Actual source code: itfunc.c

petsc-3.4.4 2014-03-13
  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
 81: .  c - complex part of computed eigenvalues
 82: -  neig - 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.

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

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

106:    Level: advanced

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

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

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

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

133: /*@
134:    KSPSetUpOnBlocks - Sets up the preconditioner for each block in
135:    the block Jacobi, block Gauss-Seidel, and overlapping Schwarz
136:    methods.

138:    Collective on KSP

140:    Input Parameter:
141: .  ksp - the KSP context

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

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

152:    Level: advanced

154: .keywords: KSP, setup, blocks

156: .seealso: PCSetUpOnBlocks(), KSPSetUp(), PCSetUp()
157: @*/
158: PetscErrorCode  KSPSetUpOnBlocks(KSP ksp)
159: {

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

171: /*@
172:    KSPSetUp - Sets up the internal data structures for the
173:    later use of an iterative solver.

175:    Collective on KSP

177:    Input Parameter:
178: .  ksp   - iterative context obtained from KSPCreate()

180:    Level: developer

182: .keywords: KSP, setup

184: .seealso: KSPCreate(), KSPSolve(), KSPDestroy()
185: @*/
186: PetscErrorCode  KSPSetUp(KSP ksp)
187: {
189:   Mat            A,B;
190:   MatStructure   stflg = SAME_NONZERO_PATTERN;


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

198:   if (!((PetscObject)ksp)->type_name) {
199:     KSPSetType(ksp,KSPGMRES);
200:   }
201:   KSPSetUpNorms_Private(ksp,&ksp->normtype,&ksp->pc_side);

203:   if (ksp->dmActive && !ksp->setupstage) {
204:     /* first time in so build matrix and vector data structures using DM */
205:     if (!ksp->vec_rhs) {DMCreateGlobalVector(ksp->dm,&ksp->vec_rhs);}
206:     if (!ksp->vec_sol) {DMCreateGlobalVector(ksp->dm,&ksp->vec_sol);}
207:     DMCreateMatrix(ksp->dm,MATAIJ,&A);
208:     KSPSetOperators(ksp,A,A,stflg);
209:     PetscObjectDereference((PetscObject)A);
210:   }

212:   if (ksp->dmActive) {
213:     DMKSP kdm;
214:     DMGetDMKSP(ksp->dm,&kdm);

216:     if (kdm->ops->computeinitialguess && ksp->setupstage != KSP_SETUP_NEWRHS) {
217:       /* only computes initial guess the first time through */
218:       (*kdm->ops->computeinitialguess)(ksp,ksp->vec_sol,kdm->initialguessctx);
219:       KSPSetInitialGuessNonzero(ksp,PETSC_TRUE);
220:     }
221:     if (kdm->ops->computerhs) {
222:       (*kdm->ops->computerhs)(ksp,ksp->vec_rhs,kdm->rhsctx);
223:     }

225:     if (ksp->setupstage != KSP_SETUP_NEWRHS) {
226:       if (kdm->ops->computeoperators) {
227:         KSPGetOperators(ksp,&A,&B,NULL);
228:         (*kdm->ops->computeoperators)(ksp,A,B,&stflg,kdm->operatorsctx);
229:         KSPSetOperators(ksp,A,B,stflg);
230:       } else SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_WRONGSTATE,"You called KSPSetDM() but did not use DMKSPSetComputeOperators() or KSPSetDMActive(dm,PETSC_FALSE);");
231:     }
232:   }

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

237:   switch (ksp->setupstage) {
238:   case KSP_SETUP_NEW:
239:     (*ksp->ops->setup)(ksp);
240:     break;
241:   case KSP_SETUP_NEWMATRIX: {   /* This should be replaced with a more general mechanism */
242:     KSPChebyshevSetNewMatrix(ksp);
243:   } break;
244:   default: break;
245:   }

247:   /* scale the matrix if requested */
248:   if (ksp->dscale) {
249:     Mat         mat,pmat;
250:     PetscScalar *xx;
251:     PetscInt    i,n;
252:     PetscBool   zeroflag = PETSC_FALSE;
253:     if (!ksp->pc) {KSPGetPC(ksp,&ksp->pc);}
254:     PCGetOperators(ksp->pc,&mat,&pmat,NULL);
255:     if (!ksp->diagonal) { /* allocate vector to hold diagonal */
256:       MatGetVecs(pmat,&ksp->diagonal,0);
257:     }
258:     MatGetDiagonal(pmat,ksp->diagonal);
259:     VecGetLocalSize(ksp->diagonal,&n);
260:     VecGetArray(ksp->diagonal,&xx);
261:     for (i=0; i<n; i++) {
262:       if (xx[i] != 0.0) xx[i] = 1.0/PetscSqrtReal(PetscAbsScalar(xx[i]));
263:       else {
264:         xx[i]    = 1.0;
265:         zeroflag = PETSC_TRUE;
266:       }
267:     }
268:     VecRestoreArray(ksp->diagonal,&xx);
269:     if (zeroflag) {
270:       PetscInfo(ksp,"Zero detected in diagonal of matrix, using 1 at those locations\n");
271:     }
272:     MatDiagonalScale(pmat,ksp->diagonal,ksp->diagonal);
273:     if (mat != pmat) {MatDiagonalScale(mat,ksp->diagonal,ksp->diagonal);}
274:     ksp->dscalefix2 = PETSC_FALSE;
275:   }
276:   PetscLogEventEnd(KSP_SetUp,ksp,ksp->vec_rhs,ksp->vec_sol,0);
277:   if (!ksp->pc) {KSPGetPC(ksp,&ksp->pc);}
278:   PCSetUp(ksp->pc);
279:   if (ksp->nullsp) {
280:     PetscBool test = PETSC_FALSE;
281:     PetscOptionsGetBool(((PetscObject)ksp)->prefix,"-ksp_test_null_space",&test,NULL);
282:     if (test) {
283:       Mat mat;
284:       PCGetOperators(ksp->pc,&mat,NULL,NULL);
285:       MatNullSpaceTest(ksp->nullsp,mat,NULL);
286:     }
287:   }
288:   ksp->setupstage = KSP_SETUP_NEWRHS;
289:   return(0);
290: }

292: #include <petscdraw.h>
295: /*@
296:    KSPSolve - Solves linear system.

298:    Collective on KSP

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

305:    Options Database Keys:
306: +  -ksp_compute_eigenvalues - compute preconditioned operators eigenvalues
307: .  -ksp_plot_eigenvalues - plot the computed eigenvalues in an X-window
308: .  -ksp_compute_eigenvalues_explicitly - compute the eigenvalues by forming the dense operator and useing LAPACK
309: .  -ksp_plot_eigenvalues_explicitly - plot the explicitly computing eigenvalues
310: .  -ksp_view_mat binary - save matrix to the default binary viewer
311: .  -ksp_view_pmat binary - save matrix used to build preconditioner to the default binary viewer
312: .  -ksp_view_rhs binary - save right hand side vector to the default binary viewer
313: .  -ksp_view_solution binary - save computed solution vector to the default binary viewer
314:            (can be read later with src/ksp/examples/tutorials/ex10.c for testing solvers)
315: .  -ksp_view_mat_explicit - for matrix-free operators, computes the matrix entries and views them
316: .  -ksp_view_preconditioned_operator_explicit - computes the product of the preconditioner and matrix as an explicit matrix and views it
317: .  -ksp_converged_reason - print reason for converged or diverged, also prints number of iterations
318: .  -ksp_final_residual - print 2-norm of true linear system residual at the end of the solution process
319: -  -ksp_view - print the ksp data structure at the end of the system solution

321:    Notes:

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

325:    The operator is specified with KSPSetOperators().

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

330:    If using a direct method (e.g., via the KSP solver
331:    KSPPREONLY and a preconditioner such as PCLU/PCILU),
332:    then its=1.  See KSPSetTolerances() and KSPDefaultConverged()
333:    for more details.

335:    Understanding Convergence:
336:    The routines KSPMonitorSet(), KSPComputeEigenvalues(), and
337:    KSPComputeEigenvaluesExplicitly() provide information on additional
338:    options to monitor convergence and print eigenvalue information.

