Actual source code: itfunc.c
petsc-3.8.4 2018-03-24
2: /*
3: Interface KSP routines that the user calls.
4: */
6: #include <petsc/private/kspimpl.h>
7: #include <petscdm.h>
9: /*@
10: KSPComputeExtremeSingularValues - Computes the extreme singular values
11: for the preconditioned operator. Called after or during KSPSolve().
13: Not Collective
15: Input Parameter:
16: . ksp - iterative context obtained from KSPCreate()
18: Output Parameters:
19: . emin, emax - extreme singular values
21: Options Database Keys:
22: . -ksp_compute_singularvalues - compute extreme singular values and print when KSPSolve completes.
24: Notes:
25: One must call KSPSetComputeSingularValues() before calling KSPSetUp()
26: (or use the option -ksp_compute_eigenvalues) in order for this routine to work correctly.
28: Many users may just want to use the monitoring routine
29: KSPMonitorSingularValue() (which can be set with option -ksp_monitor_singular_value)
30: to print the extreme singular values at each iteration of the linear solve.
32: Estimates of the smallest singular value may be very inaccurate, especially if the Krylov method has not converged.
33: The largest singular value is usually accurate to within a few percent if the method has converged, but is still not
34: intended for eigenanalysis.
36: Disable restarts if using KSPGMRES, otherwise this estimate will only be using those iterations after the last
37: restart. See KSPGMRESSetRestart() for more details.
39: Level: advanced
41: .keywords: KSP, compute, extreme, singular, values
43: .seealso: KSPSetComputeSingularValues(), KSPMonitorSingularValue(), KSPComputeEigenvalues()
44: @*/
45: PetscErrorCode KSPComputeExtremeSingularValues(KSP ksp,PetscReal *emax,PetscReal *emin)
46: {
53: if (!ksp->calc_sings) SETERRQ(PetscObjectComm((PetscObject)ksp),4,"Singular values not requested before KSPSetUp()");
55: if (ksp->ops->computeextremesingularvalues) {
56: (*ksp->ops->computeextremesingularvalues)(ksp,emax,emin);
57: } else {
58: *emin = -1.0;
59: *emax = -1.0;
60: }
61: return(0);
62: }
64: /*@
65: KSPComputeEigenvalues - Computes the extreme eigenvalues for the
66: preconditioned operator. Called after or during KSPSolve().
68: Not Collective
70: Input Parameter:
71: + ksp - iterative context obtained from KSPCreate()
72: - n - size of arrays r and c. The number of eigenvalues computed (neig) will, in
73: general, be less than this.
75: Output Parameters:
76: + r - real part of computed eigenvalues, provided by user with a dimension of at least n
77: . c - complex part of computed eigenvalues, provided by user with a dimension of at least n
78: - neig - actual number of eigenvalues computed (will be less than or equal to n)
80: Options Database Keys:
81: + -ksp_compute_eigenvalues - Prints eigenvalues to stdout
82: - -ksp_plot_eigenvalues - Plots eigenvalues in an x-window display
84: Notes:
85: The number of eigenvalues estimated depends on the size of the Krylov space
86: generated during the KSPSolve() ; for example, with
87: CG it corresponds to the number of CG iterations, for GMRES it is the number
88: of GMRES iterations SINCE the last restart. Any extra space in r[] and c[]
89: will be ignored.
91: KSPComputeEigenvalues() does not usually provide accurate estimates; it is
92: intended only for assistance in understanding the convergence of iterative
93: methods, not for eigenanalysis. For accurate computation of eigenvalues we recommend using
94: the excellent package SLEPc.
96: One must call KSPSetComputeEigenvalues() before calling KSPSetUp()
97: in order for this routine to work correctly.
99: Many users may just want to use the monitoring routine
100: KSPMonitorSingularValue() (which can be set with option -ksp_monitor_singular_value)
101: to print the singular values at each iteration of the linear solve.
103: Level: advanced
105: .keywords: KSP, compute, extreme, singular, values
107: .seealso: KSPSetComputeSingularValues(), KSPMonitorSingularValue(), KSPComputeExtremeSingularValues()
108: @*/
109: PetscErrorCode KSPComputeEigenvalues(KSP ksp,PetscInt n,PetscReal r[],PetscReal c[],PetscInt *neig)
110: {
117: if (n<0) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Requested < 0 Eigenvalues");
119: if (!ksp->calc_sings) SETERRQ(PetscObjectComm((PetscObject)ksp),4,"Eigenvalues not requested before KSPSetUp()");
121: if (n && ksp->ops->computeeigenvalues) {
122: (*ksp->ops->computeeigenvalues)(ksp,n,r,c,neig);
123: } else {
124: *neig = 0;
125: }
126: return(0);
127: }
129: /*@
130: KSPComputeRitz - Computes the Ritz or harmonic Ritz pairs associated to the
131: smallest or largest in modulus, for the preconditioned operator.
