner

411: .keywords: KSP, solve, linear system

413: .seealso: KSPCreate(), KSPSetUp(), KSPDestroy(), KSPSetTolerances(), KSPConvergedDefault(),
414:           KSPSolveTranspose(), KSPGetIterationNumber()
415: @*/
416: PetscErrorCode KSPReasonView(KSP ksp,PetscViewer viewer)
417: {
419:   PetscBool      isAscii;

422:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isAscii);
423:   if (isAscii) {
424:     PetscViewerASCIIAddTab(viewer,((PetscObject)ksp)->tablevel);
425:     if (ksp->reason > 0) {
426:       if (((PetscObject) ksp)->prefix) {
427:         PetscViewerASCIIPrintf(viewer,"Linear %s solve converged due to %s iterations %D\n",((PetscObject) ksp)->prefix,KSPConvergedReasons[ksp->reason],ksp->its);
428:       } else {
429:         PetscViewerASCIIPrintf(viewer,"Linear solve converged due to %s iterations %D\n",KSPConvergedReasons[ksp->reason],ksp->its);
430:       }
431:     } else {
432:       if (((PetscObject) ksp)->prefix) {
433:         PetscViewerASCIIPrintf(viewer,"Linear %s solve did not converge due to %s iterations %D\n",((PetscObject) ksp)->prefix,KSPConvergedReasons[ksp->reason],ksp->its);
434:       } else {
435:         PetscViewerASCIIPrintf(viewer,"Linear solve did not converge due to %s iterations %D\n",KSPConvergedReasons[ksp->reason],ksp->its);
436:       }
437:       if (ksp->reason == KSP_DIVERGED_PCSETUP_FAILED) {
438:         PCFailedReason reason;
439:         PCGetSetUpFailedReason(ksp->pc,&reason);
440:         PetscViewerASCIIPrintf(viewer,"               PCSETUP_FAILED due to %s \n",PCFailedReasons[reason]);
441:       }
442:     }
443:     PetscViewerASCIISubtractTab(viewer,((PetscObject)ksp)->tablevel);
444:   }
445:   return(0);
446: }

448: #if defined(PETSC_HAVE_THREADSAFETY)
449: #define KSPReasonViewFromOptions KSPReasonViewFromOptionsUnsafe
450: #else
451: #endif
452: /*@C
453:   KSPReasonViewFromOptions - Processes command line options to determine if/how a KSPReason is to be viewed.

455:   Collective on KSP

457:   Input Parameters:
458: . ksp   - the KSP object

460:   Level: intermediate

462: @*/
463: PetscErrorCode KSPReasonViewFromOptions(KSP ksp)
464: {
465:   PetscErrorCode    ierr;
466:   PetscViewer       viewer;
467:   PetscBool         flg;
468:   PetscViewerFormat format;

471:   PetscOptionsGetViewer(PetscObjectComm((PetscObject)ksp),((PetscObject)ksp)->prefix,"-ksp_converged_reason",&viewer,&format,&flg);
472:   if (flg) {
473:     PetscViewerPushFormat(viewer,format);
474:     KSPReasonView(ksp,viewer);
475:     PetscViewerPopFormat(viewer);
476:     PetscViewerDestroy(&viewer);
477:   }
478:   return(0);
479: }

481:  #include <petscdraw.h>
482: /*@C
483:    KSPSolve - Solves linear system.

485:    Collective on KSP

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

492:    Options Database Keys:
493: +  -ksp_compute_eigenvalues - compute preconditioned operators eigenvalues
494: .  -ksp_plot_eigenvalues - plot the computed eigenvalues in an X-window
495: .  -ksp_plot_eigencontours - plot the computed eigenvalues in an X-window with contours
496: .  -ksp_compute_eigenvalues_explicitly - compute the eigenvalues by forming the dense operator and using LAPACK
497: .  -ksp_plot_eigenvalues_explicitly - plot the explicitly computing eigenvalues
498: .  -ksp_view_mat binary - save matrix to the default binary viewer
499: .  -ksp_view_pmat binary - save matrix used to build preconditioner to the default binary viewer
500: .  -ksp_view_rhs binary - save right hand side vector to the default binary viewer
501: .  -ksp_view_solution binary - save computed solution vector to the default binary viewer
502:            (can be read later with src/ksp/examples/tutorials/ex10.c for testing solvers)
503: .  -ksp_view_mat_explicit - for matrix-free operators, computes the matrix entries and views them
504: .  -ksp_view_preconditioned_operator_explicit - computes the product of the preconditioner and matrix as an explicit matrix and views it
505: .  -ksp_converged_reason - print reason for converged or diverged, also prints number of iterations
506: .  -ksp_final_residual - print 2-norm of true linear system residual at the end of the solution process
507: -  -ksp_view - print the ksp data structure at the end of the system solution

509:    Notes:

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

513:    The operator is specified with KSPSetOperators().

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

518:    If you provide a matrix that has a MatSetNullSpace() and MatSetTransposeNullSpace() this will use that information to solve singular systems
519:    in the least squares sense with a norm minimizing solution.
520: $
521: $                   A x = b   where b = b_p + b_t where b_t is not in the range of A (and hence by the fundamental theorem of linear algebra is in the nullspace(A') see MatSetNullSpace()
522: $
523: $    KSP first removes b_t producing the linear system  A x = b_p (which has multiple solutions) and solves this to find the ||x|| minimizing solution (and hence
524: $    it finds the solution x orthogonal to the nullspace(A). The algorithm is simply in each iteration of the Krylov method we remove the nullspace(A) from the search
525: $    direction thus the solution which is a linear combination of the search directions has no component in the nullspace(A).
526: $
527: $    We recommend always using GMRES for such singular systems.
528: $    If nullspace(A) = nullspace(A') (note symmetric matrices always satisfy this property) then both left and right preconditioning will work
529: $    If nullspace(A) != nullspace(A') then left preconditioning will work but right preconditioning may not work (or it may).

531:    Developer Note: The reason we cannot always solve  nullspace(A) != nullspace(A') systems with right preconditioning is because we need to remove at each iteration
532:        the nullspace(AB) from the search direction. While we know the nullspace(A) the nullspace(AB) equals B^-1 times the nullspace(A) but except for trivial preconditioners
533:        such as diagonal scaling we cannot apply the inverse of the preconditioner to a vector and thus cannot compute the nullspace(AB).


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

541:    Understanding Convergence:
542:    The routines KSPMonitorSet(), KSPComputeEigenvalues(), and
543:    KSPComputeEigenvaluesExplicitly() provide information on additional
544:    options to monitor convergence and print eigenvalue information.

546:    Level: beginner

548: .keywords: KSP, solve, linear system

550: .seealso: KSPCreate(), KSPSetUp(), KSPDestroy(), KSPSetTolerances(), KSPConvergedDefault(),
551:           KSPSolveTranspose(), KSPGetIterationNumber(), MatNullSpaceCreate(), MatSetNullSpace(), MatSetTransposeNullSpace()
552: @*/
553: PetscErrorCode KSPSolve(KSP ksp,Vec b,Vec x)
554: {
555:   PetscErrorCode    ierr;
556:   PetscBool         flag1,flag2,flag3,flg = PETSC_FALSE,inXisinB=PETSC_FALSE,guess_zero;
557:   Mat               mat,pmat;
558:   MPI_Comm          comm;
559:   MatNullSpace      nullsp;
560:   Vec               btmp,vec_rhs=0;

566:   comm = PetscObjectComm((PetscObject)ksp);
567:   if (x && x == b) {
568:     if (!ksp->guess_zero) SETERRQ(comm,PETSC_ERR_ARG_INCOMP,"Cannot use x == b with nonzero initial guess");
569:     VecDuplicate(b,&x);
570:     inXisinB = PETSC_TRUE;
571:   }
572:   if (b) {
573:     PetscObjectReference((PetscObject)b);
574:     VecDestroy(&ksp->vec_rhs);
575:     ksp->vec_rhs = b;
576:   }
577:   if (x) {
578:     PetscObjectReference((PetscObject)x);
579:     VecDestroy(&ksp->vec_sol);
580:     ksp->vec_sol = x;
581:   }
582:   KSPViewFromOptions(ksp,NULL,"-ksp_view_pre");

584:   if (ksp->presolve) {
585:     (*ksp->presolve)(ksp,ksp->vec_rhs,ksp->vec_sol,ksp->prectx);
586:   }
587:   PetscLogEventBegin(KSP_Solve,ksp,ksp->vec_rhs,ksp->vec_sol,0);

589:   /* reset the residual history list if requested */
590:   if (ksp->res_hist_reset) ksp->res_hist_len = 0;
591:   ksp->transpose_solve = PETSC_FALSE;

593:   if (ksp->guess) {
594:     PetscObjectState ostate,state;

596:     KSPGuessSetUp(ksp->guess);
597:     PetscObjectStateGet((PetscObject)ksp->vec_sol,&ostate);
598:     KSPGuessFormGuess(ksp->guess,ksp->vec_rhs,ksp->vec_sol);
599:     PetscObjectStateGet((PetscObject)ksp->vec_sol,&state);
600:     if (state != ostate) {
601:       ksp->guess_zero = PETSC_FALSE;
602:     } else {
603:       PetscInfo(ksp,"Using zero initial guess since the KSPGuess object did not change the vector\n");
604:       ksp->guess_zero = PETSC_TRUE;
605:     }
606:   }