340:    Level: beginner

342: .keywords: KSP, solve, linear system

344: .seealso: KSPCreate(), KSPSetUp(), KSPDestroy(), KSPSetTolerances(), KSPDefaultConverged(),
345:           KSPSolveTranspose(), KSPGetIterationNumber()
346: @*/
347: PetscErrorCode  KSPSolve(KSP ksp,Vec b,Vec x)
348: {
349:   PetscErrorCode    ierr;
350:   PetscMPIInt       rank;
351:   PetscBool         flag1,flag2,flag3,flg = PETSC_FALSE,inXisinB=PETSC_FALSE,guess_zero;
352:   PetscViewer       viewer;
353:   Mat               mat,premat;
354:   PetscViewerFormat format;


361:   if (x && x == b) {
362:     if (!ksp->guess_zero) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_INCOMP,"Cannot use x == b with nonzero initial guess");
363:     VecDuplicate(b,&x);
364:     inXisinB = PETSC_TRUE;
365:   }
366:   if (b) {
367:     PetscObjectReference((PetscObject)b);
368:     VecDestroy(&ksp->vec_rhs);
369:     ksp->vec_rhs = b;
370:   }
371:   if (x) {
372:     PetscObjectReference((PetscObject)x);
373:     VecDestroy(&ksp->vec_sol);
374:     ksp->vec_sol = x;
375:   }

377:   PetscOptionsGetViewer(PetscObjectComm((PetscObject)ksp),((PetscObject)ksp)->prefix,"-ksp_view_pre",&viewer,&format,&flg);
378:   if (flg && !PetscPreLoadingOn) {
379:     PetscViewerPushFormat(viewer,format);
380:     KSPView(ksp,viewer);
381:     PetscViewerPopFormat(viewer);
382:     PetscViewerDestroy(&viewer);
383:   }

385:   if (ksp->presolve) {
386:     (*ksp->presolve)(ksp,ksp->vec_rhs,ksp->vec_sol,ksp->prectx);
387:   }
388:   PetscLogEventBegin(KSP_Solve,ksp,ksp->vec_rhs,ksp->vec_sol,0);

390:   /* reset the residual history list if requested */
391:   if (ksp->res_hist_reset) ksp->res_hist_len = 0;
392:   ksp->transpose_solve = PETSC_FALSE;

394:   if (ksp->guess) {
395:     KSPFischerGuessFormGuess(ksp->guess,ksp->vec_rhs,ksp->vec_sol);
396:     ksp->guess_zero = PETSC_FALSE;
397:   }
398:   /* KSPSetUp() scales the matrix if needed */
399:   KSPSetUp(ksp);
400:   KSPSetUpOnBlocks(ksp);

402:   /* diagonal scale RHS if called for */
403:   if (ksp->dscale) {
404:     VecPointwiseMult(ksp->vec_rhs,ksp->vec_rhs,ksp->diagonal);
405:     /* second time in, but matrix was scaled back to original */
406:     if (ksp->dscalefix && ksp->dscalefix2) {
407:       Mat mat,pmat;

409:       PCGetOperators(ksp->pc,&mat,&pmat,NULL);
410:       MatDiagonalScale(pmat,ksp->diagonal,ksp->diagonal);
411:       if (mat != pmat) {MatDiagonalScale(mat,ksp->diagonal,ksp->diagonal);}
412:     }

414:     /*  scale initial guess */
415:     if (!ksp->guess_zero) {
416:       if (!ksp->truediagonal) {
417:         VecDuplicate(ksp->diagonal,&ksp->truediagonal);
418:         VecCopy(ksp->diagonal,ksp->truediagonal);
419:         VecReciprocal(ksp->truediagonal);
420:       }
421:       VecPointwiseMult(ksp->vec_sol,ksp->vec_sol,ksp->truediagonal);
422:     }
423:   }
424:   PCPreSolve(ksp->pc,ksp);

426:   if (ksp->guess_zero) { VecSet(ksp->vec_sol,0.0);}
427:   if (ksp->guess_knoll) {
428:     PCApply(ksp->pc,ksp->vec_rhs,ksp->vec_sol);
429:     KSP_RemoveNullSpace(ksp,ksp->vec_sol);
430:     ksp->guess_zero = PETSC_FALSE;
431:   }

433:   /* can we mark the initial guess as zero for this solve? */
434:   guess_zero = ksp->guess_zero;
435:   if (!ksp->guess_zero) {
436:     PetscReal norm;

438:     VecNormAvailable(ksp->vec_sol,NORM_2,&flg,&norm);
439:     if (flg && !norm) ksp->guess_zero = PETSC_TRUE;
440:   }
441:   (*ksp->ops->solve)(ksp);
442:   ksp->guess_zero = guess_zero;

444:   if (!ksp->reason) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_PLIB,"Internal error, solver returned without setting converged reason");
445:   if (ksp->printreason) {
446:     PetscViewerASCIIAddTab(PETSC_VIEWER_STDOUT_(PetscObjectComm((PetscObject)ksp)),((PetscObject)ksp)->tablevel);
447:     if (ksp->reason > 0) {
448:       PetscViewerASCIIPrintf(PETSC_VIEWER_STDOUT_(PetscObjectComm((PetscObject)ksp)),"Linear solve converged due to %s iterations %D\n",KSPConvergedReasons[ksp->reason],ksp->its);
449:     } else {
450:       PetscViewerASCIIPrintf(PETSC_VIEWER_STDOUT_(PetscObjectComm((PetscObject)ksp)),"Linear solve did not converge due to %s iterations %D\n",KSPConvergedReasons[ksp->reason],ksp->its);
451:     }
452:     PetscViewerASCIISubtractTab(PETSC_VIEWER_STDOUT_(PetscObjectComm((PetscObject)ksp)),((PetscObject)ksp)->tablevel);
453:   }
454:   PCPostSolve(ksp->pc,ksp);

456:   /* diagonal scale solution if called for */
457:   if (ksp->dscale) {
458:     VecPointwiseMult(ksp->vec_sol,ksp->vec_sol,ksp->diagonal);
459:     /* unscale right hand side and matrix */
460:     if (ksp->dscalefix) {
461:       Mat mat,pmat;

463:       VecReciprocal(ksp->diagonal);
464:       VecPointwiseMult(ksp->vec_rhs,ksp->vec_rhs,ksp->diagonal);
465:       PCGetOperators(ksp->pc,&mat,&pmat,NULL);
466:       MatDiagonalScale(pmat,ksp->diagonal,ksp->diagonal);
467:       if (mat != pmat) {MatDiagonalScale(mat,ksp->diagonal,ksp->diagonal);}
468:       VecReciprocal(ksp->diagonal);
469:       ksp->dscalefix2 = PETSC_TRUE;
470:     }
471:   }
472:   PetscLogEventEnd(KSP_Solve,ksp,ksp->vec_rhs,ksp->vec_sol,0);
473:   if (ksp->postsolve) {
474:     (*ksp->postsolve)(ksp,ksp->vec_rhs,ksp->vec_sol,ksp->postctx);
475:   }

477:   if (ksp->guess) {
478:     KSPFischerGuessUpdate(ksp->guess,ksp->vec_sol);
479:   }

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

483:   PCGetOperators(ksp->pc,&mat,&premat,NULL);
484:   MatViewFromOptions(mat,((PetscObject)ksp)->prefix,"-ksp_view_mat");
485:   MatViewFromOptions(premat,((PetscObject)ksp)->prefix,"-ksp_view_pmat");
486:   VecViewFromOptions(ksp->vec_rhs,((PetscObject)ksp)->prefix,"-ksp_view_rhs");

488:   flag1 = PETSC_FALSE;
489:   flag2 = PETSC_FALSE;
490:   flag3 = PETSC_FALSE;
491:   PetscOptionsGetBool(((PetscObject)ksp)->prefix,"-ksp_compute_eigenvalues",&flag1,NULL);
492:   PetscOptionsGetBool(((PetscObject)ksp)->prefix,"-ksp_plot_eigenvalues",&flag2,NULL);
493:   PetscOptionsGetBool(((PetscObject)ksp)->prefix,"-ksp_plot_eigencontours",&flag3,NULL);
494:   if (flag1 || flag2 || flag3) {
495:     PetscInt  nits,n,i,neig;
496:     PetscReal *r,*c;

498:     KSPGetIterationNumber(ksp,&nits);
499:     n    = nits+2;

501:     if (!nits) {
502:       PetscPrintf(PetscObjectComm((PetscObject)ksp),"Zero iterations in solver, cannot approximate any eigenvalues\n");
503:     } else {
504:       PetscMalloc(2*n*sizeof(PetscReal),&r);
505:       c    = r + n;
506:       KSPComputeEigenvalues(ksp,n,r,c,&neig);
507:       if (flag1) {
508:         PetscPrintf(PetscObjectComm((PetscObject)ksp),"Iteratively computed eigenvalues\n");
509:         for (i=0; i<neig; i++) {
510:           if (c[i] >= 0.0) {
511:             PetscPrintf(PetscObjectComm((PetscObject)ksp),"%G + %Gi\n",r[i],c[i]);
512:           } else {
513:             PetscPrintf(PetscObjectComm((PetscObject)ksp),"%G - %Gi\n",r[i],-c[i]);
514:           }
515:         }
516:       }
517:       if (flag2 && !rank) {
518:         PetscDraw   draw;
519:         PetscDrawSP drawsp;