132: Called after KSPSolve().
134: Not Collective
136: Input Parameter:
137: + ksp - iterative context obtained from KSPCreate()
138: . ritz - PETSC_TRUE or PETSC_FALSE for ritz pairs or harmonic Ritz pairs, respectively
139: . small - PETSC_TRUE or PETSC_FALSE for smallest or largest (harmonic) Ritz values, respectively
140: . nrit - number of (harmonic) Ritz pairs to compute
142: Output Parameters:
143: + nrit - actual number of computed (harmonic) Ritz pairs
144: . S - multidimensional vector with Ritz vectors
145: . tetar - real part of the Ritz values
146: . tetai - imaginary part of the Ritz values
148: Notes:
149: -For GMRES, the (harmonic) Ritz pairs are computed from the Hessenberg matrix obtained during
150: the last complete cycle, or obtained at the end of the solution if the method is stopped before
151: a restart. Then, the number of actual (harmonic) Ritz pairs computed is less or equal to the restart
152: parameter for GMRES if a complete cycle has been performed or less or equal to the number of GMRES
153: iterations.
154: -Moreover, for real matrices, the (harmonic) Ritz pairs are possibly complex-valued. In such a case,
155: the routine selects the complex (harmonic) Ritz value and its conjugate, and two successive columns of S
156: are equal to the real and the imaginary parts of the associated vectors.
157: -the (harmonic) Ritz pairs are given in order of increasing (harmonic) Ritz values in modulus
158: -this is currently not implemented when PETSc is built with complex numbers
160: One must call KSPSetComputeRitz() before calling KSPSetUp()
161: in order for this routine to work correctly.
163: Level: advanced
165: .keywords: KSP, compute, ritz, values
167: .seealso: KSPSetComputeRitz()
168: @*/
169: PetscErrorCode KSPComputeRitz(KSP ksp,PetscBool ritz,PetscBool small,PetscInt *nrit,Vec S[],PetscReal tetar[],PetscReal tetai[])
170: {
175: if (!ksp->calc_ritz) SETERRQ(PetscObjectComm((PetscObject)ksp),4,"Ritz pairs not requested before KSPSetUp()");
176: if (ksp->ops->computeritz) {(*ksp->ops->computeritz)(ksp,ritz,small,nrit,S,tetar,tetai);}
177: return(0);
178: }
179: /*@
180: KSPSetUpOnBlocks - Sets up the preconditioner for each block in
181: the block Jacobi, block Gauss-Seidel, and overlapping Schwarz
182: methods.
184: Collective on KSP
186: Input Parameter:
187: . ksp - the KSP context
189: Notes:
190: KSPSetUpOnBlocks() is a routine that the user can optinally call for
191: more precise profiling (via -log_view) of the setup phase for these
192: block preconditioners. If the user does not call KSPSetUpOnBlocks(),
193: it will automatically be called from within KSPSolve().
195: Calling KSPSetUpOnBlocks() is the same as calling PCSetUpOnBlocks()
196: on the PC context within the KSP context.
198: Level: advanced
200: .keywords: KSP, setup, blocks
202: .seealso: PCSetUpOnBlocks(), KSPSetUp(), PCSetUp()
203: @*/
204: PetscErrorCode KSPSetUpOnBlocks(KSP ksp)
205: {
206: PC pc;
208: PCFailedReason pcreason;
212: KSPGetPC(ksp,&pc);
213: PCSetUpOnBlocks(pc);
214: PCGetSetUpFailedReason(pc,&pcreason);
215: if (pcreason) {
216: ksp->reason = KSP_DIVERGED_PCSETUP_FAILED;
217: }
218: return(0);
219: }
221: /*@
222: KSPSetReusePreconditioner - reuse the current preconditioner, do not construct a new one even if the operator changes
224: Collective on KSP
226: Input Parameters:
227: + ksp - iterative context obtained from KSPCreate()
228: - flag - PETSC_TRUE to reuse the current preconditioner
230: Level: intermediate
232: .keywords: KSP, setup
234: .seealso: KSPCreate(), KSPSolve(), KSPDestroy(), PCSetReusePreconditioner()
235: @*/
236: PetscErrorCode KSPSetReusePreconditioner(KSP ksp,PetscBool flag)
237: {
238: PC pc;
243: KSPGetPC(ksp,&pc);
244: PCSetReusePreconditioner(pc,flag);
245: return(0);
246: }
248: /*@
249: KSPSetSkipPCSetFromOptions - prevents KSPSetFromOptions() from call PCSetFromOptions(). This is used if the same PC is shared by more than one KSP so its options are not resetable for each KSP
251: Collective on KSP
253: Input Parameters:
254: + ksp - iterative context obtained from KSPCreate()
255: - flag - PETSC_TRUE to skip calling the PCSetFromOptions()
257: Level: intermediate
259: .keywords: KSP, setup
261: .seealso: KSPCreate(), KSPSolve(), KSPDestroy(), PCSetReusePreconditioner()
262: @*/
263: PetscErrorCode KSPSetSkipPCSetFromOptions(KSP ksp,PetscBool flag)
264: {
267: ksp->skippcsetfromoptions = flag;
268: return(0);
269: }
271: /*@
272: KSPSetUp - Sets up the internal data structures for the
273: later use of an iterative solver.