608:   /* KSPSetUp() scales the matrix if needed */
609:   KSPSetUp(ksp);
610:   KSPSetUpOnBlocks(ksp);

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

614:   PCGetOperators(ksp->pc,&mat,&pmat);
615:   /* diagonal scale RHS if called for */
616:   if (ksp->dscale) {
617:     VecPointwiseMult(ksp->vec_rhs,ksp->vec_rhs,ksp->diagonal);
618:     /* second time in, but matrix was scaled back to original */
619:     if (ksp->dscalefix && ksp->dscalefix2) {
620:       Mat mat,pmat;

622:       PCGetOperators(ksp->pc,&mat,&pmat);
623:       MatDiagonalScale(pmat,ksp->diagonal,ksp->diagonal);
624:       if (mat != pmat) {MatDiagonalScale(mat,ksp->diagonal,ksp->diagonal);}
625:     }

627:     /* scale initial guess */
628:     if (!ksp->guess_zero) {
629:       if (!ksp->truediagonal) {
630:         VecDuplicate(ksp->diagonal,&ksp->truediagonal);
631:         VecCopy(ksp->diagonal,ksp->truediagonal);
632:         VecReciprocal(ksp->truediagonal);
633:       }
634:       VecPointwiseMult(ksp->vec_sol,ksp->vec_sol,ksp->truediagonal);
635:     }
636:   }
637:   PCPreSolve(ksp->pc,ksp);

639:   if (ksp->guess_zero) { VecSet(ksp->vec_sol,0.0);}
640:   if (ksp->guess_knoll) { /* The Knoll trick is independent on the KSPGuess specified */
641:     PCApply(ksp->pc,ksp->vec_rhs,ksp->vec_sol);
642:     KSP_RemoveNullSpace(ksp,ksp->vec_sol);
643:     ksp->guess_zero = PETSC_FALSE;
644:   }

646:   /* can we mark the initial guess as zero for this solve? */
647:   guess_zero = ksp->guess_zero;
648:   if (!ksp->guess_zero) {
649:     PetscReal norm;

651:     VecNormAvailable(ksp->vec_sol,NORM_2,&flg,&norm);
652:     if (flg && !norm) ksp->guess_zero = PETSC_TRUE;
653:   }
654:   MatGetTransposeNullSpace(pmat,&nullsp);
655:   if (nullsp) {
656:     VecDuplicate(ksp->vec_rhs,&btmp);
657:     VecCopy(ksp->vec_rhs,btmp);
658:     MatNullSpaceRemove(nullsp,btmp);
659:     vec_rhs      = ksp->vec_rhs;
660:     ksp->vec_rhs = btmp;
661:   }
662:   VecLockPush(ksp->vec_rhs);
663:   if (ksp->reason == KSP_DIVERGED_PCSETUP_FAILED) {
664:     VecSetInf(ksp->vec_sol);
665:   }
666:   (*ksp->ops->solve)(ksp);
667: 
668:   VecLockPop(ksp->vec_rhs);
669:   if (nullsp) {
670:     ksp->vec_rhs = vec_rhs;
671:     VecDestroy(&btmp);
672:   }

674:   ksp->guess_zero = guess_zero;


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

680:   KSPReasonViewFromOptions(ksp);
681:   PCPostSolve(ksp->pc,ksp);

683:   /* diagonal scale solution if called for */
684:   if (ksp->dscale) {
685:     VecPointwiseMult(ksp->vec_sol,ksp->vec_sol,ksp->diagonal);
686:     /* unscale right hand side and matrix */
687:     if (ksp->dscalefix) {
688:       Mat mat,pmat;

690:       VecReciprocal(ksp->diagonal);
691:       VecPointwiseMult(ksp->vec_rhs,ksp->vec_rhs,ksp->diagonal);
692:       PCGetOperators(ksp->pc,&mat,&pmat);
693:       MatDiagonalScale(pmat,ksp->diagonal,ksp->diagonal);
694:       if (mat != pmat) {MatDiagonalScale(mat,ksp->diagonal,ksp->diagonal);}
695:       VecReciprocal(ksp->diagonal);
696:       ksp->dscalefix2 = PETSC_TRUE;
697:     }
698:   }
699:   PetscLogEventEnd(KSP_Solve,ksp,ksp->vec_rhs,ksp->vec_sol,0);
700:   if (ksp->postsolve) {
701:     (*ksp->postsolve)(ksp,ksp->vec_rhs,ksp->vec_sol,ksp->postctx);
702:   }
703:   if (ksp->guess) {
704:     KSPGuessUpdate(ksp->guess,ksp->vec_rhs,ksp->vec_sol);
705:   }

707:   PCGetOperators(ksp->pc,&mat,&pmat);
708:   MatViewFromOptions(mat,(PetscObject)ksp,"-ksp_view_mat");
709:   MatViewFromOptions(pmat,(PetscObject)ksp,"-ksp_view_pmat");
710:   VecViewFromOptions(ksp->vec_rhs,(PetscObject)ksp,"-ksp_view_rhs");

712:   PetscOptionsGetViewer(PetscObjectComm((PetscObject)ksp),((PetscObject)ksp)->prefix,"-ksp_compute_eigenvalues",NULL,NULL,&flag1);
713:   PetscOptionsGetViewer(PetscObjectComm((PetscObject)ksp),((PetscObject)ksp)->prefix,"-ksp_plot_eigenvalues",NULL,NULL,&flag2);
714:   PetscOptionsGetViewer(PetscObjectComm((PetscObject)ksp),((PetscObject)ksp)->prefix,"-ksp_plot_eigencontours",NULL,NULL,&flag3);
715:   if (flag1 || flag2 || flag3) {
716:     PetscInt    nits,n,i,neig;
717:     PetscReal   *r,*c;

719:     KSPGetIterationNumber(ksp,&nits);
720:     n    = nits+2;

722:     if (!nits) {
723:       PetscPrintf(comm,"Zero iterations in solver, cannot approximate any eigenvalues\n");
724:     } else {
725:       PetscMPIInt rank;
726:       MPI_Comm_rank(comm,&rank);
727:       PetscMalloc2(n,&r,n,&c);
728:       KSPComputeEigenvalues(ksp,n,r,c,&neig);
729:       if (flag1) {
730:         PetscPrintf(comm,"Iteratively computed eigenvalues\n");
731:         for (i=0; i<neig; i++) {
732:           if (c[i] >= 0.0) {
733:             PetscPrintf(comm,"%g + %gi\n",(double)r[i],(double)c[i]);
734:           } else {
735:             PetscPrintf(comm,"%g - %gi\n",(double)r[i],-(double)c[i]);
736:           }
737:         }
738:       }
739:       if (flag2 && !rank) {
740:         PetscDraw   draw;
741:         PetscDrawSP drawsp;

743:         if (!ksp->eigviewer) {
744:           PetscViewerDrawOpen(PETSC_COMM_SELF,0,"Iteratively Computed Eigenvalues",PETSC_DECIDE,PETSC_DECIDE,400,400,&ksp->eigviewer);
745:         }
746:         PetscViewerDrawGetDraw(ksp->eigviewer,0,&draw);
747:         PetscDrawSPCreate(draw,1,&drawsp);
748:         for (i=0; i<neig; i++) {
749:           PetscDrawSPAddPoint(drawsp,r+i,c+i);
750:         }
751:         PetscDrawSPDraw(drawsp,PETSC_TRUE);
752:         PetscDrawSPSave(drawsp);
753:         PetscDrawSPDestroy(&drawsp);
754:       }
755:       if (flag3 && !rank) {
756:         KSPPlotEigenContours_Private(ksp,neig,r,c);
757:       }
758:       PetscFree2(r,c);
759:     }
760:   }

762:   PetscOptionsGetViewer(PetscObjectComm((PetscObject)ksp),((PetscObject)ksp)->prefix,"-ksp_compute_singularvalues",NULL,NULL,&flag1);
763:   if (flag1) {
764:     PetscInt nits;

766:     KSPGetIterationNumber(ksp,&nits);
767:     if (!nits) {
768:       PetscPrintf(comm,"Zero iterations in solver, cannot approximate any singular values\n");
769:     } else {
770:       PetscReal emax,emin;

772:       KSPComputeExtremeSingularValues(ksp,&emax,&emin);
773:       PetscPrintf(comm,"Iteratively computed extreme singular values: max %g min %g max/min %g\n",(double)emax,(double)emin,(double)(emax/emin));
774:     }
775:   }