521:         if (!ksp->eigviewer) {
522:           PetscViewerDrawOpen(PETSC_COMM_SELF,0,"Iteratively Computed Eigenvalues",PETSC_DECIDE,PETSC_DECIDE,400,400,&ksp->eigviewer);
523:         }
524:         PetscViewerDrawGetDraw(ksp->eigviewer,0,&draw);
525:         PetscDrawSPCreate(draw,1,&drawsp);
526:         PetscDrawSPReset(drawsp);
527:         for (i=0; i<neig; i++) {
528:           PetscDrawSPAddPoint(drawsp,r+i,c+i);
529:         }
530:         PetscDrawSPDraw(drawsp,PETSC_TRUE);
531:         PetscDrawSPDestroy(&drawsp);
532:       }
533:       if (flag3 && !rank) {
534:         KSPPlotEigenContours_Private(ksp,neig,r,c);
535:       }
536:       PetscFree(r);
537:     }
538:   }

540:   flag1 = PETSC_FALSE;
541:   PetscOptionsGetBool(((PetscObject)ksp)->prefix,"-ksp_compute_singularvalues",&flag1,NULL);
542:   if (flag1) {
543:     PetscInt nits;

545:     KSPGetIterationNumber(ksp,&nits);
546:     if (!nits) {
547:       PetscPrintf(PetscObjectComm((PetscObject)ksp),"Zero iterations in solver, cannot approximate any singular values\n");
548:     } else {
549:       PetscReal emax,emin;

551:       KSPComputeExtremeSingularValues(ksp,&emax,&emin);
552:       PetscPrintf(PetscObjectComm((PetscObject)ksp),"Iteratively computed extreme singular values: max %G min %G max/min %G\n",emax,emin,emax/emin);
553:     }
554:   }


557:   flag1 = PETSC_FALSE;
558:   flag2 = PETSC_FALSE;
559:   PetscOptionsGetBool(((PetscObject)ksp)->prefix,"-ksp_compute_eigenvalues_explicitly",&flag1,NULL);
560:   PetscOptionsGetBool(((PetscObject)ksp)->prefix,"-ksp_plot_eigenvalues_explicitly",&flag2,NULL);
561:   if (flag1 || flag2) {
562:     PetscInt  n,i;
563:     PetscReal *r,*c;
564:     VecGetSize(ksp->vec_sol,&n);
565:     PetscMalloc2(n,PetscReal,&r,n,PetscReal,&c);
566:     KSPComputeEigenvaluesExplicitly(ksp,n,r,c);
567:     if (flag1) {
568:       PetscPrintf(PetscObjectComm((PetscObject)ksp),"Explicitly computed eigenvalues\n");
569:       for (i=0; i<n; i++) {
570:         if (c[i] >= 0.0) {
571:           PetscPrintf(PetscObjectComm((PetscObject)ksp),"%G + %Gi\n",r[i],c[i]);
572:         } else {
573:           PetscPrintf(PetscObjectComm((PetscObject)ksp),"%G - %Gi\n",r[i],-c[i]);
574:         }
575:       }
576:     }
577:     if (flag2 && !rank) {
578:       PetscDraw   draw;
579:       PetscDrawSP drawsp;

581:       if (!ksp->eigviewer) {
582:         PetscViewerDrawOpen(PETSC_COMM_SELF,0,"Explicitly Computed Eigenvalues",0,320,400,400,&ksp->eigviewer);
583:       }
584:       PetscViewerDrawGetDraw(ksp->eigviewer,0,&draw);
585:       PetscDrawSPCreate(draw,1,&drawsp);
586:       PetscDrawSPReset(drawsp);
587:       for (i=0; i<n; i++) {
588:         PetscDrawSPAddPoint(drawsp,r+i,c+i);
589:       }
590:       PetscDrawSPDraw(drawsp,PETSC_TRUE);
591:       PetscDrawSPDestroy(&drawsp);
592:     }
593:     PetscFree2(r,c);
594:   }

596:   PetscOptionsHasName(((PetscObject)ksp)->prefix,"-ksp_view_mat_explicit",&flag2);
597:   if (flag2) {
598:     Mat A,B;
599:     PCGetOperators(ksp->pc,&A,NULL,NULL);
600:     MatComputeExplicitOperator(A,&B);
601:     MatViewFromOptions(B,((PetscObject)ksp)->prefix,"-ksp_view_mat_explicit");
602:     MatDestroy(&B);
603:   }
604:   PetscOptionsHasName(((PetscObject)ksp)->prefix,"-ksp_view_preconditioned_operator_explicit",&flag2);
605:   if (flag2) {
606:     Mat B;
607:     KSPComputeExplicitOperator(ksp,&B);
608:     MatViewFromOptions(B,((PetscObject)ksp)->prefix,"-ksp_view_preconditioned_operator_explicit");
609:     MatDestroy(&B);
610:   }
611:   PetscOptionsGetViewer(PetscObjectComm((PetscObject)ksp),((PetscObject)ksp)->prefix,"-ksp_view",&viewer,&format,&flg);
612:   if (flg && !PetscPreLoadingOn) {
613:     PetscViewerPushFormat(viewer,format);
614:     KSPView(ksp,viewer);
615:     PetscViewerPopFormat(viewer);
616:     PetscViewerDestroy(&viewer);
617:   }

619:   flg  = PETSC_FALSE;
620:   PetscOptionsGetBool(((PetscObject)ksp)->prefix,"-ksp_final_residual",&flg,NULL);
621:   if (flg) {
622:     Mat       A;
623:     Vec       t;
624:     PetscReal norm;
625:     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");
626:     PCGetOperators(ksp->pc,&A,0,0);
627:     VecDuplicate(ksp->vec_rhs,&t);
628:     KSP_MatMult(ksp,A,ksp->vec_sol,t);
629:     VecAYPX(t, -1.0, ksp->vec_rhs);
630:     VecNorm(t,NORM_2,&norm);
631:     VecDestroy(&t);
632:     PetscPrintf(PetscObjectComm((PetscObject)ksp),"KSP final norm of residual %G\n",norm);
633:   }
634:   VecViewFromOptions(ksp->vec_sol,((PetscObject)ksp)->prefix,"-ksp_view_solution");

636:   if (inXisinB) {
637:     VecCopy(x,b);
638:     VecDestroy(&x);
639:   }
640:   PetscObjectAMSBlock((PetscObject)ksp);
641:   if (ksp->errorifnotconverged && ksp->reason < 0) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_NOT_CONVERGED,"KSPSolve has not converged");
642:   return(0);
643: }

647: /*@
648:    KSPSolveTranspose - Solves the transpose of a linear system.

650:    Collective on KSP

652:    Input Parameter:
653: +  ksp - iterative context obtained from KSPCreate()
654: .  b - right hand side vector
655: -  x - solution vector

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

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

661:    Level: developer

663: .keywords: KSP, solve, linear system

665: .seealso: KSPCreate(), KSPSetUp(), KSPDestroy(), KSPSetTolerances(), KSPDefaultConverged(),
666:           KSPSolve()
667: @*/

669: PetscErrorCode  KSPSolveTranspose(KSP ksp,Vec b,Vec x)
670: {
672:   PetscBool      inXisinB=PETSC_FALSE;

678:   if (x == b) {
679:     VecDuplicate(b,&x);
680:     inXisinB = PETSC_TRUE;
681:   }
682:   PetscObjectReference((PetscObject)b);
683:   PetscObjectReference((PetscObject)x);
684:   VecDestroy(&ksp->vec_rhs);
685:   VecDestroy(&ksp->vec_sol);

687:   ksp->vec_rhs         = b;
688:   ksp->vec_sol         = x;
689:   ksp->transpose_solve = PETSC_TRUE;

691:   KSPSetUp(ksp);
692:   if (ksp->guess_zero) { VecSet(ksp->vec_sol,0.0);}
693:   (*ksp->ops->solve)(ksp);
694:   if (!ksp->reason) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_PLIB,"Internal error, solver returned without setting converged reason");
695:   if (ksp->printreason) {
696:     if (ksp->reason > 0) {
697:       PetscPrintf(PetscObjectComm((PetscObject)ksp),"Linear solve converged due to %s iterations %D\n",KSPConvergedReasons[ksp->reason],ksp->its);
698:     } else {
699:       PetscPrintf(PetscObjectComm((PetscObject)ksp),"Linear solve did not converge due to %s iterations %D\n",KSPConvergedReasons[ksp->reason],ksp->its);
700:     }
701:   }
702:   if (inXisinB) {
703:     VecCopy(x,b);
704:     VecDestroy(&x);
705:   }
706:   if (ksp->errorifnotconverged && ksp->reason < 0) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_NOT_CONVERGED,"KSPSolve has not converged");
707:   return(0);
708: }

712: /*@
713:    KSPReset - Resets a KSP context to the kspsetupcalled = 0 state and removes any allocated Vecs and Mats

715:    Collective on KSP

717:    Input Parameter:
718: .  ksp - iterative context obtained from KSPCreate()

720:    Level: beginner

722: .keywords: KSP, destroy

724: .seealso: KSPCreate(), KSPSetUp(), KSPSolve()
725: @*/
726: PetscErrorCode  KSPReset(KSP ksp)
727: {

732:   if (!ksp) return(0);
733:   if (ksp->ops->reset) {
734:     (*ksp->ops->reset)(ksp);
735:   }
736:   if (ksp->pc) {PCReset(ksp->pc);}
737:   KSPFischerGuessDestroy(&ksp->guess);
738:   VecDestroyVecs(ksp->nwork,&ksp->work);
739:   VecDestroy(&ksp->vec_rhs);
740:   VecDestroy(&ksp->vec_sol);
741:   VecDestroy(&ksp->diagonal);
742:   VecDestroy(&ksp->truediagonal);
743:   MatNullSpaceDestroy(&ksp->nullsp);

745:   ksp->setupstage = KSP_SETUP_NEW;
746:   return(0);
747: }

751: /*@
752:    KSPDestroy - Destroys KSP context.