275: Collective on KSP
277: Input Parameter:
278: . ksp - iterative context obtained from KSPCreate()
280: Level: developer
282: .keywords: KSP, setup
284: .seealso: KSPCreate(), KSPSolve(), KSPDestroy()
285: @*/
286: PetscErrorCode KSPSetUp(KSP ksp)
287: {
289: Mat A,B;
290: Mat mat,pmat;
291: MatNullSpace nullsp;
292: PCFailedReason pcreason;
293:
297: /* reset the convergence flag from the previous solves */
298: ksp->reason = KSP_CONVERGED_ITERATING;
300: if (!((PetscObject)ksp)->type_name) {
301: KSPSetType(ksp,KSPGMRES);
302: }
303: KSPSetUpNorms_Private(ksp,PETSC_TRUE,&ksp->normtype,&ksp->pc_side);
305: if (ksp->dmActive && !ksp->setupstage) {
306: /* first time in so build matrix and vector data structures using DM */
307: if (!ksp->vec_rhs) {DMCreateGlobalVector(ksp->dm,&ksp->vec_rhs);}
308: if (!ksp->vec_sol) {DMCreateGlobalVector(ksp->dm,&ksp->vec_sol);}
309: DMCreateMatrix(ksp->dm,&A);
310: KSPSetOperators(ksp,A,A);
311: PetscObjectDereference((PetscObject)A);
312: }
314: if (ksp->dmActive) {
315: DMKSP kdm;
316: DMGetDMKSP(ksp->dm,&kdm);
318: if (kdm->ops->computeinitialguess && ksp->setupstage != KSP_SETUP_NEWRHS) {
319: /* only computes initial guess the first time through */
320: (*kdm->ops->computeinitialguess)(ksp,ksp->vec_sol,kdm->initialguessctx);
321: KSPSetInitialGuessNonzero(ksp,PETSC_TRUE);
322: }
323: if (kdm->ops->computerhs) {
324: (*kdm->ops->computerhs)(ksp,ksp->vec_rhs,kdm->rhsctx);
325: }
327: if (ksp->setupstage != KSP_SETUP_NEWRHS) {
328: if (kdm->ops->computeoperators) {
329: KSPGetOperators(ksp,&A,&B);
330: (*kdm->ops->computeoperators)(ksp,A,B,kdm->operatorsctx);
331: } else SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_WRONGSTATE,"You called KSPSetDM() but did not use DMKSPSetComputeOperators() or KSPSetDMActive(ksp,PETSC_FALSE);");
332: }
333: }
335: if (ksp->setupstage == KSP_SETUP_NEWRHS) return(0);
336: PetscLogEventBegin(KSP_SetUp,ksp,ksp->vec_rhs,ksp->vec_sol,0);
338: switch (ksp->setupstage) {
339: case KSP_SETUP_NEW:
340: (*ksp->ops->setup)(ksp);
341: break;
342: case KSP_SETUP_NEWMATRIX: { /* This should be replaced with a more general mechanism */
343: if (ksp->setupnewmatrix) {
344: (*ksp->ops->setup)(ksp);
345: }
346: } break;
347: default: break;
348: }
350: if (!ksp->pc) {KSPGetPC(ksp,&ksp->pc);}
351: PCGetOperators(ksp->pc,&mat,&pmat);
352: /* scale the matrix if requested */
353: if (ksp->dscale) {
354: PetscScalar *xx;
355: PetscInt i,n;
356: PetscBool zeroflag = PETSC_FALSE;
357: if (!ksp->pc) {KSPGetPC(ksp,&ksp->pc);}
358: if (!ksp->diagonal) { /* allocate vector to hold diagonal */
359: MatCreateVecs(pmat,&ksp->diagonal,0);
360: }
361: MatGetDiagonal(pmat,ksp->diagonal);
362: VecGetLocalSize(ksp->diagonal,&n);
363: VecGetArray(ksp->diagonal,&xx);
364: for (i=0; i<n; i++) {
365: if (xx[i] != 0.0) xx[i] = 1.0/PetscSqrtReal(PetscAbsScalar(xx[i]));
366: else {
367: xx[i] = 1.0;
368: zeroflag = PETSC_TRUE;
369: }
370: }
371: VecRestoreArray(ksp->diagonal,&xx);
372: if (zeroflag) {
