Actual source code: itfunc.c

petsc-3.5.4 2015-05-23
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  2: /*
  3:       Interface KSP routines that the user calls.
  4: */

  6: #include <petsc-private/kspimpl.h>   /*I "petscksp.h" I*/
  7: #include <petscdm.h>

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

 15:    Not Collective

 17:    Input Parameter:
 18: .  ksp - iterative context obtained from KSPCreate()

 20:    Output Parameters:
 21: .  emin, emax - extreme singular values

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

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

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

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

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

 41:    Level: advanced

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

 45: .seealso: KSPSetComputeSingularValues(), KSPMonitorSingularValue(), KSPComputeEigenvalues()
 46: @*/
 47: PetscErrorCode  KSPComputeExtremeSingularValues(KSP ksp,PetscReal *emax,PetscReal *emin)
 48: {

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

 57:   if (ksp->ops->computeextremesingularvalues) {
 58:     (*ksp->ops->computeextremesingularvalues)(ksp,emax,emin);
 59:   } else {
 60:     *emin = -1.0;
 61:     *emax = -1.0;
 62:   }
 63:   return(0);
 64: }

 68: /*@
 69:    KSPComputeEigenvalues - Computes the extreme eigenvalues for the
 70:    preconditioned operator. Called after or during KSPSolve().

 72:    Not Collective

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

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

 84:    Options Database Keys:
 85: +  -ksp_compute_eigenvalues - Prints eigenvalues to stdout
 86: -  -ksp_plot_eigenvalues - Plots eigenvalues in an x-window display

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

 95:    KSPComputeEigenvalues() does not usually provide accurate estimates; it is
 96:    intended only for assistance in understanding the convergence of iterative
 97:    methods, not for eigenanalysis. For accurate computation of eigenvalues we recommend using
 98:    the excellant package SLEPc.

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

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

107:    Level: advanced

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

111: .seealso: KSPSetComputeSingularValues(), KSPMonitorSingularValue(), KSPComputeExtremeSingularValues()
112: @*/
113: PetscErrorCode  KSPComputeEigenvalues(KSP ksp,PetscInt n,PetscReal r[],PetscReal c[],PetscInt *neig)
114: {

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

125:   if (ksp->ops->computeeigenvalues) {
126:     (*ksp->ops->computeeigenvalues)(ksp,n,r,c,neig);
127:   } else {
128:     *neig = 0;
129:   }
130:   return(0);
131: }

135: /*@
136:    KSPSetUpOnBlocks - Sets up the preconditioner for each block in
137:    the block Jacobi, block Gauss-Seidel, and overlapping Schwarz
138:    methods.

140:    Collective on KSP

142:    Input Parameter:
143: .  ksp - the KSP context

145:    Notes:
146:    KSPSetUpOnBlocks() is a routine that the user can optinally call for
147:    more precise profiling (via -log_summary) of the setup phase for these
148:    block preconditioners.  If the user does not call KSPSetUpOnBlocks(),
149:    it will automatically be called from within KSPSolve().

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

154:    Level: advanced

156: .keywords: KSP, setup, blocks

158: .seealso: PCSetUpOnBlocks(), KSPSetUp(), PCSetUp()
159: @*/
160: PetscErrorCode  KSPSetUpOnBlocks(KSP ksp)
161: {

166:   if (!ksp->pc) {KSPGetPC(ksp,&ksp->pc);}
167:   PCSetUpOnBlocks(ksp->pc);
168:   return(0);
169: }

173: /*@
174:    KSPSetReusePreconditioner - reuse the current preconditioner, do not construct a new one even if the operator changes

176:    Collective on KSP

178:    Input Parameters:
179: +  ksp   - iterative context obtained from KSPCreate()
180: -  flag - PETSC_TRUE to reuse the current preconditioner

182:    Level: intermediate

184: .keywords: KSP, setup

186: .seealso: KSPCreate(), KSPSolve(), KSPDestroy(), PCSetReusePreconditioner()
187: @*/
188: PetscErrorCode  KSPSetReusePreconditioner(KSP ksp,PetscBool flag)
189: {

194:   PCSetReusePreconditioner(ksp->pc,flag);
195:   return(0);
196: }

200: /*@
201:    KSPSetUp - Sets up the internal data structures for the
202:    later use of an iterative solver.

204:    Collective on KSP

206:    Input Parameter:
207: .  ksp   - iterative context obtained from KSPCreate()

209:    Level: developer

211: .keywords: KSP, setup

213: .seealso: KSPCreate(), KSPSolve(), KSPDestroy()
214: @*/
215: PetscErrorCode  KSPSetUp(KSP ksp)
216: {
218:   Mat            A,B;


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

226:   if (!((PetscObject)ksp)->type_name) {
227:     KSPSetType(ksp,KSPGMRES);
228:   }
229:   KSPSetUpNorms_Private(ksp,&ksp->normtype,&ksp->pc_side);

231:   if (ksp->dmActive && !ksp->setupstage) {
232:     /* first time in so build matrix and vector data structures using DM */
233:     if (!ksp->vec_rhs) {DMCreateGlobalVector(ksp->dm,&ksp->vec_rhs);}
234:     if (!ksp->vec_sol) {DMCreateGlobalVector(ksp->dm,&ksp->vec_sol);}
235:     DMCreateMatrix(ksp->dm,&A);
236:     KSPSetOperators(ksp,A,A);
237:     PetscObjectDereference((PetscObject)A);
238:   }

240:   if (ksp->dmActive) {
241:     DMKSP kdm;
242:     DMGetDMKSP(ksp->dm,&kdm);

244:     if (kdm->ops->computeinitialguess && ksp->setupstage != KSP_SETUP_NEWRHS) {
245:       /* only computes initial guess the first time through */
246:       (*kdm->ops->computeinitialguess)(ksp,ksp->vec_sol,kdm->initialguessctx);
247:       KSPSetInitialGuessNonzero(ksp,PETSC_TRUE);
248:     }
249:     if (kdm->ops->computerhs) {
250:       (*kdm->ops->computerhs)(ksp,ksp->vec_rhs,kdm->rhsctx);
251:     }

253:     if (ksp->setupstage != KSP_SETUP_NEWRHS) {
254:       if (kdm->ops->computeoperators) {
255:         KSPGetOperators(ksp,&A,&B);
256:         (*kdm->ops->computeoperators)(ksp,A,B,kdm->operatorsctx);
257:         KSPSetOperators(ksp,A,B);
258:       } else SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_WRONGSTATE,"You called KSPSetDM() but did not use DMKSPSetComputeOperators() or KSPSetDMActive(dm,PETSC_FALSE);");
259:     }
260:   }

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

265:   switch (ksp->setupstage) {
266:   case KSP_SETUP_NEW:
267:     (*ksp->ops->setup)(ksp);
268:     break;
269:   case KSP_SETUP_NEWMATRIX: {   /* This should be replaced with a more general mechanism */
270:     KSPChebyshevSetNewMatrix(ksp);
271:   } break;
272:   default: break;
273:   }

275:   /* scale the matrix if requested */
276:   if (ksp->dscale) {
277:     Mat         mat,pmat;
278:     PetscScalar *xx;
279:     PetscInt    i,n;
280:     PetscBool   zeroflag = PETSC_FALSE;
281:     if (!ksp->pc) {KSPGetPC(ksp,&ksp->pc);}
282:     PCGetOperators(ksp->pc,&mat,&pmat);
283:     if (!ksp->diagonal) { /* allocate vector to hold diagonal */
284:       MatGetVecs(pmat,&ksp->diagonal,0);
285:     }
286:     MatGetDiagonal(pmat,ksp->diagonal);
287:     VecGetLocalSize(ksp->diagonal,&n);
288:     VecGetArray(ksp->diagonal,&xx);
289:     for (i=0; i<n; i++) {
290:       if (xx[i] != 0.0) xx[i] = 1.0/PetscSqrtReal(PetscAbsScalar(xx[i]));
291:       else {
292:         xx[i]    = 1.0;
293:         zeroflag = PETSC_TRUE;
294:       }
295:     }
296:     VecRestoreArray(ksp->diagonal,&xx);
297:     if (zeroflag) {
298:       PetscInfo(ksp,"Zero detected in diagonal of matrix, using 1 at those locations\n");
299:     }
300:     MatDiagonalScale(pmat,ksp->diagonal,ksp->diagonal);
301:     if (mat != pmat) {MatDiagonalScale(mat,ksp->diagonal,ksp->diagonal);}
302:     ksp->dscalefix2 = PETSC_FALSE;
303:   }
304:   PetscLogEventEnd(KSP_SetUp,ksp,ksp->vec_rhs,ksp->vec_sol,0);
305:   if (!ksp->pc) {KSPGetPC(ksp,&ksp->pc);}
306:   PCSetUp(ksp->pc);
307:   if (ksp->nullsp) {
308:     PetscBool test = PETSC_FALSE;
309:     PetscOptionsGetBool(((PetscObject)ksp)->prefix,"-ksp_test_null_space",&test,NULL);
310:     if (test) {
311:       Mat mat;
312:       PCGetOperators(ksp->pc,&mat,NULL);
313:       MatNullSpaceTest(ksp->nullsp,mat,NULL);
314:     }
315:   }
316:   ksp->setupstage = KSP_SETUP_NEWRHS;
317:   return(0);
318: }

320: #include <petscdraw.h>
323: /*@
324:    KSPSolve - Solves linear system.