754:    Collective on KSP

756:    Input Parameter:
757: .  ksp - iterative context obtained from KSPCreate()

759:    Level: beginner

761: .keywords: KSP, destroy

763: .seealso: KSPCreate(), KSPSetUp(), KSPSolve()
764: @*/
765: PetscErrorCode  KSPDestroy(KSP *ksp)
766: {
768:   PC             pc;

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

775:   PetscObjectAMSViewOff((PetscObject)*ksp);
776:   /*
777:    Avoid a cascading call to PCReset(ksp->pc) from the following call:
778:    PCReset() shouldn't be called from KSPDestroy() as it is unprotected by pc's
779:    refcount (and may be shared, e.g., by other ksps).
780:    */
781:   pc         = (*ksp)->pc;
782:   (*ksp)->pc = NULL;
783:   KSPReset((*ksp));
784:   (*ksp)->pc = pc;
785:     if ((*ksp)->ops->destroy) {(*(*ksp)->ops->destroy)(*ksp);}

787:   DMDestroy(&(*ksp)->dm);
788:   PCDestroy(&(*ksp)->pc);
789:   PetscFree((*ksp)->res_hist_alloc);
790:   if ((*ksp)->convergeddestroy) {
791:     (*(*ksp)->convergeddestroy)((*ksp)->cnvP);
792:   }
793:   KSPMonitorCancel((*ksp));
794:   PetscViewerDestroy(&(*ksp)->eigviewer);
795:   PetscHeaderDestroy(ksp);
796:   return(0);
797: }

801: /*@
802:     KSPSetPCSide - Sets the preconditioning side.

804:     Logically Collective on KSP

806:     Input Parameter:
807: .   ksp - iterative context obtained from KSPCreate()

809:     Output Parameter:
810: .   side - the preconditioning side, where side is one of
811: .vb
812:       PC_LEFT - left preconditioning (default)
813:       PC_RIGHT - right preconditioning
814:       PC_SYMMETRIC - symmetric preconditioning
815: .ve

817:     Options Database Keys:
818: .   -ksp_pc_side <right,left,symmetric>

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

826:     Level: intermediate

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

830: .seealso: KSPGetPCSide()
831: @*/
832: PetscErrorCode  KSPSetPCSide(KSP ksp,PCSide side)
833: {
837:   ksp->pc_side = side;
838:   return(0);
839: }

843: /*@
844:     KSPGetPCSide - Gets the preconditioning side.

846:     Not Collective

848:     Input Parameter:
849: .   ksp - iterative context obtained from KSPCreate()

851:     Output Parameter:
852: .   side - the preconditioning side, where side is one of
853: .vb
854:       PC_LEFT - left preconditioning (default)
855:       PC_RIGHT - right preconditioning
856:       PC_SYMMETRIC - symmetric preconditioning
857: .ve

859:     Level: intermediate

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

863: .seealso: KSPSetPCSide()
864: @*/
865: PetscErrorCode  KSPGetPCSide(KSP ksp,PCSide *side)
866: {

872:   KSPSetUpNorms_Private(ksp,&ksp->normtype,&ksp->pc_side);
873:   *side = ksp->pc_side;
874:   return(0);
875: }

879: /*@
880:    KSPGetTolerances - Gets the relative, absolute, divergence, and maximum
881:    iteration tolerances used by the default KSP convergence tests.

883:    Not Collective

885:    Input Parameter:
886: .  ksp - the Krylov subspace context

888:    Output Parameters:
889: +  rtol - the relative convergence tolerance
890: .  abstol - the absolute convergence tolerance
891: .  dtol - the divergence tolerance
892: -  maxits - maximum number of iterations

894:    Notes:
895:    The user can specify NULL for any parameter that is not needed.

897:    Level: intermediate

899: .keywords: KSP, get, tolerance, absolute, relative, divergence, convergence,
900:            maximum, iterations

902: .seealso: KSPSetTolerances()
903: @*/
904: PetscErrorCode  KSPGetTolerances(KSP ksp,PetscReal *rtol,PetscReal *abstol,PetscReal *dtol,PetscInt *maxits)
905: {
908:   if (abstol) *abstol = ksp->abstol;
909:   if (rtol) *rtol = ksp->rtol;
910:   if (dtol) *dtol = ksp->divtol;
911:   if (maxits) *maxits = ksp->max_it;
912:   return(0);
913: }

917: /*@
918:    KSPSetTolerances - Sets the relative, absolute, divergence, and maximum
919:    iteration tolerances used by the default KSP convergence testers.

921:    Logically Collective on KSP

923:    Input Parameters:
924: +  ksp - the Krylov subspace context
925: .  rtol - the relative convergence tolerance
926:    (relative decrease in the residual norm)
927: .  abstol - the absolute convergence tolerance
928:    (absolute size of the residual norm)
929: .  dtol - the divergence tolerance
930:    (amount residual can increase before KSPDefaultConverged()
931:    concludes that the method is diverging)
932: -  maxits - maximum number of iterations to use

934:    Options Database Keys:
935: +  -ksp_atol <abstol> - Sets abstol
936: .  -ksp_rtol <rtol> - Sets rtol
937: .  -ksp_divtol <dtol> - Sets dtol
938: -  -ksp_max_it <maxits> - Sets maxits

940:    Notes:
941:    Use PETSC_DEFAULT to retain the default value of any of the tolerances.

943:    See KSPDefaultConverged() for details on the use of these parameters
944:    in the default convergence test.  See also KSPSetConvergenceTest()
945:    for setting user-defined stopping criteria.

947:    Level: intermediate

949: .keywords: KSP, set, tolerance, absolute, relative, divergence,
950:            convergence, maximum, iterations

952: .seealso: KSPGetTolerances(), KSPDefaultConverged(), KSPSetConvergenceTest()
953: @*/
954: PetscErrorCode  KSPSetTolerances(KSP ksp,PetscReal rtol,PetscReal abstol,PetscReal dtol,PetscInt maxits)
955: {

963:   if (rtol != PETSC_DEFAULT) {
964:     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",rtol);
965:     ksp->rtol = rtol;
966:   }
967:   if (abstol != PETSC_DEFAULT) {
968:     if (abstol < 0.0) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Absolute tolerance %G must be non-negative",abstol);
969:     ksp->abstol = abstol;
970:   }
971:   if (dtol != PETSC_DEFAULT) {
972:     if (dtol < 0.0) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Divergence tolerance %G must be larger than 1.0",dtol);
973:     ksp->divtol = dtol;
974:   }
975:   if (maxits != PETSC_DEFAULT) {
976:     if (maxits < 0) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Maximum number of iterations %D must be non-negative",maxits);
977:     ksp->max_it = maxits;
978:   }
979:   return(0);
980: }

984: /*@
985:    KSPSetInitialGuessNonzero - Tells the iterative solver that the
986:    initial guess is nonzero; otherwise KSP assumes the initial guess
987:    is to be zero (and thus zeros it out before solving).

989:    Logically Collective on KSP

991:    Input Parameters:
992: +  ksp - iterative context obtained from KSPCreate()
993: -  flg - PETSC_TRUE indicates the guess is non-zero, PETSC_FALSE indicates the guess is zero

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

998:    Level: beginner

1000:    Notes:
1001:     If this is not called the X vector is zeroed in the call to KSPSolve().

1003: .keywords: KSP, set, initial guess, nonzero

1005: .seealso: KSPGetInitialGuessNonzero(), KSPSetInitialGuessKnoll(), KSPGetInitialGuessKnoll()
1006: @*/
1007: PetscErrorCode  KSPSetInitialGuessNonzero(KSP ksp,PetscBool flg)
1008: {
1012:   ksp->guess_zero = (PetscBool) !(int)flg;
1013:   return(0);
1014: }

1018: /*@
1019:    KSPGetInitialGuessNonzero - Determines whether the KSP solver is using
1020:    a zero initial guess.