373: PetscInfo(ksp,"Zero detected in diagonal of matrix, using 1 at those locations\n");
374: }
375: MatDiagonalScale(pmat,ksp->diagonal,ksp->diagonal);
376: if (mat != pmat) {MatDiagonalScale(mat,ksp->diagonal,ksp->diagonal);}
377: ksp->dscalefix2 = PETSC_FALSE;
378: }
379: PetscLogEventEnd(KSP_SetUp,ksp,ksp->vec_rhs,ksp->vec_sol,0);
380: PCSetErrorIfFailure(ksp->pc,ksp->errorifnotconverged);
381: PCSetUp(ksp->pc);
382: PCGetSetUpFailedReason(ksp->pc,&pcreason);
383: if (pcreason) {
384: ksp->reason = KSP_DIVERGED_PCSETUP_FAILED;
385: }
387: MatGetNullSpace(mat,&nullsp);
388: if (nullsp) {
389: PetscBool test = PETSC_FALSE;
390: PetscOptionsGetBool(((PetscObject)ksp)->options,((PetscObject)ksp)->prefix,"-ksp_test_null_space",&test,NULL);
391: if (test) {
392: MatNullSpaceTest(nullsp,mat,NULL);
393: }
394: }
395: ksp->setupstage = KSP_SETUP_NEWRHS;
396: return(0);
397: }
399: /*@
400: KSPReasonView - Displays the reason a KSP solve converged or diverged to a viewer
402: Collective on KSP
404: Parameter:
405: + ksp - iterative context obtained from KSPCreate()
406: - viewer - the viewer to display the reason
409: Options Database Keys:
410: . -ksp_converged_reason - print reason for converged or diverged, also prints number of iterations
412: Level: beginner
414: .keywords: KSP, solve, linear system
416: .seealso: KSPCreate(), KSPSetUp(), KSPDestroy(), KSPSetTolerances(), KSPConvergedDefault(),
417: KSPSolveTranspose(), KSPGetIterationNumber()
418: @*/
419: PetscErrorCode KSPReasonView(KSP ksp,PetscViewer viewer)
420: {
422: PetscBool isAscii;
425: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isAscii);
426: if (isAscii) {
427: PetscViewerASCIIAddTab(viewer,((PetscObject)ksp)->tablevel);
428: if (ksp->reason > 0) {
429: if (((PetscObject) ksp)->prefix) {
430: PetscViewerASCIIPrintf(viewer,"Linear %s solve converged due to %s iterations %D\n",((PetscObject) ksp)->prefix,KSPConvergedReasons[ksp->reason],ksp->its);
431: } else {
432: PetscViewerASCIIPrintf(viewer,"Linear solve converged due to %s iterations %D\n",KSPConvergedReasons[ksp->reason],ksp->its);
433: }
434: } else {
435: if (((PetscObject) ksp)->prefix) {
436: PetscViewerASCIIPrintf(viewer,"Linear %s solve did not converge due to %s iterations %D\n",((PetscObject) ksp)->prefix,KSPConvergedReasons[ksp->reason],ksp->its);
437: } else {
438: PetscViewerASCIIPrintf(viewer,"Linear solve did not converge due to %s iterations %D\n",KSPConvergedReasons[ksp->reason],ksp->its);
439: }
440: if (ksp->reason == KSP_DIVERGED_PCSETUP_FAILED) {
441: PCFailedReason reason;
442: PCGetSetUpFailedReason(ksp->pc,&reason);
443: PetscViewerASCIIPrintf(viewer," PCSETUP_FAILED due to %s \n",PCFailedReasons[reason]);
444: }
445: }
446: PetscViewerASCIISubtractTab(viewer,((PetscObject)ksp)->tablevel);
447: }
448: return(0);
449: }
451: #if defined(PETSC_HAVE_THREADSAFETY)
452: #define KSPReasonViewFromOptions KSPReasonViewFromOptionsUnsafe
453: #else
454: #endif
455: /*@C
456: KSPReasonViewFromOptions - Processes command line options to determine if/how a KSPReason is to be viewed.