777:   PetscOptionsGetViewer(PetscObjectComm((PetscObject)ksp),((PetscObject)ksp)->prefix,"-ksp_compute_eigenvalues_explicitly",NULL,NULL,&flag1);
778:   PetscOptionsGetViewer(PetscObjectComm((PetscObject)ksp),((PetscObject)ksp)->prefix,"-ksp_plot_eigenvalues_explicitly",NULL,NULL,&flag2);
779:   if (flag1 || flag2) {
780:     PetscInt    n,i;
781:     PetscReal   *r,*c;
782:     PetscMPIInt rank;
783:     MPI_Comm_rank(comm,&rank);
784:     VecGetSize(ksp->vec_sol,&n);
785:     PetscMalloc2(n,&r,n,&c);
786:     KSPComputeEigenvaluesExplicitly(ksp,n,r,c);
787:     if (flag1) {
788:       PetscPrintf(comm,"Explicitly computed eigenvalues\n");
789:       for (i=0; i<n; i++) {
790:         if (c[i] >= 0.0) {
791:           PetscPrintf(comm,"%g + %gi\n",(double)r[i],(double)c[i]);
792:         } else {
793:           PetscPrintf(comm,"%g - %gi\n",(double)r[i],-(double)c[i]);
794:         }
795:       }
796:     }
797:     if (flag2 && !rank) {
798:       PetscDraw   draw;
799:       PetscDrawSP drawsp;

801:       if (!ksp->eigviewer) {
802:         PetscViewerDrawOpen(PETSC_COMM_SELF,0,"Explicitly Computed Eigenvalues",PETSC_DECIDE,PETSC_DECIDE,400,400,&ksp->eigviewer);
803:       }
804:       PetscViewerDrawGetDraw(ksp->eigviewer,0,&draw);
805:       PetscDrawSPCreate(draw,1,&drawsp);
806:       PetscDrawSPReset(drawsp);
807:       for (i=0; i<n; i++) {
808:         PetscDrawSPAddPoint(drawsp,r+i,c+i);
809:       }
810:       PetscDrawSPDraw(drawsp,PETSC_TRUE);
811:       PetscDrawSPSave(drawsp);
812:       PetscDrawSPDestroy(&drawsp);
813:     }
814:     PetscFree2(r,c);
815:   }

817:   PetscOptionsGetViewer(PetscObjectComm((PetscObject)ksp),((PetscObject)ksp)->prefix,"-ksp_view_mat_explicit",NULL,NULL,&flag2);
818:   if (flag2) {
819:     Mat A,B;
820:     PCGetOperators(ksp->pc,&A,NULL);
821:     MatComputeExplicitOperator(A,&B);
822:     MatViewFromOptions(B,(PetscObject)ksp,"-ksp_view_mat_explicit");
823:     MatDestroy(&B);
824:   }
825:   PetscOptionsGetViewer(PetscObjectComm((PetscObject)ksp),((PetscObject)ksp)->prefix,"-ksp_view_preconditioned_operator_explicit",NULL,NULL,&flag2);
826:   if (flag2) {
827:     Mat B;
828:     KSPComputeExplicitOperator(ksp,&B);
829:     MatViewFromOptions(B,(PetscObject)ksp,"-ksp_view_preconditioned_operator_explicit");
830:     MatDestroy(&B);
831:   }
832:   KSPViewFromOptions(ksp,NULL,"-ksp_view");

834:   PetscOptionsGetViewer(PetscObjectComm((PetscObject)ksp),((PetscObject)ksp)->prefix,"-ksp_final_residual",NULL,NULL,&flg);
835:   if (flg) {
836:     Mat       A;
837:     Vec       t;
838:     PetscReal norm;
839:     if (ksp->dscale && !ksp->dscalefix) SETERRQ(comm,PETSC_ERR_ARG_WRONGSTATE,"Cannot compute final scale with -ksp_diagonal_scale except also with -ksp_diagonal_scale_fix");
840:     PCGetOperators(ksp->pc,&A,NULL);
841:     VecDuplicate(ksp->vec_rhs,&t);
842:     KSP_MatMult(ksp,A,ksp->vec_sol,t);
843:     VecAYPX(t, -1.0, ksp->vec_rhs);
844:     VecNorm(t,NORM_2,&norm);
845:     VecDestroy(&t);
846:     PetscPrintf(comm,"KSP final norm of residual %g\n",(double)norm);
847:   }
848:   VecViewFromOptions(ksp->vec_sol,(PetscObject)ksp,"-ksp_view_solution");

850:   if (inXisinB) {
851:     VecCopy(x,b);
852:     VecDestroy(&x);
853:   }
854:   PetscObjectSAWsBlock((PetscObject)ksp);
855:   if (ksp->errorifnotconverged && ksp->reason < 0) SETERRQ(comm,PETSC_ERR_NOT_CONVERGED,"KSPSolve has not converged");
856:   return(0);
857: }

859: /*@
860:    KSPSolveTranspose - Solves the transpose of a linear system.

862:    Collective on KSP

864:    Input Parameter:
865: +  ksp - iterative context obtained from KSPCreate()
866: .  b - right hand side vector
867: -  x - solution vector

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

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

873:    Developer Notes: We need to implement a KSPSolveHermitianTranspose()

875:    Level: developer

877: .keywords: KSP, solve, linear system

879: .seealso: KSPCreate(), KSPSetUp(), KSPDestroy(), KSPSetTolerances(), KSPConvergedDefault(),
880:           KSPSolve()
881: @*/

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

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

904:   ksp->vec_rhs         = b;
905:   ksp->vec_sol         = x;
906:   ksp->transpose_solve = PETSC_TRUE;

908:   KSPSetUp(ksp);
909:   KSPSetUpOnBlocks(ksp);
910:   if (ksp->guess_zero) { VecSet(ksp->vec_sol,0.0);}

912:   PCGetOperators(ksp->pc,&mat,&pmat);
913:   MatGetNullSpace(pmat,&nullsp);
914:   if (nullsp) {
915:     VecDuplicate(ksp->vec_rhs,&btmp);
916:     VecCopy(ksp->vec_rhs,btmp);
917:     MatNullSpaceRemove(nullsp,btmp);
918:     vec_rhs      = ksp->vec_rhs;
919:     ksp->vec_rhs = btmp;
920:   }

922:   (*ksp->ops->solve)(ksp);
923:   if (nullsp) {
924:     ksp->vec_rhs = vec_rhs;
925:     VecDestroy(&btmp);
926:   }
927:   if (!ksp->reason) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_PLIB,"Internal error, solver returned without setting converged reason");
928:   KSPReasonViewFromOptions(ksp);
929:   if (inXisinB) {
930:     VecCopy(x,b);
931:     VecDestroy(&x);
932:   }
933:   if (ksp->errorifnotconverged && ksp->reason < 0) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_NOT_CONVERGED,"KSPSolve has not converged");
934:   return(0);
935: }

937: /*@
938:    KSPReset - Resets a KSP context to the kspsetupcalled = 0 state and removes any allocated Vecs and Mats

940:    Collective on KSP

942:    Input Parameter:
943: .  ksp - iterative context obtained from KSPCreate()

945:    Level: beginner

947: .keywords: KSP, destroy

949: .seealso: KSPCreate(), KSPSetUp(), KSPSolve()
950: @*/
951: PetscErrorCode  KSPReset(KSP ksp)
952: {

957:   if (!ksp) return(0);
958:   if (ksp->ops->reset) {
959:     (*ksp->ops->reset)(ksp);
960:   }
961:   if (ksp->pc) {PCReset(ksp->pc);}
962:   if (ksp->guess) {
963:     KSPGuess guess = ksp->guess;
964:     if (guess->ops->reset) { (*guess->ops->reset)(guess); }
965:   }
966:   VecDestroyVecs(ksp->nwork,&ksp->work);
967:   VecDestroy(&ksp->vec_rhs);
968:   VecDestroy(&ksp->vec_sol);
969:   VecDestroy(&ksp->diagonal);
970:   VecDestroy(&ksp->truediagonal);

972:   ksp->setupstage = KSP_SETUP_NEW;
973:   return(0);
974: }

976: /*@
977:    KSPDestroy - Destroys KSP context.

979:    Collective on KSP

981:    Input Parameter:
982: .  ksp - iterative context obtained from KSPCreate()

984:    Level: beginner

986: .keywords: KSP, destroy

988: .seealso: KSPCreate(), KSPSetUp(), KSPSolve()
989: @*/
990: PetscErrorCode  KSPDestroy(KSP *ksp)
991: {
993:   PC             pc;

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

1000:   PetscObjectSAWsViewOff((PetscObject)*ksp);
1001:   /*
1002:    Avoid a cascading call to PCReset(ksp->pc) from the following call:
1003:    PCReset() shouldn't be called from KSPDestroy() as it is unprotected by pc's
1004:    refcount (and may be shared, e.g., by other ksps).
1005:    */
1006:   pc         = (*ksp)->pc;
1007:   (*ksp)->pc = NULL;
1008:   KSPReset((*ksp));
1009:   (*ksp)->pc = pc;
1010:     if ((*ksp)->ops->destroy) {(*(*ksp)->ops->destroy)(*ksp);}

1012:   DMDestroy(&(*ksp)->dm);
1013:   PCDestroy(&(*ksp)->pc);
1014:   PetscFree((*ksp)->res_hist_alloc);
1015:   if ((*ksp)->convergeddestroy) {
1016:     (*(*ksp)->convergeddestroy)((*ksp)->cnvP);
1017:   }
1018:   KSPMonitorCancel((*ksp));
1019:   PetscViewerDestroy(&(*ksp)->eigviewer);
1020:   PetscHeaderDestroy(ksp);
1021:   return(0);
1022: }

1024: /*@
1025:     KSPSetPCSide - Sets the preconditioning side.