1022:    Not Collective

1024:    Input Parameter:
1025: .  ksp - iterative context obtained from KSPCreate()

1027:    Output Parameter:
1028: .  flag - PETSC_TRUE if guess is nonzero, else PETSC_FALSE

1030:    Level: intermediate

1032: .keywords: KSP, set, initial guess, nonzero

1034: .seealso: KSPSetInitialGuessNonzero(), KSPSetInitialGuessKnoll(), KSPGetInitialGuessKnoll()
1035: @*/
1036: PetscErrorCode  KSPGetInitialGuessNonzero(KSP ksp,PetscBool  *flag)
1037: {
1041:   if (ksp->guess_zero) *flag = PETSC_FALSE;
1042:   else *flag = PETSC_TRUE;
1043:   return(0);
1044: }

1048: /*@
1049:    KSPSetErrorIfNotConverged - Causes KSPSolve() to generate an error if the solver has not converged.

1051:    Logically Collective on KSP

1053:    Input Parameters:
1054: +  ksp - iterative context obtained from KSPCreate()
1055: -  flg - PETSC_TRUE indicates you want the error generated

1057:    Options database keys:
1058: .  -ksp_error_if_not_converged : this takes an optional truth value (0/1/no/yes/true/false)

1060:    Level: intermediate

1062:    Notes:
1063:     Normally PETSc continues if a linear solver fails to converge, you can call KSPGetConvergedReason() after a KSPSolve()
1064:     to determine if it has converged.

1066: .keywords: KSP, set, initial guess, nonzero

1068: .seealso: KSPGetInitialGuessNonzero(), KSPSetInitialGuessKnoll(), KSPGetInitialGuessKnoll(), KSPGetErrorIfNotConverged()
1069: @*/
1070: PetscErrorCode  KSPSetErrorIfNotConverged(KSP ksp,PetscBool flg)
1071: {
1075:   ksp->errorifnotconverged = flg;
1076:   return(0);
1077: }

1081: /*@
1082:    KSPGetErrorIfNotConverged - Will KSPSolve() generate an error if the solver does not converge?

1084:    Not Collective

1086:    Input Parameter:
1087: .  ksp - iterative context obtained from KSPCreate()

1089:    Output Parameter:
1090: .  flag - PETSC_TRUE if it will generate an error, else PETSC_FALSE

1092:    Level: intermediate

1094: .keywords: KSP, set, initial guess, nonzero

1096: .seealso: KSPSetInitialGuessNonzero(), KSPSetInitialGuessKnoll(), KSPGetInitialGuessKnoll(), KSPSetErrorIfNotConverged()
1097: @*/
1098: PetscErrorCode  KSPGetErrorIfNotConverged(KSP ksp,PetscBool  *flag)
1099: {
1103:   *flag = ksp->errorifnotconverged;
1104:   return(0);
1105: }

1109: /*@
1110:    KSPSetInitialGuessKnoll - Tells the iterative solver to use PCApply(pc,b,..) to compute the initial guess (The Knoll trick)

1112:    Logically Collective on KSP

1114:    Input Parameters:
1115: +  ksp - iterative context obtained from KSPCreate()
1116: -  flg - PETSC_TRUE or PETSC_FALSE

1118:    Level: advanced


1121: .keywords: KSP, set, initial guess, nonzero

1123: .seealso: KSPGetInitialGuessKnoll(), KSPSetInitialGuessNonzero(), KSPGetInitialGuessNonzero()
1124: @*/
1125: PetscErrorCode  KSPSetInitialGuessKnoll(KSP ksp,PetscBool flg)
1126: {
1130:   ksp->guess_knoll = flg;
1131:   return(0);
1132: }

1136: /*@
1137:    KSPGetInitialGuessKnoll - Determines whether the KSP solver is using the Knoll trick (using PCApply(pc,b,...) to compute
1138:      the initial guess

1140:    Not Collective

1142:    Input Parameter:
1143: .  ksp - iterative context obtained from KSPCreate()

1145:    Output Parameter:
1146: .  flag - PETSC_TRUE if using Knoll trick, else PETSC_FALSE

1148:    Level: advanced

1150: .keywords: KSP, set, initial guess, nonzero

1152: .seealso: KSPSetInitialGuessKnoll(), KSPSetInitialGuessNonzero(), KSPGetInitialGuessNonzero()
1153: @*/
1154: PetscErrorCode  KSPGetInitialGuessKnoll(KSP ksp,PetscBool  *flag)
1155: {
1159:   *flag = ksp->guess_knoll;
1160:   return(0);
1161: }

1165: /*@
1166:    KSPGetComputeSingularValues - Gets the flag indicating whether the extreme singular
1167:    values will be calculated via a Lanczos or Arnoldi process as the linear
1168:    system is solved.

1170:    Not Collective

1172:    Input Parameter:
1173: .  ksp - iterative context obtained from KSPCreate()

1175:    Output Parameter:
1176: .  flg - PETSC_TRUE or PETSC_FALSE

1178:    Options Database Key:
1179: .  -ksp_monitor_singular_value - Activates KSPSetComputeSingularValues()

1181:    Notes:
1182:    Currently this option is not valid for all iterative methods.

1184:    Many users may just want to use the monitoring routine
1185:    KSPMonitorSingularValue() (which can be set with option -ksp_monitor_singular_value)
1186:    to print the singular values at each iteration of the linear solve.

1188:    Level: advanced

1190: .keywords: KSP, set, compute, singular values

1192: .seealso: KSPComputeExtremeSingularValues(), KSPMonitorSingularValue()
1193: @*/
1194: PetscErrorCode  KSPGetComputeSingularValues(KSP ksp,PetscBool  *flg)
1195: {
1199:   *flg = ksp->calc_sings;
1200:   return(0);
1201: }

1205: /*@
1206:    KSPSetComputeSingularValues - Sets a flag so that the extreme singular
1207:    values will be calculated via a Lanczos or Arnoldi process as the linear
1208:    system is solved.

1210:    Logically Collective on KSP

1212:    Input Parameters:
1213: +  ksp - iterative context obtained from KSPCreate()
1214: -  flg - PETSC_TRUE or PETSC_FALSE

1216:    Options Database Key:
1217: .  -ksp_monitor_singular_value - Activates KSPSetComputeSingularValues()

1219:    Notes:
1220:    Currently this option is not valid for all iterative methods.

1222:    Many users may just want to use the monitoring routine
1223:    KSPMonitorSingularValue() (which can be set with option -ksp_monitor_singular_value)
1224:    to print the singular values at each iteration of the linear solve.

1226:    Level: advanced

1228: .keywords: KSP, set, compute, singular values

1230: .seealso: KSPComputeExtremeSingularValues(), KSPMonitorSingularValue()
1231: @*/
1232: PetscErrorCode  KSPSetComputeSingularValues(KSP ksp,PetscBool flg)
1233: {
1237:   ksp->calc_sings = flg;
1238:   return(0);
1239: }

1243: /*@
1244:    KSPGetComputeEigenvalues - Gets the flag indicating that the extreme eigenvalues
1245:    values will be calculated via a Lanczos or Arnoldi process as the linear
1246:    system is solved.

1248:    Not Collective

1250:    Input Parameter:
1251: .  ksp - iterative context obtained from KSPCreate()

1253:    Output Parameter:
1254: .  flg - PETSC_TRUE or PETSC_FALSE

1256:    Notes:
1257:    Currently this option is not valid for all iterative methods.

1259:    Level: advanced

1261: .keywords: KSP, set, compute, eigenvalues

1263: .seealso: KSPComputeEigenvalues(), KSPComputeEigenvaluesExplicitly()
1264: @*/
1265: PetscErrorCode  KSPGetComputeEigenvalues(KSP ksp,PetscBool  *flg)
1266: {
1270:   *flg = ksp->calc_sings;
1271:   return(0);
1272: }

1276: /*@
1277:    KSPSetComputeEigenvalues - Sets a flag so that the extreme eigenvalues
1278:    values will be calculated via a Lanczos or Arnoldi process as the linear
1279:    system is solved.

1281:    Logically Collective on KSP

1283:    Input Parameters:
1284: +  ksp - iterative context obtained from KSPCreate()
1285: -  flg - PETSC_TRUE or PETSC_FALSE

1287:    Notes:
1288:    Currently this option is not valid for all iterative methods.

1290:    Level: advanced

1292: .keywords: KSP, set, compute, eigenvalues

1294: .seealso: KSPComputeEigenvalues(), KSPComputeEigenvaluesExplicitly()
1295: @*/
1296: PetscErrorCode  KSPSetComputeEigenvalues(KSP ksp,PetscBool flg)
1297: {
1301:   ksp->calc_sings = flg;
1302:   return(0);
1303: }

1307: /*@
1308:    KSPGetRhs - Gets the right-hand-side vector for the linear system to
1309:    be solved.