458: Collective on KSP
460: Input Parameters:
461: . ksp - the KSP object
463: Level: intermediate
465: @*/
466: PetscErrorCode KSPReasonViewFromOptions(KSP ksp)
467: {
468: PetscErrorCode ierr;
469: PetscViewer viewer;
470: PetscBool flg;
471: PetscViewerFormat format;
474: PetscOptionsGetViewer(PetscObjectComm((PetscObject)ksp),((PetscObject)ksp)->prefix,"-ksp_converged_reason",&viewer,&format,&flg);
475: if (flg) {
476: PetscViewerPushFormat(viewer,format);
477: KSPReasonView(ksp,viewer);
478: PetscViewerPopFormat(viewer);
479: PetscViewerDestroy(&viewer);
480: }
481: return(0);
482: }
484: #include <petscdraw.h>
485: /*@C
486: KSPSolve - Solves linear system.
488: Collective on KSP
490: Parameter:
491: + ksp - iterative context obtained from KSPCreate()
492: . b - the right hand side vector
493: - x - the solution (this may be the same vector as b, then b will be overwritten with answer)
495: Options Database Keys:
496: + -ksp_compute_eigenvalues - compute preconditioned operators eigenvalues
497: . -ksp_plot_eigenvalues - plot the computed eigenvalues in an X-window
498: . -ksp_plot_eigencontours - plot the computed eigenvalues in an X-window with contours
499: . -ksp_compute_eigenvalues_explicitly - compute the eigenvalues by forming the dense operator and using LAPACK
500: . -ksp_plot_eigenvalues_explicitly - plot the explicitly computing eigenvalues
501: . -ksp_view_mat binary - save matrix to the default binary viewer
502: . -ksp_view_pmat binary - save matrix used to build preconditioner to the default binary viewer
503: . -ksp_view_rhs binary - save right hand side vector to the default binary viewer
504: . -ksp_view_solution binary - save computed solution vector to the default binary viewer
505: (can be read later with src/ksp/examples/tutorials/ex10.c for testing solvers)
506: . -ksp_view_mat_explicit - for matrix-free operators, computes the matrix entries and views them
507: . -ksp_view_preconditioned_operator_explicit - computes the product of the preconditioner and matrix as an explicit matrix and views it
508: . -ksp_converged_reason - print reason for converged or diverged, also prints number of iterations
509: . -ksp_final_residual - print 2-norm of true linear system residual at the end of the solution process
510: - -ksp_view - print the ksp data structure at the end of the system solution
512: Notes:
514: If one uses KSPSetDM() then x or b need not be passed. Use KSPGetSolution() to access the solution in this case.
516: The operator is specified with KSPSetOperators().
518: Call KSPGetConvergedReason() to determine if the solver converged or failed and
519: why. The number of iterations can be obtained from KSPGetIterationNumber().
521: If you provide a matrix that has a MatSetNullSpace() and MatSetTransposeNullSpace() this will use that information to solve singular systems
522: in the least squares sense with a norm minimizing solution.
523: $
524: $ A x = b where b = b_p + b_t where b_t is not in the range of A (and hence by the fundamental theorem of linear algebra is in the nullspace(A') see MatSetNullSpace()
525: $
526: $ KSP first removes b_t producing the linear system A x = b_p (which has multiple solutions) and solves this to find the ||x|| minimizing solution (and hence
527: $ it finds the solution x orthogonal to the nullspace(A). The algorithm is simply in each iteration of the Krylov method we remove the nullspace(A) from the search
528: $ direction thus the solution which is a linear combination of the search directions has no component in the nullspace(A).
529: $
530: $ We recommend always using GMRES for such singular systems.
531: $ If nullspace(A) = nullspace(A') (note symmetric matrices always satisfy this property) then both left and right preconditioning will work
532: $ If nullspace(A) != nullspace(A') then left preconditioning will work but right preconditioning may not work (or it may).
534: Developer Note: The reason we cannot always solve nullspace(A) != nullspace(A') systems with right preconditioning is because we need to remove at each iteration
535: the nullspace(AB) from the search direction. While we know the nullspace(A) the nullspace(AB) equals B^-1 times the nullspace(A) but except for trivial preconditioners
536: such as diagonal scaling we cannot apply the inverse of the preconditioner to a vector and thus cannot compute the nullspace(AB).