1027:     Logically Collective on KSP

1029:     Input Parameter:
1030: .   ksp - iterative context obtained from KSPCreate()

1032:     Output Parameter:
1033: .   side - the preconditioning side, where side is one of
1034: .vb
1035:       PC_LEFT - left preconditioning (default)
1036:       PC_RIGHT - right preconditioning
1037:       PC_SYMMETRIC - symmetric preconditioning
1038: .ve

1040:     Options Database Keys:
1041: .   -ksp_pc_side <right,left,symmetric>

1043:     Notes:
1044:     Left preconditioning is used by default for most Krylov methods except KSPFGMRES which only supports right preconditioning.

1046:     For methods changing the side of the preconditioner changes the norm type that is used, see KSPSetNormType().

1048:     Symmetric preconditioning is currently available only for the KSPQCG method. Note, however, that
1049:     symmetric preconditioning can be emulated by using either right or left
1050:     preconditioning and a pre or post processing step.

1052:     Setting the PC side often affects the default norm type.  See KSPSetNormType() for details.

1054:     Level: intermediate

1056: .keywords: KSP, set, right, left, symmetric, side, preconditioner, flag

1058: .seealso: KSPGetPCSide(), KSPSetNormType(), KSPGetNormType()
1059: @*/
1060: PetscErrorCode  KSPSetPCSide(KSP ksp,PCSide side)
1061: {
1065:   ksp->pc_side = ksp->pc_side_set = side;
1066:   return(0);
1067: }

1069: /*@
1070:     KSPGetPCSide - Gets the preconditioning side.

1072:     Not Collective

1074:     Input Parameter:
1075: .   ksp - iterative context obtained from KSPCreate()

1077:     Output Parameter:
1078: .   side - the preconditioning side, where side is one of
1079: .vb
1080:       PC_LEFT - left preconditioning (default)
1081:       PC_RIGHT - right preconditioning
1082:       PC_SYMMETRIC - symmetric preconditioning
1083: .ve

1085:     Level: intermediate

1087: .keywords: KSP, get, right, left, symmetric, side, preconditioner, flag

1089: .seealso: KSPSetPCSide()
1090: @*/
1091: PetscErrorCode  KSPGetPCSide(KSP ksp,PCSide *side)
1092: {

1098:   KSPSetUpNorms_Private(ksp,PETSC_TRUE,&ksp->normtype,&ksp->pc_side);
1099:   *side = ksp->pc_side;
1100:   return(0);
1101: }

1103: /*@
1104:    KSPGetTolerances - Gets the relative, absolute, divergence, and maximum
1105:    iteration tolerances used by the default KSP convergence tests.

1107:    Not Collective

1109:    Input Parameter:
1110: .  ksp - the Krylov subspace context

1112:    Output Parameters:
1113: +  rtol - the relative convergence tolerance
1114: .  abstol - the absolute convergence tolerance
1115: .  dtol - the divergence tolerance
1116: -  maxits - maximum number of iterations

1118:    Notes:
1119:    The user can specify NULL for any parameter that is not needed.

1121:    Level: intermediate

1123: .keywords: KSP, get, tolerance, absolute, relative, divergence, convergence,
1124:            maximum, iterations

1126: .seealso: KSPSetTolerances()
1127: @*/
1128: PetscErrorCode  KSPGetTolerances(KSP ksp,PetscReal *rtol,PetscReal *abstol,PetscReal *dtol,PetscInt *maxits)
1129: {
1132:   if (abstol) *abstol = ksp->abstol;
1133:   if (rtol) *rtol = ksp->rtol;
1134:   if (dtol) *dtol = ksp->divtol;
1135:   if (maxits) *maxits = ksp->max_it;
1136:   return(0);
1137: }

1139: /*@
1140:    KSPSetTolerances - Sets the relative, absolute, divergence, and maximum
1141:    iteration tolerances used by the default KSP convergence testers.

1143:    Logically Collective on KSP

1145:    Input Parameters:
1146: +  ksp - the Krylov subspace context
1147: .  rtol - the relative convergence tolerance, relative decrease in the (possibly preconditioned) residual norm
1148: .  abstol - the absolute convergence tolerance   absolute size of the (possibly preconditioned) residual norm
1149: .  dtol - the divergence tolerance,   amount (possibly preconditioned) residual norm can increase before KSPConvergedDefault() concludes that the method is diverging
1150: -  maxits - maximum number of iterations to use

1152:    Options Database Keys:
1153: +  -ksp_atol <abstol> - Sets abstol
1154: .  -ksp_rtol <rtol> - Sets rtol
1155: .  -ksp_divtol <dtol> - Sets dtol
1156: -  -ksp_max_it <maxits> - Sets maxits

1158:    Notes:
1159:    Use PETSC_DEFAULT to retain the default value of any of the tolerances.

1161:    See KSPConvergedDefault() for details how these parameters are used in the default convergence test.  See also KSPSetConvergenceTest()
1162:    for setting user-defined stopping criteria.

1164:    Level: intermediate

1166: .keywords: KSP, set, tolerance, absolute, relative, divergence,
1167:            convergence, maximum, iterations

1169: .seealso: KSPGetTolerances(), KSPConvergedDefault(), KSPSetConvergenceTest()
1170: @*/
1171: PetscErrorCode  KSPSetTolerances(KSP ksp,PetscReal rtol,PetscReal abstol,PetscReal dtol,PetscInt maxits)
1172: {

1180:   if (rtol != PETSC_DEFAULT) {
1181:     if (rtol < 0.0 || 1.0 <= rtol) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Relative tolerance %g must be non-negative and less than 1.0",(double)rtol);
1182:     ksp->rtol = rtol;
1183:   }
1184:   if (abstol != PETSC_DEFAULT) {
1185:     if (abstol < 0.0) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Absolute tolerance %g must be non-negative",(double)abstol);
1186:     ksp->abstol = abstol;
1187:   }
1188:   if (dtol != PETSC_DEFAULT) {
1189:     if (dtol < 0.0) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Divergence tolerance %g must be larger than 1.0",(double)dtol);
1190:     ksp->divtol = dtol;
1191:   }
1192:   if (maxits != PETSC_DEFAULT) {
1193:     if (maxits < 0) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Maximum number of iterations %D must be non-negative",maxits);
1194:     ksp->max_it = maxits;
1195:   }
1196:   return(0);
1197: }

1199: /*@
1200:    KSPSetInitialGuessNonzero - Tells the iterative solver that the
1201:    initial guess is nonzero; otherwise KSP assumes the initial guess
1202:    is to be zero (and thus zeros it out before solving).

1204:    Logically Collective on KSP

1206:    Input Parameters:
1207: +  ksp - iterative context obtained from KSPCreate()
1208: -  flg - PETSC_TRUE indicates the guess is non-zero, PETSC_FALSE indicates the guess is zero

1210:    Options database keys:
1211: .  -ksp_initial_guess_nonzero : use nonzero initial guess; this takes an optional truth value (0/1/no/yes/true/false)

1213:    Level: beginner

1215:    Notes:
1216:     If this is not called the X vector is zeroed in the call to KSPSolve().

1218: .keywords: KSP, set, initial guess, nonzero

1220: .seealso: KSPGetInitialGuessNonzero(), KSPSetGuessType(), KSPGuessType
1221: @*/
1222: PetscErrorCode  KSPSetInitialGuessNonzero(KSP ksp,PetscBool flg)
1223: {
1227:   ksp->guess_zero = (PetscBool) !(int)flg;
1228:   return(0);
1229: }

1231: /*@
1232:    KSPGetInitialGuessNonzero - Determines whether the KSP solver is using
1233:    a zero initial guess.

1235:    Not Collective

1237:    Input Parameter:
1238: .  ksp - iterative context obtained from KSPCreate()

1240:    Output Parameter:
1241: .  flag - PETSC_TRUE if guess is nonzero, else PETSC_FALSE

1243:    Level: intermediate

1245: .keywords: KSP, set, initial guess, nonzero

1247: .seealso: KSPSetInitialGuessNonzero()
1248: @*/
1249: PetscErrorCode  KSPGetInitialGuessNonzero(KSP ksp,PetscBool  *flag)
1250: {
1254:   if (ksp->guess_zero) *flag = PETSC_FALSE;
1255:   else *flag = PETSC_TRUE;
1256:   return(0);
1257: }

1259: /*@
1260:    KSPSetErrorIfNotConverged - Causes KSPSolve() to generate an error if the solver has not converged.

1262:    Logically Collective on KSP

1264:    Input Parameters:
1265: +  ksp - iterative context obtained from KSPCreate()
1266: -  flg - PETSC_TRUE indicates you want the error generated

1268:    Options database keys:
1269: .  -ksp_error_if_not_converged : this takes an optional truth value (0/1/no/yes/true/false)

1271:    Level: intermediate

1273:    Notes:
1274:     Normally PETSc continues if a linear solver fails to converge, you can call KSPGetConvergedReason() after a KSPSolve()
1275:     to determine if it has converged.