326:    Collective on KSP

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

333:    Options Database Keys:
334: +  -ksp_compute_eigenvalues - compute preconditioned operators eigenvalues
335: .  -ksp_plot_eigenvalues - plot the computed eigenvalues in an X-window
336: .  -ksp_compute_eigenvalues_explicitly - compute the eigenvalues by forming the dense operator and useing LAPACK
337: .  -ksp_plot_eigenvalues_explicitly - plot the explicitly computing eigenvalues
338: .  -ksp_view_mat binary - save matrix to the default binary viewer
339: .  -ksp_view_pmat binary - save matrix used to build preconditioner to the default binary viewer
340: .  -ksp_view_rhs binary - save right hand side vector to the default binary viewer
341: .  -ksp_view_solution binary - save computed solution vector to the default binary viewer
342:            (can be read later with src/ksp/examples/tutorials/ex10.c for testing solvers)
343: .  -ksp_view_mat_explicit - for matrix-free operators, computes the matrix entries and views them
344: .  -ksp_view_preconditioned_operator_explicit - computes the product of the preconditioner and matrix as an explicit matrix and views it
345: .  -ksp_converged_reason - print reason for converged or diverged, also prints number of iterations
346: .  -ksp_final_residual - print 2-norm of true linear system residual at the end of the solution process
347: -  -ksp_view - print the ksp data structure at the end of the system solution

349:    Notes:

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

353:    The operator is specified with KSPSetOperators().

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

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

363:    Understanding Convergence:
364:    The routines KSPMonitorSet(), KSPComputeEigenvalues(), and
365:    KSPComputeEigenvaluesExplicitly() provide information on additional
366:    options to monitor convergence and print eigenvalue information.

368:    Level: beginner

370: .keywords: KSP, solve, linear system

372: .seealso: KSPCreate(), KSPSetUp(), KSPDestroy(), KSPSetTolerances(), KSPConvergedDefault(),
373:           KSPSolveTranspose(), KSPGetIterationNumber()
374: @*/
375: PetscErrorCode  KSPSolve(KSP ksp,Vec b,Vec x)
376: {
377:   PetscErrorCode    ierr;
378:   PetscMPIInt       rank;
379:   PetscBool         flag1,flag2,flag3,flg = PETSC_FALSE,inXisinB=PETSC_FALSE,guess_zero;
380:   Mat               mat,premat;


387:   if (x && x == b) {
388:     if (!ksp->guess_zero) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_INCOMP,"Cannot use x == b with nonzero initial guess");
389:     VecDuplicate(b,&x);
390:     inXisinB = PETSC_TRUE;
391:   }
392:   if (b) {
393:     PetscObjectReference((PetscObject)b);
394:     VecDestroy(&ksp->vec_rhs);
395:     ksp->vec_rhs = b;
396:   }
397:   if (x) {
398:     PetscObjectReference((PetscObject)x);
399:     VecDestroy(&ksp->vec_sol);
400:     ksp->vec_sol = x;
401:   }
402:   KSPViewFromOptions(ksp,NULL,"-ksp_view_pre");

404:   if (ksp->presolve) {
405:     (*ksp->presolve)(ksp,ksp->vec_rhs,ksp->vec_sol,ksp->prectx);
406:   }
407:   PetscLogEventBegin(KSP_Solve,ksp,ksp->vec_rhs,ksp->vec_sol,0);

409:   /* reset the residual history list if requested */
410:   if (ksp->res_hist_reset) ksp->res_hist_len = 0;
411:   ksp->transpose_solve = PETSC_FALSE;

413:   if (ksp->guess) {
414:     KSPFischerGuessFormGuess(ksp->guess,ksp->vec_rhs,ksp->vec_sol);
415:     ksp->guess_zero = PETSC_FALSE;
416:   }
417:   /* KSPSetUp() scales the matrix if needed */
418:   KSPSetUp(ksp);
419:   KSPSetUpOnBlocks(ksp);

421:   /* diagonal scale RHS if called for */
422:   if (ksp->dscale) {
423:     VecPointwiseMult(ksp->vec_rhs,ksp->vec_rhs,ksp->diagonal);
424:     /* second time in, but matrix was scaled back to original */
425:     if (ksp->dscalefix && ksp->dscalefix2) {
426:       Mat mat,pmat;

428:       PCGetOperators(ksp->pc,&mat,&pmat);
429:       MatDiagonalScale(pmat,ksp->diagonal,ksp->diagonal);
430:       if (mat != pmat) {MatDiagonalScale(mat,ksp->diagonal,ksp->diagonal);}
431:     }

433:     /*  scale initial guess */
434:     if (!ksp->guess_zero) {
435:       if (!ksp->truediagonal) {
436:         VecDuplicate(ksp->diagonal,&ksp->truediagonal);
437:         VecCopy(ksp->diagonal,ksp->truediagonal);
438:         VecReciprocal(ksp->truediagonal);
439:       }
440:       VecPointwiseMult(ksp->vec_sol,ksp->vec_sol,ksp->truediagonal);
441:     }
442:   }
443:   PCPreSolve(ksp->pc,ksp);

445:   if (ksp->guess_zero) { VecSet(ksp->vec_sol,0.0);}
446:   if (ksp->guess_knoll) {
447:     PCApply(ksp->pc,ksp->vec_rhs,ksp->vec_sol);
448:     KSP_RemoveNullSpace(ksp,ksp->vec_sol);
449:     ksp->guess_zero = PETSC_FALSE;
450:   }

452:   /* can we mark the initial guess as zero for this solve? */
453:   guess_zero = ksp->guess_zero;
454:   if (!ksp->guess_zero) {
455:     PetscReal norm;

457:     VecNormAvailable(ksp->vec_sol,NORM_2,&flg,&norm);
458:     if (flg && !norm) ksp->guess_zero = PETSC_TRUE;
459:   }
460:   (*ksp->ops->solve)(ksp);
461:   ksp->guess_zero = guess_zero;

463:   if (!ksp->reason) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_PLIB,"Internal error, solver returned without setting converged reason");
464:   if (ksp->printreason) {
465:     PetscViewerASCIIAddTab(PETSC_VIEWER_STDOUT_(PetscObjectComm((PetscObject)ksp)),((PetscObject)ksp)->tablevel);
466:     if (ksp->reason > 0) {
467:       PetscViewerASCIIPrintf(PETSC_VIEWER_STDOUT_(PetscObjectComm((PetscObject)ksp)),"Linear solve converged due to %s iterations %D\n",KSPConvergedReasons[ksp->reason],ksp->its);
468:     } else {
469:       PetscViewerASCIIPrintf(PETSC_VIEWER_STDOUT_(PetscObjectComm((PetscObject)ksp)),"Linear solve did not converge due to %s iterations %D\n",KSPConvergedReasons[ksp->reason],ksp->its);
470:     }
471:     PetscViewerASCIISubtractTab(PETSC_VIEWER_STDOUT_(PetscObjectComm((PetscObject)ksp)),((PetscObject)ksp)->tablevel);
472:   }
473:   PCPostSolve(ksp->pc,ksp);

475:   /* diagonal scale solution if called for */
476:   if (ksp->dscale) {
477:     VecPointwiseMult(ksp->vec_sol,ksp->vec_sol,ksp->diagonal);
478:     /* unscale right hand side and matrix */
479:     if (ksp->dscalefix) {
480:       Mat mat,pmat;

482:       VecReciprocal(ksp->diagonal);
483:       VecPointwiseMult(ksp->vec_rhs,ksp->vec_rhs,ksp->diagonal);
484:       PCGetOperators(ksp->pc,&mat,&pmat);
485:       MatDiagonalScale(pmat,ksp->diagonal,ksp->diagonal);
486:       if (mat != pmat) {MatDiagonalScale(mat,ksp->diagonal,ksp->diagonal);}
487:       VecReciprocal(ksp->diagonal);
488:       ksp->dscalefix2 = PETSC_TRUE;
489:     }
490:   }
491:   PetscLogEventEnd(KSP_Solve,ksp,ksp->vec_rhs,ksp->vec_sol,0);
492:   if (ksp->postsolve) {
493:     (*ksp->postsolve)(ksp,ksp->vec_rhs,ksp->vec_sol,ksp->postctx);
494:   }

496:   if (ksp->guess) {
497:     KSPFischerGuessUpdate(ksp->guess,ksp->vec_sol);
498:   }

500:   MPI_Comm_rank(PetscObjectComm((PetscObject)ksp),&rank);

502:   PCGetOperators(ksp->pc,&mat,&premat);
503:   MatViewFromOptions(mat,((PetscObject)ksp)->prefix,"-ksp_view_mat");
504:   MatViewFromOptions(premat,((PetscObject)ksp)->prefix,"-ksp_view_pmat");
505:   VecViewFromOptions(ksp->vec_rhs,((PetscObject)ksp)->prefix,"-ksp_view_rhs");