539: If using a direct method (e.g., via the KSP solver
540: KSPPREONLY and a preconditioner such as PCLU/PCILU),
541: then its=1. See KSPSetTolerances() and KSPConvergedDefault()
542: for more details.
544: Understanding Convergence:
545: The routines KSPMonitorSet(), KSPComputeEigenvalues(), and
546: KSPComputeEigenvaluesExplicitly() provide information on additional
547: options to monitor convergence and print eigenvalue information.
549: Level: beginner
551: .keywords: KSP, solve, linear system
553: .seealso: KSPCreate(), KSPSetUp(), KSPDestroy(), KSPSetTolerances(), KSPConvergedDefault(),
554: KSPSolveTranspose(), KSPGetIterationNumber(), MatNullSpaceCreate(), MatSetNullSpace(), MatSetTransposeNullSpace()
555: @*/
556: PetscErrorCode KSPSolve(KSP ksp,Vec b,Vec x)
557: {
558: PetscErrorCode ierr;
559: PetscBool flag1,flag2,flag3,flg = PETSC_FALSE,inXisinB=PETSC_FALSE,guess_zero;
560: Mat mat,pmat;
561: MPI_Comm comm;
562: MatNullSpace nullsp;
563: Vec btmp,vec_rhs=0;
569: comm = PetscObjectComm((PetscObject)ksp);
570: if (x && x == b) {
571: if (!ksp->guess_zero) SETERRQ(comm,PETSC_ERR_ARG_INCOMP,"Cannot use x == b with nonzero initial guess");
572: VecDuplicate(b,&x);
573: inXisinB = PETSC_TRUE;
574: }
575: if (b) {
576: PetscObjectReference((PetscObject)b);
577: VecDestroy(&ksp->vec_rhs);
578: ksp->vec_rhs = b;
579: }
580: if (x) {
581: PetscObjectReference((PetscObject)x);
582: VecDestroy(&ksp->vec_sol);
583: ksp->vec_sol = x;
584: }
585: KSPViewFromOptions(ksp,NULL,"-ksp_view_pre");
587: if (ksp->presolve) {
588: (*ksp->presolve)(ksp,ksp->vec_rhs,ksp->vec_sol,ksp->prectx);
589: }
590: PetscLogEventBegin(KSP_Solve,ksp,ksp->vec_rhs,ksp->vec_sol,0);
592: /* reset the residual history list if requested */
593: if (ksp->res_hist_reset) ksp->res_hist_len = 0;
594: ksp->transpose_solve = PETSC_FALSE;
596: if (ksp->guess) {
597: PetscObjectState ostate,state;
599: KSPGuessSetUp(ksp->guess);
600: PetscObjectStateGet((PetscObject)ksp->vec_sol,&ostate);
601: KSPGuessFormGuess(ksp->guess,ksp->vec_rhs,ksp->vec_sol);
602: PetscObjectStateGet((PetscObject)ksp->vec_sol,&state);
603: if (state != ostate) {
604: ksp->guess_zero = PETSC_FALSE;
605: } else {
606: PetscInfo(ksp,"Using zero initial guess since the KSPGuess object did not change the vector\n");
607: ksp->guess_zero = PETSC_TRUE;
608: }
609: }
611: /* KSPSetUp() scales the matrix if needed */
612: KSPSetUp(ksp);
613: KSPSetUpOnBlocks(ksp);
615: VecLocked(ksp->vec_sol,3);
617: PCGetOperators(ksp->pc,&mat,&pmat);
618: /* diagonal scale RHS if called for */
619: if (ksp->dscale) {
620: VecPointwiseMult(ksp->vec_rhs,ksp->vec_rhs,ksp->diagonal);
621: /* second time in, but matrix was scaled back to original */
622: if (ksp->dscalefix && ksp->dscalefix2) {
623: Mat mat,pmat;
625: PCGetOperators(ksp->pc,&mat,&pmat);
626: MatDiagonalScale(pmat,ksp->diagonal,ksp->diagonal);
627: if (mat != pmat) {MatDiagonalScale(mat,ksp->diagonal,ksp->diagonal);}
628: }
630: /* scale initial guess */
631: if (!ksp->guess_zero) {
632: if (!ksp->truediagonal) {
633: VecDuplicate(ksp->diagonal,&ksp->truediagonal);