1277: .keywords: KSP

1279: .seealso: KSPGetErrorIfNotConverged()
1280: @*/
1281: PetscErrorCode  KSPSetErrorIfNotConverged(KSP ksp,PetscBool flg)
1282: {
1286:   ksp->errorifnotconverged = flg;
1287:   return(0);
1288: }

1290: /*@
1291:    KSPGetErrorIfNotConverged - Will KSPSolve() generate an error if the solver does not converge?

1293:    Not Collective

1295:    Input Parameter:
1296: .  ksp - iterative context obtained from KSPCreate()

1298:    Output Parameter:
1299: .  flag - PETSC_TRUE if it will generate an error, else PETSC_FALSE

1301:    Level: intermediate

1303: .keywords: KSP

1305: .seealso: KSPSetErrorIfNotConverged()
1306: @*/
1307: PetscErrorCode  KSPGetErrorIfNotConverged(KSP ksp,PetscBool  *flag)
1308: {
1312:   *flag = ksp->errorifnotconverged;
1313:   return(0);
1314: }

1316: /*@
1317:    KSPSetInitialGuessKnoll - Tells the iterative solver to use PCApply(pc,b,..) to compute the initial guess (The Knoll trick)

1319:    Logically Collective on KSP

1321:    Input Parameters:
1322: +  ksp - iterative context obtained from KSPCreate()
1323: -  flg - PETSC_TRUE or PETSC_FALSE

1325:    Level: advanced

1327:    Developer Note: the Knoll trick is not currently implemented using the KSPGuess class

1329: .keywords: KSP, set, initial guess, nonzero

1331: .seealso: KSPGetInitialGuessKnoll(), KSPSetInitialGuessNonzero(), KSPGetInitialGuessNonzero()
1332: @*/
1333: PetscErrorCode  KSPSetInitialGuessKnoll(KSP ksp,PetscBool flg)
1334: {
1338:   ksp->guess_knoll = flg;
1339:   return(0);
1340: }

1342: /*@
1343:    KSPGetInitialGuessKnoll - Determines whether the KSP solver is using the Knoll trick (using PCApply(pc,b,...) to compute
1344:      the initial guess

1346:    Not Collective

1348:    Input Parameter:
1349: .  ksp - iterative context obtained from KSPCreate()

1351:    Output Parameter:
1352: .  flag - PETSC_TRUE if using Knoll trick, else PETSC_FALSE

1354:    Level: advanced

1356: .keywords: KSP, set, initial guess, nonzero

1358: .seealso: KSPSetInitialGuessKnoll(), KSPSetInitialGuessNonzero(), KSPGetInitialGuessNonzero()
1359: @*/
1360: PetscErrorCode  KSPGetInitialGuessKnoll(KSP ksp,PetscBool  *flag)
1361: {
1365:   *flag = ksp->guess_knoll;
1366:   return(0);
1367: }

1369: /*@
1370:    KSPGetComputeSingularValues - Gets the flag indicating whether the extreme singular
1371:    values will be calculated via a Lanczos or Arnoldi process as the linear
1372:    system is solved.

1374:    Not Collective

1376:    Input Parameter:
1377: .  ksp - iterative context obtained from KSPCreate()

1379:    Output Parameter:
1380: .  flg - PETSC_TRUE or PETSC_FALSE

1382:    Options Database Key:
1383: .  -ksp_monitor_singular_value - Activates KSPSetComputeSingularValues()

1385:    Notes:
1386:    Currently this option is not valid for all iterative methods.

1388:    Many users may just want to use the monitoring routine
1389:    KSPMonitorSingularValue() (which can be set with option -ksp_monitor_singular_value)
1390:    to print the singular values at each iteration of the linear solve.

1392:    Level: advanced

1394: .keywords: KSP, set, compute, singular values

1396: .seealso: KSPComputeExtremeSingularValues(), KSPMonitorSingularValue()
1397: @*/
1398: PetscErrorCode  KSPGetComputeSingularValues(KSP ksp,PetscBool  *flg)
1399: {
1403:   *flg = ksp->calc_sings;
1404:   return(0);
1405: }

1407: /*@
1408:    KSPSetComputeSingularValues - Sets a flag so that the extreme singular
1409:    values will be calculated via a Lanczos or Arnoldi process as the linear
1410:    system is solved.

1412:    Logically Collective on KSP

1414:    Input Parameters:
1415: +  ksp - iterative context obtained from KSPCreate()
1416: -  flg - PETSC_TRUE or PETSC_FALSE

1418:    Options Database Key:
1419: .  -ksp_monitor_singular_value - Activates KSPSetComputeSingularValues()

1421:    Notes:
1422:    Currently this option is not valid for all iterative methods.

1424:    Many users may just want to use the monitoring routine
1425:    KSPMonitorSingularValue() (which can be set with option -ksp_monitor_singular_value)
1426:    to print the singular values at each iteration of the linear solve.

1428:    Level: advanced

1430: .keywords: KSP, set, compute, singular values

1432: .seealso: KSPComputeExtremeSingularValues(), KSPMonitorSingularValue()
1433: @*/
1434: PetscErrorCode  KSPSetComputeSingularValues(KSP ksp,PetscBool flg)
1435: {
1439:   ksp->calc_sings = flg;
1440:   return(0);
1441: }

1443: /*@
1444:    KSPGetComputeEigenvalues - Gets the flag indicating that the extreme eigenvalues
1445:    values will be calculated via a Lanczos or Arnoldi process as the linear
1446:    system is solved.

1448:    Not Collective

1450:    Input Parameter:
1451: .  ksp - iterative context obtained from KSPCreate()

1453:    Output Parameter:
1454: .  flg - PETSC_TRUE or PETSC_FALSE

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

1459:    Level: advanced

1461: .keywords: KSP, set, compute, eigenvalues

1463: .seealso: KSPComputeEigenvalues(), KSPComputeEigenvaluesExplicitly()
1464: @*/
1465: PetscErrorCode  KSPGetComputeEigenvalues(KSP ksp,PetscBool  *flg)
1466: {
1470:   *flg = ksp->calc_sings;
1471:   return(0);
1472: }

1474: /*@
1475:    KSPSetComputeEigenvalues - Sets a flag so that the extreme eigenvalues
1476:    values will be calculated via a Lanczos or Arnoldi process as the linear
1477:    system is solved.

1479:    Logically Collective on KSP

1481:    Input Parameters:
1482: +  ksp - iterative context obtained from KSPCreate()
1483: -  flg - PETSC_TRUE or PETSC_FALSE

1485:    Notes:
1486:    Currently this option is not valid for all iterative methods.

1488:    Level: advanced

1490: .keywords: KSP, set, compute, eigenvalues

1492: .seealso: KSPComputeEigenvalues(), KSPComputeEigenvaluesExplicitly()
1493: @*/
1494: PetscErrorCode  KSPSetComputeEigenvalues(KSP ksp,PetscBool flg)
1495: {
1499:   ksp->calc_sings = flg;
1500:   return(0);
1501: }

1503: /*@
1504:    KSPSetComputeRitz - Sets a flag so that the Ritz or harmonic Ritz pairs
1505:    will be calculated via a Lanczos or Arnoldi process as the linear
1506:    system is solved.

1508:    Logically Collective on KSP

1510:    Input Parameters:
1511: +  ksp - iterative context obtained from KSPCreate()
1512: -  flg - PETSC_TRUE or PETSC_FALSE

1514:    Notes:
1515:    Currently this option is only valid for the GMRES method.

1517:    Level: advanced

1519: .keywords: KSP, set, compute, ritz

1521: .seealso: KSPComputeRitz()
1522: @*/
1523: PetscErrorCode  KSPSetComputeRitz(KSP ksp, PetscBool flg)
1524: {
1528:   ksp->calc_ritz = flg;
1529:   return(0);
1530: }

1532: /*@
1533:    KSPGetRhs - Gets the right-hand-side vector for the linear system to
1534:    be solved.

1536:    Not Collective

1538:    Input Parameter:
1539: .  ksp - iterative context obtained from KSPCreate()

1541:    Output Parameter:
1542: .  r - right-hand-side vector

1544:    Level: developer

1546: .keywords: KSP, get, right-hand-side, rhs

1548: .seealso: KSPGetSolution(), KSPSolve()
1549: @*/
1550: PetscErrorCode  KSPGetRhs(KSP ksp,Vec *r)
1551: {
1555:   *r = ksp->vec_rhs;
1556:   return(0);
1557: }

1559: /*@
1560:    KSPGetSolution - Gets the location of the solution for the
1561:    linear system to be solved.  Note that this may not be where the solution
1562:    is stored during the iterative process; see KSPBuildSolution().

1564:    Not Collective

1566:    Input Parameters:
1567: .  ksp - iterative context obtained from KSPCreate()

1569:    Output Parameters:
1570: .  v - solution vector

1572:    Level: developer

1574: .keywords: KSP, get, solution

1576: .seealso: KSPGetRhs(),  KSPBuildSolution(), KSPSolve()
1577: @*/
1578: PetscErrorCode  KSPGetSolution(KSP ksp,Vec *v)
1579: {
1583:   *v = ksp->vec_sol;
1584:   return(0);
1585: }

1587: /*@
1588:    KSPSetPC - Sets the preconditioner to be used to calculate the
1589:    application of the preconditioner on a vector.