507:   flag1 = PETSC_FALSE;
508:   flag2 = PETSC_FALSE;
509:   flag3 = PETSC_FALSE;
510:   PetscOptionsGetBool(((PetscObject)ksp)->prefix,"-ksp_compute_eigenvalues",&flag1,NULL);
511:   PetscOptionsGetBool(((PetscObject)ksp)->prefix,"-ksp_plot_eigenvalues",&flag2,NULL);
512:   PetscOptionsGetBool(((PetscObject)ksp)->prefix,"-ksp_plot_eigencontours",&flag3,NULL);
513:   if (flag1 || flag2 || flag3) {
514:     PetscInt  nits,n,i,neig;
515:     PetscReal *r,*c;

517:     KSPGetIterationNumber(ksp,&nits);
518:     n    = nits+2;

520:     if (!nits) {
521:       PetscPrintf(PetscObjectComm((PetscObject)ksp),"Zero iterations in solver, cannot approximate any eigenvalues\n");
522:     } else {
523:       PetscMalloc2(n,&r,n,&c);
524:       KSPComputeEigenvalues(ksp,n,r,c,&neig);
525:       if (flag1) {
526:         PetscPrintf(PetscObjectComm((PetscObject)ksp),"Iteratively computed eigenvalues\n");
527:         for (i=0; i<neig; i++) {
528:           if (c[i] >= 0.0) {
529:             PetscPrintf(PetscObjectComm((PetscObject)ksp),"%g + %gi\n",(double)r[i],(double)c[i]);
530:           } else {
531:             PetscPrintf(PetscObjectComm((PetscObject)ksp),"%g - %gi\n",(double)r[i],-(double)c[i]);
532:           }
533:         }
534:       }
535:       if (flag2 && !rank) {
536:         PetscDraw   draw;
537:         PetscDrawSP drawsp;

539:         if (!ksp->eigviewer) {
540:           PetscViewerDrawOpen(PETSC_COMM_SELF,0,"Iteratively Computed Eigenvalues",PETSC_DECIDE,PETSC_DECIDE,400,400,&ksp->eigviewer);
541:         }
542:         PetscViewerDrawGetDraw(ksp->eigviewer,0,&draw);
543:         PetscDrawSPCreate(draw,1,&drawsp);
544:         PetscDrawSPReset(drawsp);
545:         for (i=0; i<neig; i++) {
546:           PetscDrawSPAddPoint(drawsp,r+i,c+i);
547:         }
548:         PetscDrawSPDraw(drawsp,PETSC_TRUE);
549:         PetscDrawSPDestroy(&drawsp);
550:       }
551:       if (flag3 && !rank) {
552:         KSPPlotEigenContours_Private(ksp,neig,r,c);
553:       }
554:       PetscFree2(r,c);
555:     }
556:   }

558:   flag1 = PETSC_FALSE;
559:   PetscOptionsGetBool(((PetscObject)ksp)->prefix,"-ksp_compute_singularvalues",&flag1,NULL);
560:   if (flag1) {
561:     PetscInt nits;

563:     KSPGetIterationNumber(ksp,&nits);
564:     if (!nits) {
565:       PetscPrintf(PetscObjectComm((PetscObject)ksp),"Zero iterations in solver, cannot approximate any singular values\n");
566:     } else {
567:       PetscReal emax,emin;

569:       KSPComputeExtremeSingularValues(ksp,&emax,&emin);
570:       PetscPrintf(PetscObjectComm((PetscObject)ksp),"Iteratively computed extreme singular values: max %g min %g max/min %g\n",(double)emax,(double)emin,(double)(emax/emin));
571:     }
572:   }


575:   flag1 = PETSC_FALSE;
576:   flag2 = PETSC_FALSE;
577:   PetscOptionsGetBool(((PetscObject)ksp)->prefix,"-ksp_compute_eigenvalues_explicitly",&flag1,NULL);
578:   PetscOptionsGetBool(((PetscObject)ksp)->prefix,"-ksp_plot_eigenvalues_explicitly",&flag2,NULL);
579:   if (flag1 || flag2) {
580:     PetscInt  n,i;
581:     PetscReal *r,*c;
582:     VecGetSize(ksp->vec_sol,&n);
583:     PetscMalloc2(n,&r,n,&c);
584:     KSPComputeEigenvaluesExplicitly(ksp,n,r,c);
585:     if (flag1) {
586:       PetscPrintf(PetscObjectComm((PetscObject)ksp),"Explicitly computed eigenvalues\n");
587:       for (i=0; i<n; i++) {
588:         if (c[i] >= 0.0) {
589:           PetscPrintf(PetscObjectComm((PetscObject)ksp),"%g + %gi\n",(double)r[i],(double)c[i]);
590:         } else {
591:           PetscPrintf(PetscObjectComm((PetscObject)ksp),"%g - %gi\n",(double)r[i],-(double)c[i]);
592:         }
593:       }
594:     }
595:     if (flag2 && !rank) {
596:       PetscDraw   draw;
597:       PetscDrawSP drawsp;

599:       if (!ksp->eigviewer) {
600:         PetscViewerDrawOpen(PETSC_COMM_SELF,0,"Explicitly Computed Eigenvalues",0,320,400,400,&ksp->eigviewer);
601:       }
602:       PetscViewerDrawGetDraw(ksp->eigviewer,0,&draw);
603:       PetscDrawSPCreate(draw,1,&drawsp);
604:       PetscDrawSPReset(drawsp);
605:       for (i=0; i<n; i++) {
606:         PetscDrawSPAddPoint(drawsp,r+i,c+i);
607:       }
608:       PetscDrawSPDraw(drawsp,PETSC_TRUE);
609:       PetscDrawSPDestroy(&drawsp);
610:     }
611:     PetscFree2(r,c);
612:   }

614:   PetscOptionsHasName(((PetscObject)ksp)->prefix,"-ksp_view_mat_explicit",&flag2);
615:   if (flag2) {
616:     Mat A,B;
617:     PCGetOperators(ksp->pc,&A,NULL);
618:     MatComputeExplicitOperator(A,&B);
619:     MatViewFromOptions(B,((PetscObject)ksp)->prefix,"-ksp_view_mat_explicit");
620:     MatDestroy(&B);
621:   }
622:   PetscOptionsHasName(((PetscObject)ksp)->prefix,"-ksp_view_preconditioned_operator_explicit",&flag2);
623:   if (flag2) {
624:     Mat B;
625:     KSPComputeExplicitOperator(ksp,&B);
626:     MatViewFromOptions(B,((PetscObject)ksp)->prefix,"-ksp_view_preconditioned_operator_explicit");
627:     MatDestroy(&B);
628:   }
629:   KSPViewFromOptions(ksp,NULL,"-ksp_view");

631:   flg  = PETSC_FALSE;
632:   PetscOptionsGetBool(((PetscObject)ksp)->prefix,"-ksp_final_residual",&flg,NULL);
633:   if (flg) {
634:     Mat       A;
635:     Vec       t;
636:     PetscReal norm;
637:     if (ksp->dscale && !ksp->dscalefix) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_WRONGSTATE,"Cannot compute final scale with -ksp_diagonal_scale except also with -ksp_diagonal_scale_fix");
638:     PCGetOperators(ksp->pc,&A,NULL);
639:     VecDuplicate(ksp->vec_rhs,&t);
640:     KSP_MatMult(ksp,A,ksp->vec_sol,t);
641:     VecAYPX(t, -1.0, ksp->vec_rhs);
642:     VecNorm(t,NORM_2,&norm);
643:     VecDestroy(&t);
644:     PetscPrintf(PetscObjectComm((PetscObject)ksp),"KSP final norm of residual %g\n",(double)norm);
645:   }
646:   VecViewFromOptions(ksp->vec_sol,((PetscObject)ksp)->prefix,"-ksp_view_solution");

648:   if (inXisinB) {
649:     VecCopy(x,b);
650:     VecDestroy(&x);
651:   }
652:   PetscObjectSAWsBlock((PetscObject)ksp);
653:   if (ksp->errorifnotconverged && ksp->reason < 0) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_NOT_CONVERGED,"KSPSolve has not converged");
654:   return(0);
655: }

659: /*@
660:    KSPSolveTranspose - Solves the transpose of a linear system.