634: VecCopy(ksp->diagonal,ksp->truediagonal);
635: VecReciprocal(ksp->truediagonal);
636: }
637: VecPointwiseMult(ksp->vec_sol,ksp->vec_sol,ksp->truediagonal);
638: }
639: }
640: PCPreSolve(ksp->pc,ksp);
642: if (ksp->guess_zero) { VecSet(ksp->vec_sol,0.0);}
643: if (ksp->guess_knoll) { /* The Knoll trick is independent on the KSPGuess specified */
644: PCApply(ksp->pc,ksp->vec_rhs,ksp->vec_sol);
645: KSP_RemoveNullSpace(ksp,ksp->vec_sol);
646: ksp->guess_zero = PETSC_FALSE;
647: }
649: /* can we mark the initial guess as zero for this solve? */
650: guess_zero = ksp->guess_zero;
651: if (!ksp->guess_zero) {
652: PetscReal norm;
654: VecNormAvailable(ksp->vec_sol,NORM_2,&flg,&norm);
655: if (flg && !norm) ksp->guess_zero = PETSC_TRUE;
656: }
657: MatGetTransposeNullSpace(pmat,&nullsp);
658: if (nullsp) {
659: VecDuplicate(ksp->vec_rhs,&btmp);
660: VecCopy(ksp->vec_rhs,btmp);
661: MatNullSpaceRemove(nullsp,btmp);
662: vec_rhs = ksp->vec_rhs;
663: ksp->vec_rhs = btmp;
664: }
665: VecLockPush(ksp->vec_rhs);
666: if (ksp->reason == KSP_DIVERGED_PCSETUP_FAILED) {
667: VecSetInf(ksp->vec_sol);
668: }
669: (*ksp->ops->solve)(ksp);
670:
671: VecLockPop(ksp->vec_rhs);
672: if (nullsp) {
673: ksp->vec_rhs = vec_rhs;
674: VecDestroy(&btmp);
675: }
677: ksp->guess_zero = guess_zero;
680: if (!ksp->reason) SETERRQ(comm,PETSC_ERR_PLIB,"Internal error, solver returned without setting converged reason");
681: ksp->totalits += ksp->its;
683: KSPReasonViewFromOptions(ksp);
684: PCPostSolve(ksp->pc,ksp);
686: /* diagonal scale solution if called for */
687: if (ksp->dscale) {
688: VecPointwiseMult(ksp->vec_sol,ksp->vec_sol,ksp->diagonal);
689: /* unscale right hand side and matrix */
690: if (ksp->dscalefix) {
691: Mat mat,pmat;
693: VecReciprocal(ksp->diagonal);
694: VecPointwiseMult(ksp->vec_rhs,ksp->vec_rhs,ksp->diagonal);
695: PCGetOperators(ksp->pc,&mat,&pmat);
696: MatDiagonalScale(pmat,ksp->diagonal,ksp->diagonal);
697: if (mat != pmat) {MatDiagonalScale(mat,ksp->diagonal,ksp->diagonal);}
698: VecReciprocal(ksp->diagonal);
699: ksp->dscalefix2 = PETSC_TRUE;
700: }
701: }
702: PetscLogEventEnd(KSP_Solve,ksp,ksp->vec_rhs,ksp->vec_sol,0);
703: if (ksp->postsolve) {
704: (*ksp->postsolve)(ksp,ksp->vec_rhs,ksp->vec_sol,ksp->postctx);
705: }
706: if (ksp->guess) {
707: KSPGuessUpdate(ksp->guess,ksp->vec_rhs,ksp->vec_sol);
708: }
710: PCGetOperators(ksp->pc,&mat,&pmat);
711: MatViewFromOptions(mat,(PetscObject)ksp,"-ksp_view_mat");
712: MatViewFromOptions(pmat,(PetscObject)ksp,"-ksp_view_pmat");
713: VecViewFromOptions(ksp->vec_rhs,(PetscObject)ksp,"-ksp_view_rhs");
715: PetscOptionsGetViewer(PetscObjectComm((PetscObject)ksp),((PetscObject)ksp)->prefix,"-ksp_compute_eigenvalues",NULL,NULL,&flag1);
716: PetscOptionsGetViewer(PetscObjectComm((PetscObject)ksp),((PetscObject)ksp)->prefix,"-ksp_plot_eigenvalues",NULL,NULL,&flag2);
717: PetscOptionsGetViewer(PetscObjectComm((PetscObject)ksp),((PetscObject)ksp)->prefix,"-ksp_plot_eigencontours",NULL,NULL,&flag3);
718: if (flag1 || flag2 || flag3) {
719: PetscInt nits,n,i,neig;
720: PetscReal *r,*c;