1311:    Not Collective

1313:    Input Parameter:
1314: .  ksp - iterative context obtained from KSPCreate()

1316:    Output Parameter:
1317: .  r - right-hand-side vector

1319:    Level: developer

1321: .keywords: KSP, get, right-hand-side, rhs

1323: .seealso: KSPGetSolution(), KSPSolve()
1324: @*/
1325: PetscErrorCode  KSPGetRhs(KSP ksp,Vec *r)
1326: {
1330:   *r = ksp->vec_rhs;
1331:   return(0);
1332: }

1336: /*@
1337:    KSPGetSolution - Gets the location of the solution for the
1338:    linear system to be solved.  Note that this may not be where the solution
1339:    is stored during the iterative process; see KSPBuildSolution().

1341:    Not Collective

1343:    Input Parameters:
1344: .  ksp - iterative context obtained from KSPCreate()

1346:    Output Parameters:
1347: .  v - solution vector

1349:    Level: developer

1351: .keywords: KSP, get, solution

1353: .seealso: KSPGetRhs(),  KSPBuildSolution(), KSPSolve()
1354: @*/
1355: PetscErrorCode  KSPGetSolution(KSP ksp,Vec *v)
1356: {
1360:   *v = ksp->vec_sol;
1361:   return(0);
1362: }

1366: /*@
1367:    KSPSetPC - Sets the preconditioner to be used to calculate the
1368:    application of the preconditioner on a vector.

1370:    Collective on KSP

1372:    Input Parameters:
1373: +  ksp - iterative context obtained from KSPCreate()
1374: -  pc   - the preconditioner object

1376:    Notes:
1377:    Use KSPGetPC() to retrieve the preconditioner context (for example,
1378:    to free it at the end of the computations).

1380:    Level: developer

1382: .keywords: KSP, set, precondition, Binv

1384: .seealso: KSPGetPC()
1385: @*/
1386: PetscErrorCode  KSPSetPC(KSP ksp,PC pc)
1387: {

1394:   PetscObjectReference((PetscObject)pc);
1395:   PCDestroy(&ksp->pc);
1396:   ksp->pc = pc;
1397:   PetscLogObjectParent(ksp,ksp->pc);
1398:   return(0);
1399: }

1403: /*@
1404:    KSPGetPC - Returns a pointer to the preconditioner context
1405:    set with KSPSetPC().

1407:    Not Collective

1409:    Input Parameters:
1410: .  ksp - iterative context obtained from KSPCreate()

1412:    Output Parameter:
1413: .  pc - preconditioner context

1415:    Level: developer

1417: .keywords: KSP, get, preconditioner, Binv

1419: .seealso: KSPSetPC()
1420: @*/
1421: PetscErrorCode  KSPGetPC(KSP ksp,PC *pc)
1422: {

1428:   if (!ksp->pc) {
1429:     PCCreate(PetscObjectComm((PetscObject)ksp),&ksp->pc);
1430:     PetscObjectIncrementTabLevel((PetscObject)ksp->pc,(PetscObject)ksp,0);
1431:     PetscLogObjectParent(ksp,ksp->pc);
1432:   }
1433:   *pc = ksp->pc;
1434:   return(0);
1435: }

1439: /*@
1440:    KSPMonitor - runs the user provided monitor routines, if they exist

1442:    Collective on KSP

1444:    Input Parameters:
1445: +  ksp - iterative context obtained from KSPCreate()
1446: .  it - iteration number
1447: -  rnorm - relative norm of the residual

1449:    Notes:
1450:    This routine is called by the KSP implementations.
1451:    It does not typically need to be called by the user.

1453:    Level: developer

1455: .seealso: KSPMonitorSet()
1456: @*/
1457: PetscErrorCode KSPMonitor(KSP ksp,PetscInt it,PetscReal rnorm)
1458: {
1459:   PetscInt       i, n = ksp->numbermonitors;

1463:   for (i=0; i<n; i++) {
1464:     (*ksp->monitor[i])(ksp,it,rnorm,ksp->monitorcontext[i]);
1465:   }
1466:   return(0);
1467: }

1471: /*@C
1472:    KSPMonitorSet - Sets an ADDITIONAL function to be called at every iteration to monitor
1473:    the residual/error etc.

1475:    Logically Collective on KSP

1477:    Input Parameters:
1478: +  ksp - iterative context obtained from KSPCreate()
1479: .  monitor - pointer to function (if this is NULL, it turns off monitoring
1480: .  mctx    - [optional] context for private data for the
1481:              monitor routine (use NULL if no context is desired)
1482: -  monitordestroy - [optional] routine that frees monitor context
1483:           (may be NULL)

1485:    Calling Sequence of monitor:
1486: $     monitor (KSP ksp, int it, PetscReal rnorm, void *mctx)

1488: +  ksp - iterative context obtained from KSPCreate()
1489: .  it - iteration number
1490: .  rnorm - (estimated) 2-norm of (preconditioned) residual
1491: -  mctx  - optional monitoring context, as set by KSPMonitorSet()

1493:    Options Database Keys:
1494: +    -ksp_monitor        - sets KSPMonitorDefault()
1495: .    -ksp_monitor_true_residual    - sets KSPMonitorTrueResidualNorm()
1496: .    -ksp_monitor_max    - sets KSPMonitorTrueResidualMaxNorm()
1497: .    -ksp_monitor_lg_residualnorm    - sets line graph monitor,
1498:                            uses KSPMonitorLGResidualNormCreate()
1499: .    -ksp_monitor_lg_true_residualnorm   - sets line graph monitor,
1500:                            uses KSPMonitorLGResidualNormCreate()
1501: .    -ksp_monitor_singular_value    - sets KSPMonitorSingularValue()
1502: -    -ksp_monitor_cancel - cancels all monitors that have
1503:                           been hardwired into a code by
1504:                           calls to KSPMonitorSet(), but
1505:                           does not cancel those set via
1506:                           the options database.

1508:    Notes:
1509:    The default is to do nothing.  To print the residual, or preconditioned
1510:    residual if KSPSetNormType(ksp,KSP_NORM_PRECONDITIONED) was called, use
1511:    KSPMonitorDefault() as the monitoring routine, with a null monitoring
1512:    context.

1514:    Several different monitoring routines may be set by calling
1515:    KSPMonitorSet() multiple times; all will be called in the
1516:    order in which they were set.

1518:    Fortran notes: Only a single monitor function can be set for each KSP object

1520:    Level: beginner

1522: .keywords: KSP, set, monitor

1524: .seealso: KSPMonitorDefault(), KSPMonitorLGResidualNormCreate(), KSPMonitorCancel()
1525: @*/
1526: PetscErrorCode  KSPMonitorSet(KSP ksp,PetscErrorCode (*monitor)(KSP,PetscInt,PetscReal,void*),void *mctx,PetscErrorCode (*monitordestroy)(void**))
1527: {
1528:   PetscInt       i;

1533:   if (ksp->numbermonitors >= MAXKSPMONITORS) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Too many KSP monitors set");
1534:   for (i=0; i<ksp->numbermonitors;i++) {
1535:     if (monitor == ksp->monitor[i] && monitordestroy == ksp->monitordestroy[i] && mctx == ksp->monitorcontext[i]) {
1536:       if (monitordestroy) {
1537:         (*monitordestroy)(&mctx);
1538:       }
1539:       return(0);
1540:     }
1541:   }
1542:   ksp->monitor[ksp->numbermonitors]          = monitor;
1543:   ksp->monitordestroy[ksp->numbermonitors]   = monitordestroy;
1544:   ksp->monitorcontext[ksp->numbermonitors++] = (void*)mctx;
1545:   return(0);
1546: }

1550: /*@
1551:    KSPMonitorCancel - Clears all monitors for a KSP object.

1553:    Logically Collective on KSP

1555:    Input Parameters:
1556: .  ksp - iterative context obtained from KSPCreate()

1558:    Options Database Key:
1559: .  -ksp_monitor_cancel - Cancels all monitors that have
1560:     been hardwired into a code by calls to KSPMonitorSet(),
1561:     but does not cancel those set via the options database.

1563:    Level: intermediate

1565: .keywords: KSP, set, monitor

1567: .seealso: KSPMonitorDefault(), KSPMonitorLGResidualNormCreate(), KSPMonitorSet()
1568: @*/
1569: PetscErrorCode  KSPMonitorCancel(KSP ksp)
1570: {
1572:   PetscInt       i;

1576:   for (i=0; i<ksp->numbermonitors; i++) {
1577:     if (ksp->monitordestroy[i]) {
1578:       (*ksp->monitordestroy[i])(&ksp->monitorcontext[i]);
1579:     }
1580:   }
1581:   ksp->numbermonitors = 0;
1582:   return(0);
1583: }

1587: /*@C
1588:    KSPGetMonitorContext - Gets the monitoring context, as set by
1589:    KSPMonitorSet() for the FIRST monitor only.