662:    Collective on KSP

664:    Input Parameter:
665: +  ksp - iterative context obtained from KSPCreate()
666: .  b - right hand side vector
667: -  x - solution vector

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

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

673:    Level: developer

675: .keywords: KSP, solve, linear system

677: .seealso: KSPCreate(), KSPSetUp(), KSPDestroy(), KSPSetTolerances(), KSPConvergedDefault(),
678:           KSPSolve()
679: @*/

681: PetscErrorCode  KSPSolveTranspose(KSP ksp,Vec b,Vec x)
682: {
684:   PetscBool      inXisinB=PETSC_FALSE;

690:   if (x == b) {
691:     VecDuplicate(b,&x);
692:     inXisinB = PETSC_TRUE;
693:   }
694:   PetscObjectReference((PetscObject)b);
695:   PetscObjectReference((PetscObject)x);
696:   VecDestroy(&ksp->vec_rhs);
697:   VecDestroy(&ksp->vec_sol);

699:   ksp->vec_rhs         = b;
700:   ksp->vec_sol         = x;
701:   ksp->transpose_solve = PETSC_TRUE;

703:   KSPSetUp(ksp);
704:   if (ksp->guess_zero) { VecSet(ksp->vec_sol,0.0);}
705:   (*ksp->ops->solve)(ksp);
706:   if (!ksp->reason) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_PLIB,"Internal error, solver returned without setting converged reason");
707:   if (ksp->printreason) {
708:     if (ksp->reason > 0) {
709:       PetscPrintf(PetscObjectComm((PetscObject)ksp),"Linear solve converged due to %s iterations %D\n",KSPConvergedReasons[ksp->reason],ksp->its);
710:     } else {
711:       PetscPrintf(PetscObjectComm((PetscObject)ksp),"Linear solve did not converge due to %s iterations %D\n",KSPConvergedReasons[ksp->reason],ksp->its);
712:     }
713:   }
714:   if (inXisinB) {
715:     VecCopy(x,b);
716:     VecDestroy(&x);
717:   }
718:   if (ksp->errorifnotconverged && ksp->reason < 0) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_NOT_CONVERGED,"KSPSolve has not converged");
719:   return(0);
720: }

724: /*@
725:    KSPReset - Resets a KSP context to the kspsetupcalled = 0 state and removes any allocated Vecs and Mats

727:    Collective on KSP

729:    Input Parameter:
730: .  ksp - iterative context obtained from KSPCreate()

732:    Level: beginner

734: .keywords: KSP, destroy

736: .seealso: KSPCreate(), KSPSetUp(), KSPSolve()
737: @*/
738: PetscErrorCode  KSPReset(KSP ksp)
739: {

744:   if (!ksp) return(0);
745:   if (ksp->ops->reset) {
746:     (*ksp->ops->reset)(ksp);
747:   }
748:   if (ksp->pc) {PCReset(ksp->pc);}
749:   KSPFischerGuessDestroy(&ksp->guess);
750:   VecDestroyVecs(ksp->nwork,&ksp->work);
751:   VecDestroy(&ksp->vec_rhs);
752:   VecDestroy(&ksp->vec_sol);
753:   VecDestroy(&ksp->diagonal);
754:   VecDestroy(&ksp->truediagonal);
755:   MatNullSpaceDestroy(&ksp->nullsp);

757:   ksp->setupstage = KSP_SETUP_NEW;
758:   return(0);
759: }

763: /*@
764:    KSPDestroy - Destroys KSP context.

766:    Collective on KSP

768:    Input Parameter:
769: .  ksp - iterative context obtained from KSPCreate()

771:    Level: beginner

773: .keywords: KSP, destroy

775: .seealso: KSPCreate(), KSPSetUp(), KSPSolve()
776: @*/
777: PetscErrorCode  KSPDestroy(KSP *ksp)
778: {
780:   PC             pc;

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

787:   PetscObjectSAWsViewOff((PetscObject)*ksp);
788:   /*
789:    Avoid a cascading call to PCReset(ksp->pc) from the following call:
790:    PCReset() shouldn't be called from KSPDestroy() as it is unprotected by pc's
791:    refcount (and may be shared, e.g., by other ksps).
792:    */
793:   pc         = (*ksp)->pc;
794:   (*ksp)->pc = NULL;
795:   KSPReset((*ksp));
796:   (*ksp)->pc = pc;
797:     if ((*ksp)->ops->destroy) {(*(*ksp)->ops->destroy)(*ksp);}

799:   DMDestroy(&(*ksp)->dm);
800:   PCDestroy(&(*ksp)->pc);
801:   PetscFree((*ksp)->res_hist_alloc);
802:   if ((*ksp)->convergeddestroy) {
803:     (*(*ksp)->convergeddestroy)((*ksp)->cnvP);
804:   }
805:   KSPMonitorCancel((*ksp));
806:   PetscViewerDestroy(&(*ksp)->eigviewer);
807:   PetscHeaderDestroy(ksp);
808:   return(0);
809: }

813: /*@
814:     KSPSetPCSide - Sets the preconditioning side.

816:     Logically Collective on KSP

818:     Input Parameter:
819: .   ksp - iterative context obtained from KSPCreate()

821:     Output Parameter:
822: .   side - the preconditioning side, where side is one of
823: .vb
824:       PC_LEFT - left preconditioning (default)
825:       PC_RIGHT - right preconditioning
826:       PC_SYMMETRIC - symmetric preconditioning
827: .ve

829:     Options Database Keys:
830: .   -ksp_pc_side <right,left,symmetric>

832:     Notes:
833:     Left preconditioning is used by default for most Krylov methods except KSPFGMRES which only supports right preconditioning.
834:     Symmetric preconditioning is currently available only for the KSPQCG method. Note, however, that
835:     symmetric preconditioning can be emulated by using either right or left
836:     preconditioning and a pre or post processing step.

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

840:     Level: intermediate

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

844: .seealso: KSPGetPCSide(), KSPSetNormType()
845: @*/
846: PetscErrorCode  KSPSetPCSide(KSP ksp,PCSide side)
847: {
851:   ksp->pc_side = ksp->pc_side_set = side;
852:   return(0);
853: }

857: /*@
858:     KSPGetPCSide - Gets the preconditioning side.

860:     Not Collective

862:     Input Parameter:
863: .   ksp - iterative context obtained from KSPCreate()

865:     Output Parameter:
866: .   side - the preconditioning side, where side is one of
867: .vb
868:       PC_LEFT - left preconditioning (default)
869:       PC_RIGHT - right preconditioning
870:       PC_SYMMETRIC - symmetric preconditioning
871: .ve

873:     Level: intermediate

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

877: .seealso: KSPSetPCSide()
878: @*/
879: PetscErrorCode  KSPGetPCSide(KSP ksp,PCSide *side)
880: {

886:   KSPSetUpNorms_Private(ksp,&ksp->normtype,&ksp->pc_side);
887:   *side = ksp->pc_side;
888:   return(0);
889: }

893: /*@
894:    KSPGetTolerances - Gets the relative, absolute, divergence, and maximum
895:    iteration tolerances used by the default KSP convergence tests.

897:    Not Collective

899:    Input Parameter:
900: .  ksp - the Krylov subspace context

902:    Output Parameters:
903: +  rtol - the relative convergence tolerance
904: .  abstol - the absolute convergence tolerance
905: .  dtol - the divergence tolerance
906: -  maxits - maximum number of iterations

908:    Notes:
909:    The user can specify NULL for any parameter that is not needed.

911:    Level: intermediate

913: .keywords: KSP, get, tolerance, absolute, relative, divergence, convergence,
914:            maximum, iterations

916: .seealso: KSPSetTolerances()
917: @*/
918: PetscErrorCode  KSPGetTolerances(KSP ksp,PetscReal *rtol,PetscReal *abstol,PetscReal *dtol,PetscInt *maxits)
919: {
922:   if (abstol) *abstol = ksp->abstol;
923:   if (rtol) *rtol = ksp->rtol;
924:   if (dtol) *dtol = ksp->divtol;
925:   if (maxits) *maxits = ksp->max_it;
926:   return(0);
927: }

931: /*@
932:    KSPSetTolerances - Sets the relative, absolute, divergence, and maximum
933:    iteration tolerances used by the default KSP convergence testers.

935:    Logically Collective on KSP

937:    Input Parameters:
938: +  ksp - the Krylov subspace context
939: .  rtol - the relative convergence tolerance, relative decrease in the (possibly preconditioned) residual norm
940: .  abstol - the absolute convergence tolerance   absolute size of the (possibly preconditioned) residual norm
941: .  dtol - the divergence tolerance,   amount (possibly preconditioned) residual norm can increase before KSPConvergedDefault() concludes that the method is diverging
942: -  maxits - maximum number of iterations to use

944:    Options Database Keys:
945: +  -ksp_atol <abstol> - Sets abstol
946: .  -ksp_rtol <rtol> - Sets rtol
947: .  -ksp_divtol <dtol> - Sets dtol
948: -  -ksp_max_it <maxits> - Sets maxits

950:    Notes:
951:    Use PETSC_DEFAULT to retain the default value of any of the tolerances.

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

956:    Level: intermediate

958: .keywords: KSP, set, tolerance, absolute, relative, divergence,
959:            convergence, maximum, iterations

961: .seealso: KSPGetTolerances(), KSPConvergedDefault(), KSPSetConvergenceTest()
962: @*/
963: PetscErrorCode  KSPSetTolerances(KSP ksp,PetscReal rtol,PetscReal abstol,PetscReal dtol,PetscInt maxits)
964: {

972:   if (rtol != PETSC_DEFAULT) {
973:     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);
974:     ksp->rtol = rtol;
975:   }
976:   if (abstol != PETSC_DEFAULT) {
977:     if (abstol < 0.0) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Absolute tolerance %g must be non-negative",(double)abstol);
978:     ksp->abstol = abstol;
979:   }
980:   if (dtol != PETSC_DEFAULT) {
981:     if (dtol < 0.0) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Divergence tolerance %g must be larger than 1.0",(double)dtol);
982:     ksp->divtol = dtol;
983:   }
984:   if (maxits != PETSC_DEFAULT) {
985:     if (maxits < 0) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Maximum number of iterations %D must be non-negative",maxits);
986:     ksp->max_it = maxits;
987:   }
988:   return(0);
989: }

993: /*@
994:    KSPSetInitialGuessNonzero - Tells the iterative solver that the
995:    initial guess is nonzero; otherwise KSP assumes the initial guess
996:    is to be zero (and thus zeros it out before solving).