1591:    Collective on KSP

1593:    Input Parameters:
1594: +  ksp - iterative context obtained from KSPCreate()
1595: -  pc   - the preconditioner object

1597:    Notes:
1598:    Use KSPGetPC() to retrieve the preconditioner context (for example,
1599:    to free it at the end of the computations).

1601:    Level: developer

1603: .keywords: KSP, set, precondition, Binv

1605: .seealso: KSPGetPC()
1606: @*/
1607: PetscErrorCode  KSPSetPC(KSP ksp,PC pc)
1608: {

1615:   PetscObjectReference((PetscObject)pc);
1616:   PCDestroy(&ksp->pc);
1617:   ksp->pc = pc;
1618:   PetscLogObjectParent((PetscObject)ksp,(PetscObject)ksp->pc);
1619:   return(0);
1620: }

1622: /*@
1623:    KSPGetPC - Returns a pointer to the preconditioner context
1624:    set with KSPSetPC().

1626:    Not Collective

1628:    Input Parameters:
1629: .  ksp - iterative context obtained from KSPCreate()

1631:    Output Parameter:
1632: .  pc - preconditioner context

1634:    Level: developer

1636: .keywords: KSP, get, preconditioner, Binv

1638: .seealso: KSPSetPC()
1639: @*/
1640: PetscErrorCode  KSPGetPC(KSP ksp,PC *pc)
1641: {

1647:   if (!ksp->pc) {
1648:     PCCreate(PetscObjectComm((PetscObject)ksp),&ksp->pc);
1649:     PetscObjectIncrementTabLevel((PetscObject)ksp->pc,(PetscObject)ksp,0);
1650:     PetscLogObjectParent((PetscObject)ksp,(PetscObject)ksp->pc);
1651:   }
1652:   *pc = ksp->pc;
1653:   return(0);
1654: }

1656: /*@
1657:    KSPMonitor - runs the user provided monitor routines, if they exist

1659:    Collective on KSP

1661:    Input Parameters:
1662: +  ksp - iterative context obtained from KSPCreate()
1663: .  it - iteration number
1664: -  rnorm - relative norm of the residual

1666:    Notes:
1667:    This routine is called by the KSP implementations.
1668:    It does not typically need to be called by the user.

1670:    Level: developer

1672: .seealso: KSPMonitorSet()
1673: @*/
1674: PetscErrorCode KSPMonitor(KSP ksp,PetscInt it,PetscReal rnorm)
1675: {
1676:   PetscInt       i, n = ksp->numbermonitors;

1680:   for (i=0; i<n; i++) {
1681:     (*ksp->monitor[i])(ksp,it,rnorm,ksp->monitorcontext[i]);
1682:   }
1683:   return(0);
1684: }

1686: /*

1688:     Checks if two monitors are identical; if they are then it destroys the new one
1689: */
1690: PetscErrorCode PetscMonitorCompare(PetscErrorCode (*nmon)(void),void *nmctx,PetscErrorCode (*nmdestroy)(void**),PetscErrorCode (*mon)(void),void *mctx,PetscErrorCode (*mdestroy)(void**),PetscBool *identical)
1691: {
1692:   *identical = PETSC_FALSE;
1693:   if (nmon == mon && nmdestroy == mdestroy) {
1694:     if (nmctx == mctx) *identical = PETSC_TRUE;
1695:     else if (nmdestroy == (PetscErrorCode (*)(void**)) PetscViewerAndFormatDestroy) {
1696:       PetscViewerAndFormat *old = (PetscViewerAndFormat*)mctx, *newo = (PetscViewerAndFormat*)nmctx;
1697:       if (old->viewer == newo->viewer && old->format == newo->format) *identical = PETSC_TRUE;
1698:     }
1699:     if (*identical) {
1700:       if (mdestroy) {
1702:         (*mdestroy)(&nmctx);
1703:       }
1704:     }
1705:   }
1706:   return(0);
1707: }

1709: /*@C
1710:    KSPMonitorSet - Sets an ADDITIONAL function to be called at every iteration to monitor
1711:    the residual/error etc.

1713:    Logically Collective on KSP

1715:    Input Parameters:
1716: +  ksp - iterative context obtained from KSPCreate()
1717: .  monitor - pointer to function (if this is NULL, it turns off monitoring
1718: .  mctx    - [optional] context for private data for the
1719:              monitor routine (use NULL if no context is desired)
1720: -  monitordestroy - [optional] routine that frees monitor context
1721:           (may be NULL)

1723:    Calling Sequence of monitor:
1724: $     monitor (KSP ksp, int it, PetscReal rnorm, void *mctx)

1726: +  ksp - iterative context obtained from KSPCreate()
1727: .  it - iteration number
1728: .  rnorm - (estimated) 2-norm of (preconditioned) residual
1729: -  mctx  - optional monitoring context, as set by KSPMonitorSet()

1731:    Options Database Keys:
1732: +    -ksp_monitor        - sets KSPMonitorDefault()
1733: .    -ksp_monitor_true_residual    - sets KSPMonitorTrueResidualNorm()
1734: .    -ksp_monitor_max    - sets KSPMonitorTrueResidualMaxNorm()
1735: .    -ksp_monitor_lg_residualnorm    - sets line graph monitor,
1736:                            uses KSPMonitorLGResidualNormCreate()
1737: .    -ksp_monitor_lg_true_residualnorm   - sets line graph monitor,
1738:                            uses KSPMonitorLGResidualNormCreate()
1739: .    -ksp_monitor_singular_value    - sets KSPMonitorSingularValue()
1740: -    -ksp_monitor_cancel - cancels all monitors that have
1741:                           been hardwired into a code by
1742:                           calls to KSPMonitorSet(), but
1743:                           does not cancel those set via
1744:                           the options database.

1746:    Notes:
1747:    The default is to do nothing.  To print the residual, or preconditioned
1748:    residual if KSPSetNormType(ksp,KSP_NORM_PRECONDITIONED) was called, use
1749:    KSPMonitorDefault() as the monitoring routine, with a ASCII viewer as the
1750:    context.

1752:    Several different monitoring routines may be set by calling
1753:    KSPMonitorSet() multiple times; all will be called in the
1754:    order in which they were set.

1756:    Fortran notes: Only a single monitor function can be set for each KSP object

1758:    Level: beginner

1760: .keywords: KSP, set, monitor

1762: .seealso: KSPMonitorDefault(), KSPMonitorLGResidualNormCreate(), KSPMonitorCancel()
1763: @*/
1764: PetscErrorCode  KSPMonitorSet(KSP ksp,PetscErrorCode (*monitor)(KSP,PetscInt,PetscReal,void*),void *mctx,PetscErrorCode (*monitordestroy)(void**))
1765: {
1766:   PetscInt       i;
1768:   PetscBool      identical;

1772:   for (i=0; i<ksp->numbermonitors;i++) {
1773:     PetscMonitorCompare((PetscErrorCode (*)(void))monitor,mctx,monitordestroy,(PetscErrorCode (*)(void))ksp->monitor[i],ksp->monitorcontext[i],ksp->monitordestroy[i],&identical);
1774:     if (identical) return(0);
1775:   }
1776:   if (ksp->numbermonitors >= MAXKSPMONITORS) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Too many KSP monitors set");
1777:   ksp->monitor[ksp->numbermonitors]          = monitor;
1778:   ksp->monitordestroy[ksp->numbermonitors]   = monitordestroy;
1779:   ksp->monitorcontext[ksp->numbermonitors++] = (void*)mctx;
1780:   return(0);
1781: }

1783: /*@
1784:    KSPMonitorCancel - Clears all monitors for a KSP object.

1786:    Logically Collective on KSP

1788:    Input Parameters:
1789: .  ksp - iterative context obtained from KSPCreate()

1791:    Options Database Key:
1792: .  -ksp_monitor_cancel - Cancels all monitors that have
1793:     been hardwired into a code by calls to KSPMonitorSet(),
1794:     but does not cancel those set via the options database.

1796:    Level: intermediate

1798: .keywords: KSP, set, monitor

1800: .seealso: KSPMonitorDefault(), KSPMonitorLGResidualNormCreate(), KSPMonitorSet()
1801: @*/
1802: PetscErrorCode  KSPMonitorCancel(KSP ksp)
1803: {
1805:   PetscInt       i;

1809:   for (i=0; i<ksp->numbermonitors; i++) {
1810:     if (ksp->monitordestroy[i]) {
1811:       (*ksp->monitordestroy[i])(&ksp->monitorcontext[i]);
1812:     }
1813:   }
1814:   ksp->numbermonitors = 0;
1815:   return(0);
1816: }

1818: /*@C
1819:    KSPGetMonitorContext - Gets the monitoring context, as set by
1820:    KSPMonitorSet() for the FIRST monitor only.