1591:    Not Collective

1593:    Input Parameter:
1594: .  ksp - iterative context obtained from KSPCreate()

1596:    Output Parameter:
1597: .  ctx - monitoring context

1599:    Level: intermediate

1601: .keywords: KSP, get, monitor, context

1603: .seealso: KSPMonitorDefault(), KSPMonitorLGResidualNormCreate()
1604: @*/
1605: PetscErrorCode  KSPGetMonitorContext(KSP ksp,void **ctx)
1606: {
1609:   *ctx =      (ksp->monitorcontext[0]);
1610:   return(0);
1611: }

1615: /*@
1616:    KSPSetResidualHistory - Sets the array used to hold the residual history.
1617:    If set, this array will contain the residual norms computed at each
1618:    iteration of the solver.

1620:    Not Collective

1622:    Input Parameters:
1623: +  ksp - iterative context obtained from KSPCreate()
1624: .  a   - array to hold history
1625: .  na  - size of a
1626: -  reset - PETSC_TRUE indicates the history counter is reset to zero
1627:            for each new linear solve

1629:    Level: advanced

1631:    Notes: The array is NOT freed by PETSc so the user needs to keep track of
1632:            it and destroy once the KSP object is destroyed.

1634:    If 'a' is NULL then space is allocated for the history. If 'na' PETSC_DECIDE or PETSC_DEFAULT then a
1635:    default array of length 10000 is allocated.

1637: .keywords: KSP, set, residual, history, norm

1639: .seealso: KSPGetResidualHistory()

1641: @*/
1642: PetscErrorCode  KSPSetResidualHistory(KSP ksp,PetscReal a[],PetscInt na,PetscBool reset)
1643: {


1649:   PetscFree(ksp->res_hist_alloc);
1650:   if (na != PETSC_DECIDE && na != PETSC_DEFAULT && a) {
1651:     ksp->res_hist     = a;
1652:     ksp->res_hist_max = na;
1653:   } else {
1654:     if (na != PETSC_DECIDE && na != PETSC_DEFAULT) ksp->res_hist_max = na;
1655:     else                                           ksp->res_hist_max = 10000; /* like default ksp->max_it */
1656:     PetscMalloc(ksp->res_hist_max*sizeof(PetscReal),&ksp->res_hist_alloc);

1658:     ksp->res_hist = ksp->res_hist_alloc;
1659:   }
1660:   ksp->res_hist_len   = 0;
1661:   ksp->res_hist_reset = reset;
1662:   return(0);
1663: }

1667: /*@C
1668:    KSPGetResidualHistory - Gets the array used to hold the residual history
1669:    and the number of residuals it contains.

1671:    Not Collective

1673:    Input Parameter:
1674: .  ksp - iterative context obtained from KSPCreate()

1676:    Output Parameters:
1677: +  a   - pointer to array to hold history (or NULL)
1678: -  na  - number of used entries in a (or NULL)

1680:    Level: advanced

1682:    Notes:
1683:      Can only be called after a KSPSetResidualHistory() otherwise a and na are set to zero

1685:      The Fortran version of this routine has a calling sequence
1686: $   call KSPGetResidualHistory(KSP ksp, integer na, integer ierr)
1687:     note that you have passed a Fortran array into KSPSetResidualHistory() and you need
1688:     to access the residual values from this Fortran array you provided. Only the na (number of
1689:     residual norms currently held) is set.

1691: .keywords: KSP, get, residual, history, norm

1693: .seealso: KSPGetResidualHistory()

1695: @*/
1696: PetscErrorCode  KSPGetResidualHistory(KSP ksp,PetscReal *a[],PetscInt *na)
1697: {
1700:   if (a) *a = ksp->res_hist;
1701:   if (na) *na = ksp->res_hist_len;
1702:   return(0);
1703: }

1707: /*@C
1708:    KSPSetConvergenceTest - Sets the function to be used to determine
1709:    convergence.

1711:    Logically Collective on KSP

1713:    Input Parameters:
1714: +  ksp - iterative context obtained from KSPCreate()
1715: .  converge - pointer to int function
1716: .  cctx    - context for private data for the convergence routine (may be null)
1717: -  destroy - a routine for destroying the context (may be null)

1719:    Calling sequence of converge:
1720: $     converge (KSP ksp, int it, PetscReal rnorm, KSPConvergedReason *reason,void *mctx)

1722: +  ksp - iterative context obtained from KSPCreate()
1723: .  it - iteration number
1724: .  rnorm - (estimated) 2-norm of (preconditioned) residual
1725: .  reason - the reason why it has converged or diverged
1726: -  cctx  - optional convergence context, as set by KSPSetConvergenceTest()


1729:    Notes:
1730:    Must be called after the KSP type has been set so put this after
1731:    a call to KSPSetType(), or KSPSetFromOptions().

1733:    The default convergence test, KSPDefaultConverged(), aborts if the
1734:    residual grows to more than 10000 times the initial residual.

1736:    The default is a combination of relative and absolute tolerances.
1737:    The residual value that is tested may be an approximation; routines
1738:    that need exact values should compute them.

1740:    In the default PETSc convergence test, the precise values of reason
1741:    are macros such as KSP_CONVERGED_RTOL, which are defined in petscksp.h.

1743:    Level: advanced

1745: .keywords: KSP, set, convergence, test, context

1747: .seealso: KSPDefaultConverged(), KSPGetConvergenceContext(), KSPSetTolerances()
1748: @*/
1749: PetscErrorCode  KSPSetConvergenceTest(KSP ksp,PetscErrorCode (*converge)(KSP,PetscInt,PetscReal,KSPConvergedReason*,void*),void *cctx,PetscErrorCode (*destroy)(void*))
1750: {

1755:   if (ksp->convergeddestroy) {
1756:     (*ksp->convergeddestroy)(ksp->cnvP);
1757:   }
1758:   ksp->converged        = converge;
1759:   ksp->convergeddestroy = destroy;
1760:   ksp->cnvP             = (void*)cctx;
1761:   return(0);
1762: }

1766: /*@C
1767:    KSPGetConvergenceContext - Gets the convergence context set with
1768:    KSPSetConvergenceTest().

1770:    Not Collective

1772:    Input Parameter:
1773: .  ksp - iterative context obtained from KSPCreate()

1775:    Output Parameter:
1776: .  ctx - monitoring context

1778:    Level: advanced

1780: .keywords: KSP, get, convergence, test, context

1782: .seealso: KSPDefaultConverged(), KSPSetConvergenceTest()
1783: @*/
1784: PetscErrorCode  KSPGetConvergenceContext(KSP ksp,void **ctx)
1785: {
1788:   *ctx = ksp->cnvP;
1789:   return(0);
1790: }

1794: /*@C
1795:    KSPBuildSolution - Builds the approximate solution in a vector provided.
1796:    This routine is NOT commonly needed (see KSPSolve()).

1798:    Collective on KSP

1800:    Input Parameter:
1801: .  ctx - iterative context obtained from KSPCreate()

1803:    Output Parameter:
1804:    Provide exactly one of
1805: +  v - location to stash solution.
1806: -  V - the solution is returned in this location. This vector is created
1807:        internally. This vector should NOT be destroyed by the user with
1808:        VecDestroy().

1810:    Notes:
1811:    This routine can be used in one of two ways
1812: .vb
1813:       KSPBuildSolution(ksp,NULL,&V);
1814:    or
1815:       KSPBuildSolution(ksp,v,NULL); or KSPBuildSolution(ksp,v,&v);
1816: .ve
1817:    In the first case an internal vector is allocated to store the solution
1818:    (the user cannot destroy this vector). In the second case the solution
1819:    is generated in the vector that the user provides. Note that for certain
1820:    methods, such as KSPCG, the second case requires a copy of the solution,
1821:    while in the first case the call is essentially free since it simply
1822:    returns the vector where the solution already is stored. For some methods
1823:    like GMRES this is a reasonably expensive operation and should only be
1824:    used in truly needed.

1826:    Level: advanced

1828: .keywords: KSP, build, solution

1830: .seealso: KSPGetSolution(), KSPBuildResidual()
1831: @*/
1832: PetscErrorCode  KSPBuildSolution(KSP ksp,Vec v,Vec *V)
1833: {

1838:   if (!V && !v) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_WRONG,"Must provide either v or V");
1839:   if (!V) V = &v;
1840:   (*ksp->ops->buildsolution)(ksp,v,V);
1841:   return(0);
1842: }

1846: /*@C
1847:    KSPBuildResidual - Builds the residual in a vector provided.

1849:    Collective on KSP

1851:    Input Parameter:
1852: .  ksp - iterative context obtained from KSPCreate()

1854:    Output Parameters:
1855: +  v - optional location to stash residual.  If v is not provided,
1856:        then a location is generated.
1857: .  t - work vector.  If not provided then one is generated.
1858: -  V - the residual

1860:    Notes:
1861:    Regardless of whether or not v is provided, the residual is
1862:    returned in V.