998:    Logically Collective on KSP

1000:    Input Parameters:
1001: +  ksp - iterative context obtained from KSPCreate()
1002: -  flg - PETSC_TRUE indicates the guess is non-zero, PETSC_FALSE indicates the guess is zero

1004:    Options database keys:
1005: .  -ksp_initial_guess_nonzero : use nonzero initial guess; this takes an optional truth value (0/1/no/yes/true/false)

1007:    Level: beginner

1009:    Notes:
1010:     If this is not called the X vector is zeroed in the call to KSPSolve().

1012: .keywords: KSP, set, initial guess, nonzero

1014: .seealso: KSPGetInitialGuessNonzero(), KSPSetInitialGuessKnoll(), KSPGetInitialGuessKnoll()
1015: @*/
1016: PetscErrorCode  KSPSetInitialGuessNonzero(KSP ksp,PetscBool flg)
1017: {
1021:   ksp->guess_zero = (PetscBool) !(int)flg;
1022:   return(0);
1023: }

1027: /*@
1028:    KSPGetInitialGuessNonzero - Determines whether the KSP solver is using
1029:    a zero initial guess.

1031:    Not Collective

1033:    Input Parameter:
1034: .  ksp - iterative context obtained from KSPCreate()

1036:    Output Parameter:
1037: .  flag - PETSC_TRUE if guess is nonzero, else PETSC_FALSE

1039:    Level: intermediate

1041: .keywords: KSP, set, initial guess, nonzero

1043: .seealso: KSPSetInitialGuessNonzero(), KSPSetInitialGuessKnoll(), KSPGetInitialGuessKnoll()
1044: @*/
1045: PetscErrorCode  KSPGetInitialGuessNonzero(KSP ksp,PetscBool  *flag)
1046: {
1050:   if (ksp->guess_zero) *flag = PETSC_FALSE;
1051:   else *flag = PETSC_TRUE;
1052:   return(0);
1053: }

1057: /*@
1058:    KSPSetErrorIfNotConverged - Causes KSPSolve() to generate an error if the solver has not converged.

1060:    Logically Collective on KSP

1062:    Input Parameters:
1063: +  ksp - iterative context obtained from KSPCreate()
1064: -  flg - PETSC_TRUE indicates you want the error generated

1066:    Options database keys:
1067: .  -ksp_error_if_not_converged : this takes an optional truth value (0/1/no/yes/true/false)

1069:    Level: intermediate

1071:    Notes:
1072:     Normally PETSc continues if a linear solver fails to converge, you can call KSPGetConvergedReason() after a KSPSolve()
1073:     to determine if it has converged.

1075: .keywords: KSP, set, initial guess, nonzero

1077: .seealso: KSPGetInitialGuessNonzero(), KSPSetInitialGuessKnoll(), KSPGetInitialGuessKnoll(), KSPGetErrorIfNotConverged()
1078: @*/
1079: PetscErrorCode  KSPSetErrorIfNotConverged(KSP ksp,PetscBool flg)
1080: {
1084:   ksp->errorifnotconverged = flg;
1085:   return(0);
1086: }

1090: /*@
1091:    KSPGetErrorIfNotConverged - Will KSPSolve() generate an error if the solver does not converge?

1093:    Not Collective

1095:    Input Parameter:
1096: .  ksp - iterative context obtained from KSPCreate()

1098:    Output Parameter:
1099: .  flag - PETSC_TRUE if it will generate an error, else PETSC_FALSE

1101:    Level: intermediate

1103: .keywords: KSP, set, initial guess, nonzero

1105: .seealso: KSPSetInitialGuessNonzero(), KSPSetInitialGuessKnoll(), KSPGetInitialGuessKnoll(), KSPSetErrorIfNotConverged()
1106: @*/
1107: PetscErrorCode  KSPGetErrorIfNotConverged(KSP ksp,PetscBool  *flag)
1108: {
1112:   *flag = ksp->errorifnotconverged;
1113:   return(0);
1114: }

1118: /*@
1119:    KSPSetInitialGuessKnoll - Tells the iterative solver to use PCApply(pc,b,..) to compute the initial guess (The Knoll trick)

1121:    Logically Collective on KSP

1123:    Input Parameters:
1124: +  ksp - iterative context obtained from KSPCreate()
1125: -  flg - PETSC_TRUE or PETSC_FALSE

1127:    Level: advanced


1130: .keywords: KSP, set, initial guess, nonzero

1132: .seealso: KSPGetInitialGuessKnoll(), KSPSetInitialGuessNonzero(), KSPGetInitialGuessNonzero()
1133: @*/
1134: PetscErrorCode  KSPSetInitialGuessKnoll(KSP ksp,PetscBool flg)
1135: {
1139:   ksp->guess_knoll = flg;
1140:   return(0);
1141: }

1145: /*@
1146:    KSPGetInitialGuessKnoll - Determines whether the KSP solver is using the Knoll trick (using PCApply(pc,b,...) to compute
1147:      the initial guess

1149:    Not Collective

1151:    Input Parameter:
1152: .  ksp - iterative context obtained from KSPCreate()

1154:    Output Parameter:
1155: .  flag - PETSC_TRUE if using Knoll trick, else PETSC_FALSE

1157:    Level: advanced

1159: .keywords: KSP, set, initial guess, nonzero

1161: .seealso: KSPSetInitialGuessKnoll(), KSPSetInitialGuessNonzero(), KSPGetInitialGuessNonzero()
1162: @*/
1163: PetscErrorCode  KSPGetInitialGuessKnoll(KSP ksp,PetscBool  *flag)
1164: {
1168:   *flag = ksp->guess_knoll;
1169:   return(0);
1170: }

1174: /*@
1175:    KSPGetComputeSingularValues - Gets the flag indicating whether the extreme singular
1176:    values will be calculated via a Lanczos or Arnoldi process as the linear
1177:    system is solved.

1179:    Not Collective

1181:    Input Parameter:
1182: .  ksp - iterative context obtained from KSPCreate()

1184:    Output Parameter:
1185: .  flg - PETSC_TRUE or PETSC_FALSE

1187:    Options Database Key:
1188: .  -ksp_monitor_singular_value - Activates KSPSetComputeSingularValues()

1190:    Notes:
1191:    Currently this option is not valid for all iterative methods.

1193:    Many users may just want to use the monitoring routine
1194:    KSPMonitorSingularValue() (which can be set with option -ksp_monitor_singular_value)
1195:    to print the singular values at each iteration of the linear solve.

1197:    Level: advanced

1199: .keywords: KSP, set, compute, singular values

1201: .seealso: KSPComputeExtremeSingularValues(), KSPMonitorSingularValue()
1202: @*/
1203: PetscErrorCode  KSPGetComputeSingularValues(KSP ksp,PetscBool  *flg)
1204: {
1208:   *flg = ksp->calc_sings;
1209:   return(0);
1210: }

1214: /*@
1215:    KSPSetComputeSingularValues - Sets a flag so that the extreme singular
1216:    values will be calculated via a Lanczos or Arnoldi process as the linear
1217:    system is solved.

1219:    Logically Collective on KSP

1221:    Input Parameters:
1222: +  ksp - iterative context obtained from KSPCreate()
1223: -  flg - PETSC_TRUE or PETSC_FALSE

1225:    Options Database Key:
1226: .  -ksp_monitor_singular_value - Activates KSPSetComputeSingularValues()

1228:    Notes:
1229:    Currently this option is not valid for all iterative methods.

1231:    Many users may just want to use the monitoring routine
1232:    KSPMonitorSingularValue() (which can be set with option -ksp_monitor_singular_value)
1233:    to print the singular values at each iteration of the linear solve.

1235:    Level: advanced

1237: .keywords: KSP, set, compute, singular values

1239: .seealso: KSPComputeExtremeSingularValues(), KSPMonitorSingularValue()
1240: @*/
1241: PetscErrorCode  KSPSetComputeSingularValues(KSP ksp,PetscBool flg)
1242: {
1246:   ksp->calc_sings = flg;
1247:   return(0);
1248: }

1252: /*@
1253:    KSPGetComputeEigenvalues - Gets the flag indicating that the extreme eigenvalues
1254:    values will be calculated via a Lanczos or Arnoldi process as the linear
1255:    system is solved.

1257:    Not Collective

1259:    Input Parameter:
1260: .  ksp - iterative context obtained from KSPCreate()

1262:    Output Parameter:
1263: .  flg - PETSC_TRUE or PETSC_FALSE

1265:    Notes:
1266:    Currently this option is not valid for all iterative methods.

1268:    Level: advanced

1270: .keywords: KSP, set, compute, eigenvalues

1272: .seealso: KSPComputeEigenvalues(), KSPComputeEigenvaluesExplicitly()
1273: @*/
1274: PetscErrorCode  KSPGetComputeEigenvalues(KSP ksp,PetscBool  *flg)
1275: {
1279:   *flg = ksp->calc_sings;
1280:   return(0);
1281: }

1285: /*@
1286:    KSPSetComputeEigenvalues - Sets a flag so that the extreme eigenvalues
1287:    values will be calculated via a Lanczos or Arnoldi process as the linear
1288:    system is solved.

1290:    Logically Collective on KSP

1292:    Input Parameters:
1293: +  ksp - iterative context obtained from KSPCreate()
1294: -  flg - PETSC_TRUE or PETSC_FALSE

1296:    Notes:
1297:    Currently this option is not valid for all iterative methods.