1822:    Not Collective

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

1827:    Output Parameter:
1828: .  ctx - monitoring context

1830:    Level: intermediate

1832: .keywords: KSP, get, monitor, context

1834: .seealso: KSPMonitorDefault(), KSPMonitorLGResidualNormCreate()
1835: @*/
1836: PetscErrorCode  KSPGetMonitorContext(KSP ksp,void **ctx)
1837: {
1840:   *ctx =      (ksp->monitorcontext[0]);
1841:   return(0);
1842: }

1844: /*@
1845:    KSPSetResidualHistory - Sets the array used to hold the residual history.
1846:    If set, this array will contain the residual norms computed at each
1847:    iteration of the solver.

1849:    Not Collective

1851:    Input Parameters:
1852: +  ksp - iterative context obtained from KSPCreate()
1853: .  a   - array to hold history
1854: .  na  - size of a
1855: -  reset - PETSC_TRUE indicates the history counter is reset to zero
1856:            for each new linear solve

1858:    Level: advanced

1860:    Notes: The array is NOT freed by PETSc so the user needs to keep track of
1861:            it and destroy once the KSP object is destroyed.

1863:    If 'a' is NULL then space is allocated for the history. If 'na' PETSC_DECIDE or PETSC_DEFAULT then a
1864:    default array of length 10000 is allocated.

1866: .keywords: KSP, set, residual, history, norm

1868: .seealso: KSPGetResidualHistory()

1870: @*/
1871: PetscErrorCode  KSPSetResidualHistory(KSP ksp,PetscReal a[],PetscInt na,PetscBool reset)
1872: {


1878:   PetscFree(ksp->res_hist_alloc);
1879:   if (na != PETSC_DECIDE && na != PETSC_DEFAULT && a) {
1880:     ksp->res_hist     = a;
1881:     ksp->res_hist_max = na;
1882:   } else {
1883:     if (na != PETSC_DECIDE && na != PETSC_DEFAULT) ksp->res_hist_max = na;
1884:     else                                           ksp->res_hist_max = 10000; /* like default ksp->max_it */
1885:     PetscCalloc1(ksp->res_hist_max,&ksp->res_hist_alloc);

1887:     ksp->res_hist = ksp->res_hist_alloc;
1888:   }
1889:   ksp->res_hist_len   = 0;
1890:   ksp->res_hist_reset = reset;
1891:   return(0);
1892: }

1894: /*@C
1895:    KSPGetResidualHistory - Gets the array used to hold the residual history
1896:    and the number of residuals it contains.

1898:    Not Collective

1900:    Input Parameter:
1901: .  ksp - iterative context obtained from KSPCreate()

1903:    Output Parameters:
1904: +  a   - pointer to array to hold history (or NULL)
1905: -  na  - number of used entries in a (or NULL)

1907:    Level: advanced

1909:    Notes:
1910:      Can only be called after a KSPSetResidualHistory() otherwise a and na are set to zero

1912:      The Fortran version of this routine has a calling sequence
1913: $   call KSPGetResidualHistory(KSP ksp, integer na, integer ierr)
1914:     note that you have passed a Fortran array into KSPSetResidualHistory() and you need
1915:     to access the residual values from this Fortran array you provided. Only the na (number of
1916:     residual norms currently held) is set.

1918: .keywords: KSP, get, residual, history, norm

1920: .seealso: KSPGetResidualHistory()

1922: @*/
1923: PetscErrorCode  KSPGetResidualHistory(KSP ksp,PetscReal *a[],PetscInt *na)
1924: {
1927:   if (a) *a = ksp->res_hist;
1928:   if (na) *na = ksp->res_hist_len;
1929:   return(0);
1930: }

1932: /*@C
1933:    KSPSetConvergenceTest - Sets the function to be used to determine
1934:    convergence.

1936:    Logically Collective on KSP

1938:    Input Parameters:
1939: +  ksp - iterative context obtained from KSPCreate()
1940: .  converge - pointer to int function
1941: .  cctx    - context for private data for the convergence routine (may be null)
1942: -  destroy - a routine for destroying the context (may be null)

1944:    Calling sequence of converge:
1945: $     converge (KSP ksp, int it, PetscReal rnorm, KSPConvergedReason *reason,void *mctx)

1947: +  ksp - iterative context obtained from KSPCreate()
1948: .  it - iteration number
1949: .  rnorm - (estimated) 2-norm of (preconditioned) residual
1950: .  reason - the reason why it has converged or diverged
1951: -  cctx  - optional convergence context, as set by KSPSetConvergenceTest()


1954:    Notes:
1955:    Must be called after the KSP type has been set so put this after
1956:    a call to KSPSetType(), or KSPSetFromOptions().

1958:    The default convergence test, KSPConvergedDefault(), aborts if the
1959:    residual grows to more than 10000 times the initial residual.

1961:    The default is a combination of relative and absolute tolerances.
1962:    The residual value that is tested may be an approximation; routines
1963:    that need exact values should compute them.

1965:    In the default PETSc convergence test, the precise values of reason
1966:    are macros such as KSP_CONVERGED_RTOL, which are defined in petscksp.h.

1968:    Level: advanced

1970: .keywords: KSP, set, convergence, test, context

1972: .seealso: KSPConvergedDefault(), KSPGetConvergenceContext(), KSPSetTolerances()
1973: @*/
1974: PetscErrorCode  KSPSetConvergenceTest(KSP ksp,PetscErrorCode (*converge)(KSP,PetscInt,PetscReal,KSPConvergedReason*,void*),void *cctx,PetscErrorCode (*destroy)(void*))
1975: {

1980:   if (ksp->convergeddestroy) {
1981:     (*ksp->convergeddestroy)(ksp->cnvP);
1982:   }
1983:   ksp->converged        = converge;
1984:   ksp->convergeddestroy = destroy;
1985:   ksp->cnvP             = (void*)cctx;
1986:   return(0);
1987: }

1989: /*@C
1990:    KSPGetConvergenceContext - Gets the convergence context set with
1991:    KSPSetConvergenceTest().

1993:    Not Collective

1995:    Input Parameter:
1996: .  ksp - iterative context obtained from KSPCreate()

1998:    Output Parameter:
1999: .  ctx - monitoring context

2001:    Level: advanced

2003: .keywords: KSP, get, convergence, test, context

2005: .seealso: KSPConvergedDefault(), KSPSetConvergenceTest()
2006: @*/
2007: PetscErrorCode  KSPGetConvergenceContext(KSP ksp,void **ctx)
2008: {
2011:   *ctx = ksp->cnvP;
2012:   return(0);
2013: }

2015: /*@C
2016:    KSPBuildSolution - Builds the approximate solution in a vector provided.
2017:    This routine is NOT commonly needed (see KSPSolve()).

2019:    Collective on KSP

2021:    Input Parameter:
2022: .  ctx - iterative context obtained from KSPCreate()

2024:    Output Parameter:
2025:    Provide exactly one of
2026: +  v - location to stash solution.
2027: -  V - the solution is returned in this location. This vector is created
2028:        internally. This vector should NOT be destroyed by the user with
2029:        VecDestroy().

2031:    Notes:
2032:    This routine can be used in one of two ways
2033: .vb
2034:       KSPBuildSolution(ksp,NULL,&V);
2035:    or
2036:       KSPBuildSolution(ksp,v,NULL); or KSPBuildSolution(ksp,v,&v);
2037: .ve
2038:    In the first case an internal vector is allocated to store the solution
2039:    (the user cannot destroy this vector). In the second case the solution
2040:    is generated in the vector that the user provides. Note that for certain
2041:    methods, such as KSPCG, the second case requires a copy of the solution,
2042:    while in the first case the call is essentially free since it simply
2043:    returns the vector where the solution already is stored. For some methods
2044:    like GMRES this is a reasonably expensive operation and should only be
2045:    used in truly needed.

2047:    Level: advanced

2049: .keywords: KSP, build, solution

2051: .seealso: KSPGetSolution(), KSPBuildResidual()
2052: @*/
2053: PetscErrorCode  KSPBuildSolution(KSP ksp,Vec v,Vec *V)
2054: {

2059:   if (!V && !v) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_WRONG,"Must provide either v or V");
2060:   if (!V) V = &v;
2061:   (*ksp->ops->buildsolution)(ksp,v,V);
2062:   return(0);
2063: }

2065: /*@C
2066:    KSPBuildResidual - Builds the residual in a vector provided.

2068:    Collective on KSP

2070:    Input Parameter:
2071: .  ksp - iterative context obtained from KSPCreate()

2073:    Output Parameters:
2074: +  v - optional location to stash residual.  If v is not provided,
2075:        then a location is generated.
2076: .  t - work vector.  If not provided then one is generated.
2077: -  V - the residual

2079:    Notes:
2080:    Regardless of whether or not v is provided, the residual is
2081:    returned in V.