1864:    Level: advanced

1866: .keywords: KSP, build, residual

1868: .seealso: KSPBuildSolution()
1869: @*/
1870: PetscErrorCode  KSPBuildResidual(KSP ksp,Vec t,Vec v,Vec *V)
1871: {
1873:   PetscBool      flag = PETSC_FALSE;
1874:   Vec            w    = v,tt = t;

1878:   if (!w) {
1879:     VecDuplicate(ksp->vec_rhs,&w);
1880:     PetscLogObjectParent((PetscObject)ksp,w);
1881:   }
1882:   if (!tt) {
1883:     VecDuplicate(ksp->vec_sol,&tt); flag = PETSC_TRUE;
1884:     PetscLogObjectParent((PetscObject)ksp,tt);
1885:   }
1886:   (*ksp->ops->buildresidual)(ksp,tt,w,V);
1887:   if (flag) {VecDestroy(&tt);}
1888:   return(0);
1889: }

1893: /*@
1894:    KSPSetDiagonalScale - Tells KSP to symmetrically diagonally scale the system
1895:      before solving. This actually CHANGES the matrix (and right hand side).

1897:    Logically Collective on KSP

1899:    Input Parameter:
1900: +  ksp - the KSP context
1901: -  scale - PETSC_TRUE or PETSC_FALSE

1903:    Options Database Key:
1904: +   -ksp_diagonal_scale -
1905: -   -ksp_diagonal_scale_fix - scale the matrix back AFTER the solve


1908:     Notes: Scales the matrix by  D^(-1/2)  A  D^(-1/2)  [D^(1/2) x ] = D^(-1/2) b
1909:        where D_{ii} is 1/abs(A_{ii}) unless A_{ii} is zero and then it is 1.

1911:     BE CAREFUL with this routine: it actually scales the matrix and right
1912:     hand side that define the system. After the system is solved the matrix
1913:     and right hand side remain scaled unless you use KSPSetDiagonalScaleFix()

1915:     This should NOT be used within the SNES solves if you are using a line
1916:     search.

1918:     If you use this with the PCType Eisenstat preconditioner than you can
1919:     use the PCEisenstatNoDiagonalScaling() option, or -pc_eisenstat_no_diagonal_scaling
1920:     to save some unneeded, redundant flops.

1922:    Level: intermediate

1924: .keywords: KSP, set, options, prefix, database

1926: .seealso: KSPGetDiagonalScale(), KSPSetDiagonalScaleFix()
1927: @*/
1928: PetscErrorCode  KSPSetDiagonalScale(KSP ksp,PetscBool scale)
1929: {
1933:   ksp->dscale = scale;
1934:   return(0);
1935: }

1939: /*@
1940:    KSPGetDiagonalScale - Checks if KSP solver scales the matrix and
1941:                           right hand side

1943:    Not Collective

1945:    Input Parameter:
1946: .  ksp - the KSP context

1948:    Output Parameter:
1949: .  scale - PETSC_TRUE or PETSC_FALSE

1951:    Notes:
1952:     BE CAREFUL with this routine: it actually scales the matrix and right
1953:     hand side that define the system. After the system is solved the matrix
1954:     and right hand side remain scaled  unless you use KSPSetDiagonalScaleFix()

1956:    Level: intermediate

1958: .keywords: KSP, set, options, prefix, database

1960: .seealso: KSPSetDiagonalScale(), KSPSetDiagonalScaleFix()
1961: @*/
1962: PetscErrorCode  KSPGetDiagonalScale(KSP ksp,PetscBool  *scale)
1963: {
1967:   *scale = ksp->dscale;
1968:   return(0);
1969: }

1973: /*@
1974:    KSPSetDiagonalScaleFix - Tells KSP to diagonally scale the system
1975:      back after solving.

1977:    Logically Collective on KSP

1979:    Input Parameter:
1980: +  ksp - the KSP context
1981: -  fix - PETSC_TRUE to scale back after the system solve, PETSC_FALSE to not
1982:          rescale (default)

1984:    Notes:
1985:      Must be called after KSPSetDiagonalScale()

1987:      Using this will slow things down, because it rescales the matrix before and
1988:      after each linear solve. This is intended mainly for testing to allow one
1989:      to easily get back the original system to make sure the solution computed is
1990:      accurate enough.

1992:    Level: intermediate

1994: .keywords: KSP, set, options, prefix, database

1996: .seealso: KSPGetDiagonalScale(), KSPSetDiagonalScale(), KSPGetDiagonalScaleFix()
1997: @*/
1998: PetscErrorCode  KSPSetDiagonalScaleFix(KSP ksp,PetscBool fix)
1999: {
2003:   ksp->dscalefix = fix;
2004:   return(0);
2005: }

2009: /*@
2010:    KSPGetDiagonalScaleFix - Determines if KSP diagonally scales the system
2011:      back after solving.

2013:    Not Collective

2015:    Input Parameter:
2016: .  ksp - the KSP context

2018:    Output Parameter:
2019: .  fix - PETSC_TRUE to scale back after the system solve, PETSC_FALSE to not
2020:          rescale (default)

2022:    Notes:
2023:      Must be called after KSPSetDiagonalScale()

2025:      If PETSC_TRUE will slow things down, because it rescales the matrix before and
2026:      after each linear solve. This is intended mainly for testing to allow one
2027:      to easily get back the original system to make sure the solution computed is
2028:      accurate enough.

2030:    Level: intermediate

2032: .keywords: KSP, set, options, prefix, database

2034: .seealso: KSPGetDiagonalScale(), KSPSetDiagonalScale(), KSPSetDiagonalScaleFix()
2035: @*/
2036: PetscErrorCode  KSPGetDiagonalScaleFix(KSP ksp,PetscBool  *fix)
2037: {
2041:   *fix = ksp->dscalefix;
2042:   return(0);
2043: }

2047: /*@C
2048:    KSPSetComputeOperators - set routine to compute the linear operators

2050:    Logically Collective

2052:    Input Arguments:
2053: +  ksp - the KSP context
2054: .  func - function to compute the operators
2055: -  ctx - optional context

2057:    Calling sequence of func:
2058: $  func(KSP ksp,Mat *A,Mat *B,MatStructure *mstruct,void *ctx)

2060: +  ksp - the KSP context
2061: .  A - the linear operator
2062: .  B - preconditioning matrix
2063: .  mstruct - flag indicating structure, same as in KSPSetOperators(), one of SAME_NONZERO_PATTERN,DIFFERENT_NONZERO_PATTERN,SAME_PRECONDITIONER
2064: -  ctx - optional user-provided context

2066:    Level: beginner

2068: .seealso: KSPSetOperators(), DMKSPSetComputeOperators()
2069: @*/
2070: PetscErrorCode KSPSetComputeOperators(KSP ksp,PetscErrorCode (*func)(KSP,Mat,Mat,MatStructure*,void*),void *ctx)
2071: {
2073:   DM             dm;

2077:   KSPGetDM(ksp,&dm);
2078:   DMKSPSetComputeOperators(dm,func,ctx);
2079:   if (ksp->setupstage == KSP_SETUP_NEWRHS) ksp->setupstage = KSP_SETUP_NEWMATRIX;
2080:   return(0);
2081: }

2085: /*@C
2086:    KSPSetComputeRHS - set routine to compute the right hand side of the linear system

2088:    Logically Collective

2090:    Input Arguments:
2091: +  ksp - the KSP context
2092: .  func - function to compute the right hand side
2093: -  ctx - optional context

2095:    Calling sequence of func:
2096: $  func(KSP ksp,Vec b,void *ctx)

2098: +  ksp - the KSP context
2099: .  b - right hand side of linear system
2100: -  ctx - optional user-provided context

2102:    Level: beginner

2104: .seealso: KSPSolve(), DMKSPSetComputeRHS()
2105: @*/
2106: PetscErrorCode KSPSetComputeRHS(KSP ksp,PetscErrorCode (*func)(KSP,Vec,void*),void *ctx)
2107: {
2109:   DM             dm;

2113:   KSPGetDM(ksp,&dm);
2114:   DMKSPSetComputeRHS(dm,func,ctx);
2115:   return(0);
2116: }

2120: /*@C
2121:    KSPSetComputeInitialGuess - set routine to compute the initial guess of the linear system

2123:    Logically Collective

2125:    Input Arguments:
2126: +  ksp - the KSP context
2127: .  func - function to compute the initial guess
2128: -  ctx - optional context

2130:    Calling sequence of func:
2131: $  func(KSP ksp,Vec x,void *ctx)

2133: +  ksp - the KSP context
2134: .  x - solution vector
2135: -  ctx - optional user-provided context

2137:    Level: beginner

2139: .seealso: KSPSolve(), DMKSPSetComputeInitialGuess()
2140: @*/
2141: PetscErrorCode KSPSetComputeInitialGuess(KSP ksp,PetscErrorCode (*func)(KSP,Vec,void*),void *ctx)
2142: {
2144:   DM             dm;

2148:   KSPGetDM(ksp,&dm);
2149:   DMKSPSetComputeInitialGuess(dm,func,ctx);
2150:   return(0);
2151: }