1299:    Level: advanced

1301: .keywords: KSP, set, compute, eigenvalues

1303: .seealso: KSPComputeEigenvalues(), KSPComputeEigenvaluesExplicitly()
1304: @*/
1305: PetscErrorCode  KSPSetComputeEigenvalues(KSP ksp,PetscBool flg)
1306: {
1310:   ksp->calc_sings = flg;
1311:   return(0);
1312: }

1316: /*@
1317:    KSPGetRhs - Gets the right-hand-side vector for the linear system to
1318:    be solved.

1320:    Not Collective

1322:    Input Parameter:
1323: .  ksp - iterative context obtained from KSPCreate()

1325:    Output Parameter:
1326: .  r - right-hand-side vector

1328:    Level: developer

1330: .keywords: KSP, get, right-hand-side, rhs

1332: .seealso: KSPGetSolution(), KSPSolve()
1333: @*/
1334: PetscErrorCode  KSPGetRhs(KSP ksp,Vec *r)
1335: {
1339:   *r = ksp->vec_rhs;
1340:   return(0);
1341: }

1345: /*@
1346:    KSPGetSolution - Gets the location of the solution for the
1347:    linear system to be solved.  Note that this may not be where the solution
1348:    is stored during the iterative process; see KSPBuildSolution().

1350:    Not Collective

1352:    Input Parameters:
1353: .  ksp - iterative context obtained from KSPCreate()

1355:    Output Parameters:
1356: .  v - solution vector

1358:    Level: developer

1360: .keywords: KSP, get, solution

1362: .seealso: KSPGetRhs(),  KSPBuildSolution(), KSPSolve()
1363: @*/
1364: PetscErrorCode  KSPGetSolution(KSP ksp,Vec *v)
1365: {
1369:   *v = ksp->vec_sol;
1370:   return(0);
1371: }

1375: /*@
1376:    KSPSetPC - Sets the preconditioner to be used to calculate the
1377:    application of the preconditioner on a vector.

1379:    Collective on KSP

1381:    Input Parameters:
1382: +  ksp - iterative context obtained from KSPCreate()
1383: -  pc   - the preconditioner object

1385:    Notes:
1386:    Use KSPGetPC() to retrieve the preconditioner context (for example,
1387:    to free it at the end of the computations).

1389:    Level: developer

1391: .keywords: KSP, set, precondition, Binv

1393: .seealso: KSPGetPC()
1394: @*/
1395: PetscErrorCode  KSPSetPC(KSP ksp,PC pc)
1396: {

1403:   PetscObjectReference((PetscObject)pc);
1404:   PCDestroy(&ksp->pc);
1405:   ksp->pc = pc;
1406:   PetscLogObjectParent((PetscObject)ksp,(PetscObject)ksp->pc);
1407:   return(0);
1408: }

1412: /*@
1413:    KSPGetPC - Returns a pointer to the preconditioner context
1414:    set with KSPSetPC().

1416:    Not Collective

1418:    Input Parameters:
1419: .  ksp - iterative context obtained from KSPCreate()

1421:    Output Parameter:
1422: .  pc - preconditioner context

1424:    Level: developer

1426: .keywords: KSP, get, preconditioner, Binv

1428: .seealso: KSPSetPC()
1429: @*/
1430: PetscErrorCode  KSPGetPC(KSP ksp,PC *pc)
1431: {

1437:   if (!ksp->pc) {
1438:     PCCreate(PetscObjectComm((PetscObject)ksp),&ksp->pc);
1439:     PetscObjectIncrementTabLevel((PetscObject)ksp->pc,(PetscObject)ksp,0);
1440:     PetscLogObjectParent((PetscObject)ksp,(PetscObject)ksp->pc);
1441:   }
1442:   *pc = ksp->pc;
1443:   return(0);
1444: }

1448: /*@
1449:    KSPMonitor - runs the user provided monitor routines, if they exist

1451:    Collective on KSP

1453:    Input Parameters:
1454: +  ksp - iterative context obtained from KSPCreate()
1455: .  it - iteration number
1456: -  rnorm - relative norm of the residual

1458:    Notes:
1459:    This routine is called by the KSP implementations.
1460:    It does not typically need to be called by the user.

1462:    Level: developer

1464: .seealso: KSPMonitorSet()
1465: @*/
1466: PetscErrorCode KSPMonitor(KSP ksp,PetscInt it,PetscReal rnorm)
1467: {
1468:   PetscInt       i, n = ksp->numbermonitors;

1472:   for (i=0; i<n; i++) {
1473:     (*ksp->monitor[i])(ksp,it,rnorm,ksp->monitorcontext[i]);
1474:   }
1475:   return(0);
1476: }

1480: /*@C
1481:    KSPMonitorSet - Sets an ADDITIONAL function to be called at every iteration to monitor
1482:    the residual/error etc.

1484:    Logically Collective on KSP

1486:    Input Parameters:
1487: +  ksp - iterative context obtained from KSPCreate()
1488: .  monitor - pointer to function (if this is NULL, it turns off monitoring
1489: .  mctx    - [optional] context for private data for the
1490:              monitor routine (use NULL if no context is desired)
1491: -  monitordestroy - [optional] routine that frees monitor context
1492:           (may be NULL)

1494:    Calling Sequence of monitor:
1495: $     monitor (KSP ksp, int it, PetscReal rnorm, void *mctx)

1497: +  ksp - iterative context obtained from KSPCreate()
1498: .  it - iteration number
1499: .  rnorm - (estimated) 2-norm of (preconditioned) residual
1500: -  mctx  - optional monitoring context, as set by KSPMonitorSet()

1502:    Options Database Keys:
1503: +    -ksp_monitor        - sets KSPMonitorDefault()
1504: .    -ksp_monitor_true_residual    - sets KSPMonitorTrueResidualNorm()
1505: .    -ksp_monitor_max    - sets KSPMonitorTrueResidualMaxNorm()
1506: .    -ksp_monitor_lg_residualnorm    - sets line graph monitor,
1507:                            uses KSPMonitorLGResidualNormCreate()
1508: .    -ksp_monitor_lg_true_residualnorm   - sets line graph monitor,
1509:                            uses KSPMonitorLGResidualNormCreate()
1510: .    -ksp_monitor_singular_value    - sets KSPMonitorSingularValue()
1511: -    -ksp_monitor_cancel - cancels all monitors that have
1512:                           been hardwired into a code by
1513:                           calls to KSPMonitorSet(), but
1514:                           does not cancel those set via
1515:                           the options database.

1517:    Notes:
1518:    The default is to do nothing.  To print the residual, or preconditioned
1519:    residual if KSPSetNormType(ksp,KSP_NORM_PRECONDITIONED) was called, use
1520:    KSPMonitorDefault() as the monitoring routine, with a null monitoring
1521:    context.

1523:    Several different monitoring routines may be set by calling
1524:    KSPMonitorSet() multiple times; all will be called in the
1525:    order in which they were set.

1527:    Fortran notes: Only a single monitor function can be set for each KSP object

1529:    Level: beginner

1531: .keywords: KSP, set, monitor

1533: .seealso: KSPMonitorDefault(), KSPMonitorLGResidualNormCreate(), KSPMonitorCancel()
1534: @*/
1535: PetscErrorCode  KSPMonitorSet(KSP ksp,PetscErrorCode (*monitor)(KSP,PetscInt,PetscReal,void*),void *mctx,PetscErrorCode (*monitordestroy)(void**))
1536: {
1537:   PetscInt       i;

1542:   if (ksp->numbermonitors >= MAXKSPMONITORS) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Too many KSP monitors set");
1543:   for (i=0; i<ksp->numbermonitors;i++) {
1544:     if (monitor == ksp->monitor[i] && monitordestroy == ksp->monitordestroy[i] && mctx == ksp->monitorcontext[i]) {
1545:       if (monitordestroy) {
1546:         (*monitordestroy)(&mctx);
1547:       }
1548:       return(0);
1549:     }
1550:   }
1551:   ksp->monitor[ksp->numbermonitors]          = monitor;
1552:   ksp->monitordestroy[ksp->numbermonitors]   = monitordestroy;
1553:   ksp->monitorcontext[ksp->numbermonitors++] = (void*)mctx;
1554:   return(0);
1555: }

1559: /*@
1560:    KSPMonitorCancel - Clears all monitors for a KSP object.

1562:    Logically Collective on KSP

1564:    Input Parameters:
1565: .  ksp - iterative context obtained from KSPCreate()

1567:    Options Database Key:
1568: .  -ksp_monitor_cancel - Cancels all monitors that have
1569:     been hardwired into a code by calls to KSPMonitorSet(),
1570:     but does not cancel those set via the options database.

1572:    Level: intermediate

1574: .keywords: KSP, set, monitor

1576: .seealso: KSPMonitorDefault(), KSPMonitorLGResidualNormCreate(), KSPMonitorSet()
1577: @*/
1578: PetscErrorCode  KSPMonitorCancel(KSP ksp)
1579: {
1581:   PetscInt       i;

1585:   for (i=0; i<ksp->numbermonitors; i++) {
1586:     if (ksp->monitordestroy[i]) {
1587:       (*ksp->monitordestroy[i])(&ksp->monitorcontext[i]);
1588:     }
1589:   }
1590:   ksp->numbermonitors = 0;
1591:   return(0);
1592: }

1596: /*@C
1597:    KSPGetMonitorContext - Gets the monitoring context, as set by
1598:    KSPMonitorSet() for the FIRST monitor only.