2083:    Level: advanced

2085: .keywords: KSP, build, residual

2087: .seealso: KSPBuildSolution()
2088: @*/
2089: PetscErrorCode  KSPBuildResidual(KSP ksp,Vec t,Vec v,Vec *V)
2090: {
2092:   PetscBool      flag = PETSC_FALSE;
2093:   Vec            w    = v,tt = t;

2097:   if (!w) {
2098:     VecDuplicate(ksp->vec_rhs,&w);
2099:     PetscLogObjectParent((PetscObject)ksp,(PetscObject)w);
2100:   }
2101:   if (!tt) {
2102:     VecDuplicate(ksp->vec_sol,&tt); flag = PETSC_TRUE;
2103:     PetscLogObjectParent((PetscObject)ksp,(PetscObject)tt);
2104:   }
2105:   (*ksp->ops->buildresidual)(ksp,tt,w,V);
2106:   if (flag) {VecDestroy(&tt);}
2107:   return(0);
2108: }

2110: /*@
2111:    KSPSetDiagonalScale - Tells KSP to symmetrically diagonally scale the system
2112:      before solving. This actually CHANGES the matrix (and right hand side).

2114:    Logically Collective on KSP

2116:    Input Parameter:
2117: +  ksp - the KSP context
2118: -  scale - PETSC_TRUE or PETSC_FALSE

2120:    Options Database Key:
2121: +   -ksp_diagonal_scale -
2122: -   -ksp_diagonal_scale_fix - scale the matrix back AFTER the solve


2125:     Notes: Scales the matrix by  D^(-1/2)  A  D^(-1/2)  [D^(1/2) x ] = D^(-1/2) b
2126:        where D_{ii} is 1/abs(A_{ii}) unless A_{ii} is zero and then it is 1.

2128:     BE CAREFUL with this routine: it actually scales the matrix and right
2129:     hand side that define the system. After the system is solved the matrix
2130:     and right hand side remain scaled unless you use KSPSetDiagonalScaleFix()

2132:     This should NOT be used within the SNES solves if you are using a line
2133:     search.

2135:     If you use this with the PCType Eisenstat preconditioner than you can
2136:     use the PCEisenstatSetNoDiagonalScaling() option, or -pc_eisenstat_no_diagonal_scaling
2137:     to save some unneeded, redundant flops.

2139:    Level: intermediate

2141: .keywords: KSP, set, options, prefix, database

2143: .seealso: KSPGetDiagonalScale(), KSPSetDiagonalScaleFix()
2144: @*/
2145: PetscErrorCode  KSPSetDiagonalScale(KSP ksp,PetscBool scale)
2146: {
2150:   ksp->dscale = scale;
2151:   return(0);
2152: }

2154: /*@
2155:    KSPGetDiagonalScale - Checks if KSP solver scales the matrix and
2156:                           right hand side

2158:    Not Collective

2160:    Input Parameter:
2161: .  ksp - the KSP context

2163:    Output Parameter:
2164: .  scale - PETSC_TRUE or PETSC_FALSE

2166:    Notes:
2167:     BE CAREFUL with this routine: it actually scales the matrix and right
2168:     hand side that define the system. After the system is solved the matrix
2169:     and right hand side remain scaled  unless you use KSPSetDiagonalScaleFix()

2171:    Level: intermediate

2173: .keywords: KSP, set, options, prefix, database

2175: .seealso: KSPSetDiagonalScale(), KSPSetDiagonalScaleFix()
2176: @*/
2177: PetscErrorCode  KSPGetDiagonalScale(KSP ksp,PetscBool  *scale)
2178: {
2182:   *scale = ksp->dscale;
2183:   return(0);
2184: }

2186: /*@
2187:    KSPSetDiagonalScaleFix - Tells KSP to diagonally scale the system
2188:      back after solving.

2190:    Logically Collective on KSP

2192:    Input Parameter:
2193: +  ksp - the KSP context
2194: -  fix - PETSC_TRUE to scale back after the system solve, PETSC_FALSE to not
2195:          rescale (default)

2197:    Notes:
2198:      Must be called after KSPSetDiagonalScale()

2200:      Using this will slow things down, because it rescales the matrix before and
2201:      after each linear solve. This is intended mainly for testing to allow one
2202:      to easily get back the original system to make sure the solution computed is
2203:      accurate enough.

2205:    Level: intermediate

2207: .keywords: KSP, set, options, prefix, database

2209: .seealso: KSPGetDiagonalScale(), KSPSetDiagonalScale(), KSPGetDiagonalScaleFix()
2210: @*/
2211: PetscErrorCode  KSPSetDiagonalScaleFix(KSP ksp,PetscBool fix)
2212: {
2216:   ksp->dscalefix = fix;
2217:   return(0);
2218: }

2220: /*@
2221:    KSPGetDiagonalScaleFix - Determines if KSP diagonally scales the system
2222:      back after solving.

2224:    Not Collective

2226:    Input Parameter:
2227: .  ksp - the KSP context

2229:    Output Parameter:
2230: .  fix - PETSC_TRUE to scale back after the system solve, PETSC_FALSE to not
2231:          rescale (default)

2233:    Notes:
2234:      Must be called after KSPSetDiagonalScale()

2236:      If PETSC_TRUE will slow things down, because it rescales the matrix before and
2237:      after each linear solve. This is intended mainly for testing to allow one
2238:      to easily get back the original system to make sure the solution computed is
2239:      accurate enough.

2241:    Level: intermediate

2243: .keywords: KSP, set, options, prefix, database

2245: .seealso: KSPGetDiagonalScale(), KSPSetDiagonalScale(), KSPSetDiagonalScaleFix()
2246: @*/
2247: PetscErrorCode  KSPGetDiagonalScaleFix(KSP ksp,PetscBool  *fix)
2248: {
2252:   *fix = ksp->dscalefix;
2253:   return(0);
2254: }

2256: /*@C
2257:    KSPSetComputeOperators - set routine to compute the linear operators

2259:    Logically Collective

2261:    Input Arguments:
2262: +  ksp - the KSP context
2263: .  func - function to compute the operators
2264: -  ctx - optional context

2266:    Calling sequence of func:
2267: $  func(KSP ksp,Mat A,Mat B,void *ctx)

2269: +  ksp - the KSP context
2270: .  A - the linear operator
2271: .  B - preconditioning matrix
2272: -  ctx - optional user-provided context

2274:    Notes: The user provided func() will be called automatically at the very next call to KSPSolve(). It will not be called at future KSPSolve() calls
2275:           unless either KSPSetComputeOperators() or KSPSetOperators() is called before that KSPSolve() is called.

2277:           To reuse the same preconditioner for the next KSPSolve() and not compute a new one based on the most recently computed matrix call KSPSetReusePreconditioner()

2279:    Level: beginner

2281: .seealso: KSPSetOperators(), KSPSetComputeRHS(), DMKSPSetComputeOperators(), KSPSetComputeInitialGuess()
2282: @*/
2283: PetscErrorCode KSPSetComputeOperators(KSP ksp,PetscErrorCode (*func)(KSP,Mat,Mat,void*),void *ctx)
2284: {
2286:   DM             dm;

2290:   KSPGetDM(ksp,&dm);
2291:   DMKSPSetComputeOperators(dm,func,ctx);
2292:   if (ksp->setupstage == KSP_SETUP_NEWRHS) ksp->setupstage = KSP_SETUP_NEWMATRIX;
2293:   return(0);
2294: }

2296: /*@C
2297:    KSPSetComputeRHS - set routine to compute the right hand side of the linear system

2299:    Logically Collective

2301:    Input Arguments:
2302: +  ksp - the KSP context
2303: .  func - function to compute the right hand side
2304: -  ctx - optional context

2306:    Calling sequence of func:
2307: $  func(KSP ksp,Vec b,void *ctx)

2309: +  ksp - the KSP context
2310: .  b - right hand side of linear system
2311: -  ctx - optional user-provided context

2313:    Notes: The routine you provide will be called EACH you call KSPSolve() to prepare the new right hand side for that solve

2315:    Level: beginner

2317: .seealso: KSPSolve(), DMKSPSetComputeRHS(), KSPSetComputeOperators()
2318: @*/
2319: PetscErrorCode KSPSetComputeRHS(KSP ksp,PetscErrorCode (*func)(KSP,Vec,void*),void *ctx)
2320: {
2322:   DM             dm;

2326:   KSPGetDM(ksp,&dm);
2327:   DMKSPSetComputeRHS(dm,func,ctx);
2328:   return(0);
2329: }

2331: /*@C
2332:    KSPSetComputeInitialGuess - set routine to compute the initial guess of the linear system

2334:    Logically Collective

2336:    Input Arguments:
2337: +  ksp - the KSP context
2338: .  func - function to compute the initial guess
2339: -  ctx - optional context

2341:    Calling sequence of func:
2342: $  func(KSP ksp,Vec x,void *ctx)

2344: +  ksp - the KSP context
2345: .  x - solution vector
2346: -  ctx - optional user-provided context

2348:    Level: beginner

2350: .seealso: KSPSolve(), KSPSetComputeRHS(), KSPSetComputeOperators(), DMKSPSetComputeInitialGuess()
2351: @*/
2352: PetscErrorCode KSPSetComputeInitialGuess(KSP ksp,PetscErrorCode (*func)(KSP,Vec,void*),void *ctx)
2353: {
2355:   DM             dm;

2359:   KSPGetDM(ksp,&dm);
2360:   DMKSPSetComputeInitialGuess(dm,func,ctx);
2361:   return(0);
2362: }