1600:    Not Collective

1602:    Input Parameter:
1603: .  ksp - iterative context obtained from KSPCreate()

1605:    Output Parameter:
1606: .  ctx - monitoring context

1608:    Level: intermediate

1610: .keywords: KSP, get, monitor, context

1612: .seealso: KSPMonitorDefault(), KSPMonitorLGResidualNormCreate()
1613: @*/
1614: PetscErrorCode  KSPGetMonitorContext(KSP ksp,void **ctx)
1615: {
1618:   *ctx =      (ksp->monitorcontext[0]);
1619:   return(0);
1620: }

1624: /*@
1625:    KSPSetResidualHistory - Sets the array used to hold the residual history.
1626:    If set, this array will contain the residual norms computed at each
1627:    iteration of the solver.

1629:    Not Collective

1631:    Input Parameters:
1632: +  ksp - iterative context obtained from KSPCreate()
1633: .  a   - array to hold history
1634: .  na  - size of a
1635: -  reset - PETSC_TRUE indicates the history counter is reset to zero
1636:            for each new linear solve

1638:    Level: advanced

1640:    Notes: The array is NOT freed by PETSc so the user needs to keep track of
1641:            it and destroy once the KSP object is destroyed.

1643:    If 'a' is NULL then space is allocated for the history. If 'na' PETSC_DECIDE or PETSC_DEFAULT then a
1644:    default array of length 10000 is allocated.

1646: .keywords: KSP, set, residual, history, norm

1648: .seealso: KSPGetResidualHistory()

1650: @*/
1651: PetscErrorCode  KSPSetResidualHistory(KSP ksp,PetscReal a[],PetscInt na,PetscBool reset)
1652: {


1658:   PetscFree(ksp->res_hist_alloc);
1659:   if (na != PETSC_DECIDE && na != PETSC_DEFAULT && a) {
1660:     ksp->res_hist     = a;
1661:     ksp->res_hist_max = na;
1662:   } else {
1663:     if (na != PETSC_DECIDE && na != PETSC_DEFAULT) ksp->res_hist_max = na;
1664:     else                                           ksp->res_hist_max = 10000; /* like default ksp->max_it */
1665:     PetscCalloc1(ksp->res_hist_max,&ksp->res_hist_alloc);

1667:     ksp->res_hist = ksp->res_hist_alloc;
1668:   }
1669:   ksp->res_hist_len   = 0;
1670:   ksp->res_hist_reset = reset;
1671:   return(0);
1672: }

1676: /*@C
1677:    KSPGetResidualHistory - Gets the array used to hold the residual history
1678:    and the number of residuals it contains.

1680:    Not Collective

1682:    Input Parameter:
1683: .  ksp - iterative context obtained from KSPCreate()

1685:    Output Parameters:
1686: +  a   - pointer to array to hold history (or NULL)
1687: -  na  - number of used entries in a (or NULL)

1689:    Level: advanced

1691:    Notes:
1692:      Can only be called after a KSPSetResidualHistory() otherwise a and na are set to zero

1694:      The Fortran version of this routine has a calling sequence
1695: $   call KSPGetResidualHistory(KSP ksp, integer na, integer ierr)
1696:     note that you have passed a Fortran array into KSPSetResidualHistory() and you need
1697:     to access the residual values from this Fortran array you provided. Only the na (number of
1698:     residual norms currently held) is set.

1700: .keywords: KSP, get, residual, history, norm

1702: .seealso: KSPGetResidualHistory()

1704: @*/
1705: PetscErrorCode  KSPGetResidualHistory(KSP ksp,PetscReal *a[],PetscInt *na)
1706: {
1709:   if (a) *a = ksp->res_hist;
1710:   if (na) *na = ksp->res_hist_len;
1711:   return(0);
1712: }

1716: /*@C
1717:    KSPSetConvergenceTest - Sets the function to be used to determine
1718:    convergence.

1720:    Logically Collective on KSP

1722:    Input Parameters:
1723: +  ksp - iterative context obtained from KSPCreate()
1724: .  converge - pointer to int function
1725: .  cctx    - context for private data for the convergence routine (may be null)
1726: -  destroy - a routine for destroying the context (may be null)

1728:    Calling sequence of converge:
1729: $     converge (KSP ksp, int it, PetscReal rnorm, KSPConvergedReason *reason,void *mctx)

1731: +  ksp - iterative context obtained from KSPCreate()
1732: .  it - iteration number
1733: .  rnorm - (estimated) 2-norm of (preconditioned) residual
1734: .  reason - the reason why it has converged or diverged
1735: -  cctx  - optional convergence context, as set by KSPSetConvergenceTest()


1738:    Notes:
1739:    Must be called after the KSP type has been set so put this after
1740:    a call to KSPSetType(), or KSPSetFromOptions().

1742:    The default convergence test, KSPConvergedDefault(), aborts if the
1743:    residual grows to more than 10000 times the initial residual.

1745:    The default is a combination of relative and absolute tolerances.
1746:    The residual value that is tested may be an approximation; routines
1747:    that need exact values should compute them.

1749:    In the default PETSc convergence test, the precise values of reason
1750:    are macros such as KSP_CONVERGED_RTOL, which are defined in petscksp.h.

1752:    Level: advanced

1754: .keywords: KSP, set, convergence, test, context

1756: .seealso: KSPConvergedDefault(), KSPGetConvergenceContext(), KSPSetTolerances()
1757: @*/
1758: PetscErrorCode  KSPSetConvergenceTest(KSP ksp,PetscErrorCode (*converge)(KSP,PetscInt,PetscReal,KSPConvergedReason*,void*),void *cctx,PetscErrorCode (*destroy)(void*))
1759: {

1764:   if (ksp->convergeddestroy) {
1765:     (*ksp->convergeddestroy)(ksp->cnvP);
1766:   }
1767:   ksp->converged        = converge;
1768:   ksp->convergeddestroy = destroy;
1769:   ksp->cnvP             = (void*)cctx;
1770:   return(0);
1771: }

1775: /*@C
1776:    KSPGetConvergenceContext - Gets the convergence context set with
1777:    KSPSetConvergenceTest().

1779:    Not Collective

1781:    Input Parameter:
1782: .  ksp - iterative context obtained from KSPCreate()

1784:    Output Parameter:
1785: .  ctx - monitoring context

1787:    Level: advanced

1789: .keywords: KSP, get, convergence, test, context

1791: .seealso: KSPConvergedDefault(), KSPSetConvergenceTest()
1792: @*/
1793: PetscErrorCode  KSPGetConvergenceContext(KSP ksp,void **ctx)
1794: {
1797:   *ctx = ksp->cnvP;
1798:   return(0);
1799: }

1803: /*@C
1804:    KSPBuildSolution - Builds the approximate solution in a vector provided.
1805:    This routine is NOT commonly needed (see KSPSolve()).

1807:    Collective on KSP

1809:    Input Parameter:
1810: .  ctx - iterative context obtained from KSPCreate()

1812:    Output Parameter:
1813:    Provide exactly one of
1814: +  v - location to stash solution.
1815: -  V - the solution is returned in this location. This vector is created
1816:        internally. This vector should NOT be destroyed by the user with
1817:        VecDestroy().

1819:    Notes:
1820:    This routine can be used in one of two ways
1821: .vb
1822:       KSPBuildSolution(ksp,NULL,&V);
1823:    or
1824:       KSPBuildSolution(ksp,v,NULL); or KSPBuildSolution(ksp,v,&v);
1825: .ve
1826:    In the first case an internal vector is allocated to store the solution
1827:    (the user cannot destroy this vector). In the second case the solution
1828:    is generated in the vector that the user provides. Note that for certain
1829:    methods, such as KSPCG, the second case requires a copy of the solution,
1830:    while in the first case the call is essentially free since it simply
1831:    returns the vector where the solution already is stored. For some methods
1832:    like GMRES this is a reasonably expensive operation and should only be
1833:    used in truly needed.

1835:    Level: advanced

1837: .keywords: KSP, build, solution

1839: .seealso: KSPGetSolution(), KSPBuildResidual()
1840: @*/
1841: PetscErrorCode  KSPBuildSolution(KSP ksp,Vec v,Vec *V)
1842: {

1847:   if (!V && !v) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_WRONG,"Must provide either v or V");
1848:   if (!V) V = &v;
1849:   (*ksp->ops->buildsolution)(ksp,v,V);
1850:   return(0);
1851: }

1855: /*@C
1856:    KSPBuildResidual - Builds the residual in a vector provided.

1858:    Collective on KSP

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

1863:    Output Parameters:
1864: +  v - optional location to stash residual.  If v is not provided,
1865:        then a location is generated.
1866: .  t - work vector.  If not provided then one is generated.
1867: -  V - the residual

1869:    Notes:
1870:    Regardless of whether or not v is provided, the residual is
1871:    returned in V.

1873:    Level: advanced

1875: .keywords: KSP, build, residual

1877: .seealso: KSPBuildSolution()
1878: @*/
1879: PetscErrorCode  KSPBuildResidual(KSP ksp,Vec t,Vec v,Vec *V)
1880: {
1882:   PetscBool      flag = PETSC_FALSE;
1883:   Vec            w    = v,tt = t;

1887:   if (!w) {
1888:     VecDuplicate(ksp->vec_rhs,&w);
1889:     PetscLogObjectParent((PetscObject)ksp,(PetscObject)w);
1890:   }
1891:   if (!tt) {
1892:     VecDuplicate(ksp->vec_sol,&tt); flag = PETSC_TRUE;
1893:     PetscLogObjectParent((PetscObject)ksp,(PetscObject)tt);
1894:   }
1895:   (*ksp->ops->buildresidual)(ksp,tt,w,V);
1896:   if (flag) {VecDestroy(&tt);}
1897:   return(0);
1898: }

1902: /*@
1903:    KSPSetDiagonalScale - Tells KSP to symmetrically diagonally scale the system
1904:      before solving. This actually CHANGES the matrix (and right hand side).

1906:    Logically Collective on KSP

1908:    Input Parameter:
1909: +  ksp - the KSP context
1910: -  scale - PETSC_TRUE or PETSC_FALSE

1912:    Options Database Key:
1913: +   -ksp_diagonal_scale -
1914: -   -ksp_diagonal_scale_fix - scale the matrix back AFTER the solve


1917:     Notes: Scales the matrix by  D^(-1/2)  A  D^(-1/2)  [D^(1/2) x ] = D^(-1/2) b
1918:        where D_{ii} is 1/abs(A_{ii}) unless A_{ii} is zero and then it is 1.

1920:     BE CAREFUL with this routine: it actually scales the matrix and right
1921:     hand side that define the system. After the system is solved the matrix
1922:     and right hand side remain scaled unless you use KSPSetDiagonalScaleFix()

1924:     This should NOT be used within the SNES solves if you are using a line
1925:     search.

1927:     If you use this with the PCType Eisenstat preconditioner than you can
1928:     use the PCEisenstatNoDiagonalScaling() option, or -pc_eisenstat_no_diagonal_scaling
1929:     to save some unneeded, redundant flops.

1931:    Level: intermediate

1933: .keywords: KSP, set, options, prefix, database

1935: .seealso: KSPGetDiagonalScale(), KSPSetDiagonalScaleFix()
1936: @*/
1937: PetscErrorCode  KSPSetDiagonalScale(KSP ksp,PetscBool scale)
1938: {
1942:   ksp->dscale = scale;
1943:   return(0);
1944: }

1948: /*@
1949:    KSPGetDiagonalScale - Checks if KSP solver scales the matrix and
1950:                           right hand side

1952:    Not Collective

1954:    Input Parameter:
1955: .  ksp - the KSP context

1957:    Output Parameter:
1958: .  scale - PETSC_TRUE or PETSC_FALSE

1960:    Notes:
1961:     BE CAREFUL with this routine: it actually scales the matrix and right
1962:     hand side that define the system. After the system is solved the matrix
1963:     and right hand side remain scaled  unless you use KSPSetDiagonalScaleFix()

1965:    Level: intermediate

1967: .keywords: KSP, set, options, prefix, database

1969: .seealso: KSPSetDiagonalScale(), KSPSetDiagonalScaleFix()
1970: @*/
1971: PetscErrorCode  KSPGetDiagonalScale(KSP ksp,PetscBool  *scale)
1972: {
1976:   *scale = ksp->dscale;
1977:   return(0);
1978: }

1982: /*@
1983:    KSPSetDiagonalScaleFix - Tells KSP to diagonally scale the system
1984:      back after solving.

1986:    Logically Collective on KSP

1988:    Input Parameter:
1989: +  ksp - the KSP context
1990: -  fix - PETSC_TRUE to scale back after the system solve, PETSC_FALSE to not
1991:          rescale (default)

1993:    Notes:
1994:      Must be called after KSPSetDiagonalScale()

1996:      Using this will slow things down, because it rescales the matrix before and
1997:      after each linear solve. This is intended mainly for testing to allow one
1998:      to easily get back the original system to make sure the solution computed is
1999:      accurate enough.

2001:    Level: intermediate

2003: .keywords: KSP, set, options, prefix, database

2005: .seealso: KSPGetDiagonalScale(), KSPSetDiagonalScale(), KSPGetDiagonalScaleFix()
2006: @*/
2007: PetscErrorCode  KSPSetDiagonalScaleFix(KSP ksp,PetscBool fix)
2008: {
2012:   ksp->dscalefix = fix;
2013:   return(0);
2014: }

2018: /*@
2019:    KSPGetDiagonalScaleFix - Determines if KSP diagonally scales the system
2020:      back after solving.

2022:    Not Collective

2024:    Input Parameter:
2025: .  ksp - the KSP context

2027:    Output Parameter:
2028: .  fix - PETSC_TRUE to scale back after the system solve, PETSC_FALSE to not
2029:          rescale (default)

2031:    Notes:
2032:      Must be called after KSPSetDiagonalScale()

2034:      If PETSC_TRUE will slow things down, because it rescales the matrix before and
2035:      after each linear solve. This is intended mainly for testing to allow one
2036:      to easily get back the original system to make sure the solution computed is
2037:      accurate enough.

2039:    Level: intermediate

2041: .keywords: KSP, set, options, prefix, database

2043: .seealso: KSPGetDiagonalScale(), KSPSetDiagonalScale(), KSPSetDiagonalScaleFix()
2044: @*/
2045: PetscErrorCode  KSPGetDiagonalScaleFix(KSP ksp,PetscBool  *fix)
2046: {
2050:   *fix = ksp->dscalefix;
2051:   return(0);
2052: }

2056: /*@C
2057:    KSPSetComputeOperators - set routine to compute the linear operators

2059:    Logically Collective

2061:    Input Arguments:
2062: +  ksp - the KSP context
2063: .  func - function to compute the operators
2064: -  ctx - optional context

2066:    Calling sequence of func:
2067: $  func(KSP ksp,Mat A,Mat B,void *ctx)

2069: +  ksp - the KSP context
2070: .  A - the linear operator
2071: .  B - preconditioning matrix
2072: -  ctx - optional user-provided context

2074:    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
2075:           unless either KSPSetComputeOperators() or KSPSetOperators() is called before that KSPSolve() is called.

2077:           To reuse the same preconditioner for the next KSPSolve() and not compute a new one based on the most recently computed matrix call KSPSetReusePreconditioner()

2079:    Level: beginner

2081: .seealso: KSPSetOperators(), KSPSetComputeRHS(), DMKSPSetComputeOperators(), KSPSetComputeInitialGuess()
2082: @*/
2083: PetscErrorCode KSPSetComputeOperators(KSP ksp,PetscErrorCode (*func)(KSP,Mat,Mat,void*),void *ctx)
2084: {
2086:   DM             dm;

2090:   KSPGetDM(ksp,&dm);
2091:   DMKSPSetComputeOperators(dm,func,ctx);
2092:   if (ksp->setupstage == KSP_SETUP_NEWRHS) ksp->setupstage = KSP_SETUP_NEWMATRIX;
2093:   return(0);
2094: }

2098: /*@C
2099:    KSPSetComputeRHS - set routine to compute the right hand side of the linear system

2101:    Logically Collective

2103:    Input Arguments:
2104: +  ksp - the KSP context
2105: .  func - function to compute the right hand side
2106: -  ctx - optional context

2108:    Calling sequence of func:
2109: $  func(KSP ksp,Vec b,void *ctx)

2111: +  ksp - the KSP context
2112: .  b - right hand side of linear system
2113: -  ctx - optional user-provided context

2115:    Notes: The routine you provide will be called EACH you call KSPSolve() to prepare the new right hand side for that solve

2117:    Level: beginner

2119: .seealso: KSPSolve(), DMKSPSetComputeRHS(), KSPSetComputeOperators()
2120: @*/
2121: PetscErrorCode KSPSetComputeRHS(KSP ksp,PetscErrorCode (*func)(KSP,Vec,void*),void *ctx)
2122: {
2124:   DM             dm;

2128:   KSPGetDM(ksp,&dm);
2129:   DMKSPSetComputeRHS(dm,func,ctx);
2130:   return(0);
2131: }

2135: /*@C
2136:    KSPSetComputeInitialGuess - set routine to compute the initial guess of the linear system

2138:    Logically Collective

2140:    Input Arguments:
2141: +  ksp - the KSP context
2142: .  func - function to compute the initial guess
2143: -  ctx - optional context

2145:    Calling sequence of func:
2146: $  func(KSP ksp,Vec x,void *ctx)

2148: +  ksp - the KSP context
2149: .  x - solution vector
2150: -  ctx - optional user-provided context

2152:    Level: beginner

2154: .seealso: KSPSolve(), KSPSetComputeRHS(), KSPSetComputeOperators(), DMKSPSetComputeInitialGuess()
2155: @*/
2156: PetscErrorCode KSPSetComputeInitialGuess(KSP ksp,PetscErrorCode (*func)(KSP,Vec,void*),void *ctx)
2157: {
2159:   DM             dm;

2163:   KSPGetDM(ksp,&dm);
2164:   DMKSPSetComputeInitialGuess(dm,func,ctx);
2165:   return(0);
2166: }