722: KSPGetIterationNumber(ksp,&nits);
723: n = nits+2;
725: if (!nits) {
726: PetscPrintf(comm,"Zero iterations in solver, cannot approximate any eigenvalues\n");
727: } else {
728: PetscMPIInt rank;
729: MPI_Comm_rank(comm,&rank);
730: PetscMalloc2(n,&r,n,&c);
731: KSPComputeEigenvalues(ksp,n,r,c,&neig);
732: if (flag1) {
733: PetscPrintf(comm,"Iteratively computed eigenvalues\n");
734: for (i=0; i<neig; i++) {
735: if (c[i] >= 0.0) {
736: PetscPrintf(comm,"%g + %gi\n",(double)r[i],(double)c[i]);
737: } else {
738: PetscPrintf(comm,"%g - %gi\n",(double)r[i],-(double)c[i]);
739: }
740: }
741: }
742: if (flag2 && !rank) {
743: PetscDraw draw;
744: PetscDrawSP drawsp;
746: if (!ksp->eigviewer) {
747: PetscViewerDrawOpen(PETSC_COMM_SELF,0,"Iteratively Computed Eigenvalues",PETSC_DECIDE,PETSC_DECIDE,400,400,&ksp->eigviewer);
748: }
749: PetscViewerDrawGetDraw(ksp->eigviewer,0,&draw);
750: PetscDrawSPCreate(draw,1,&drawsp);
751: for (i=0; i<neig; i++) {
752: PetscDrawSPAddPoint(drawsp,r+i,c+i);
753: }
754: PetscDrawSPDraw(drawsp,PETSC_TRUE);
755: PetscDrawSPSave(drawsp);
756: PetscDrawSPDestroy(&drawsp);
757: }
758: if (flag3 && !rank) {
759: KSPPlotEigenContours_Private(ksp,neig,r,c);
760: }
761: PetscFree2(r,c);
762: }
763: }
765: PetscOptionsGetViewer(PetscObjectComm((PetscObject)ksp),((PetscObject)ksp)->prefix,"-ksp_compute_singularvalues",NULL,NULL,&flag1);
766: if (flag1) {
767: PetscInt nits;
769: KSPGetIterationNumber(ksp,&nits);
770: if (!nits) {
771: PetscPrintf(comm,"Zero iterations in solver, cannot approximate any singular values\n");
772: } else {
773: PetscReal emax,emin;
775: KSPComputeExtremeSingularValues(ksp,&emax,&emin);
776: PetscPrintf(comm,"Iteratively computed extreme singular values: max %g min %g max/min %g\n",(double)emax,(double)emin,(double)(emax/emin));
777: }
778: }
780: PetscOptionsGetViewer(PetscObjectComm((PetscObject)ksp),((PetscObject)ksp)->prefix,"-ksp_compute_eigenvalues_explicitly",NULL,NULL,&flag1);
781: PetscOptionsGetViewer(PetscObjectComm((PetscObject)ksp),((PetscObject)ksp)->prefix,"-ksp_plot_eigenvalues_explicitly",NULL,NULL,&flag2);
782: if (flag1 || flag2) {
783: PetscInt n,i;
784: PetscReal *r,*c;
785: PetscMPIInt rank;
786: MPI_Comm_rank(comm,&rank);
787: VecGetSize(ksp->vec_sol,&n);
788: PetscMalloc2(n,&r,n,&c);
789: KSPComputeEigenvaluesExplicitly(ksp,n,r,c);
790: if (flag1) {
791: PetscPrintf(comm,"Explicitly computed eigenvalues\n");
792: for (i=0; i<n; i++) {
793: if (c[i] >= 0.0) {
794: PetscPrintf(comm,"%g + %gi\n",(double)r[i],(double)c[i]);
795: } else {
796: PetscPrintf(comm,"%g - %gi\n",(double)r[i],-(double)c[i]);
797: }
798: }
799: }
800: if (flag2 && !rank) {
801: PetscDraw draw;
802: PetscDrawSP drawsp;
804: if (!ksp->eigviewer) {
805: PetscViewerDrawOpen(PETSC_COMM_SELF,0,"Explicitly Computed Eigenvalues",PETSC_DECIDE,PETSC_DECIDE,400,400,&ksp->eigviewer);
806: }
807: PetscViewerDrawGetDraw(ksp->eigviewer,0,&draw);
808: PetscDrawSPCreate(draw,1,&drawsp);
809: PetscDrawSPReset(drawsp);
810: for (i=0; i<n; i++) {
811: PetscDrawSPAddPoint(drawsp,r+i,c+i);
812: }
813: PetscDrawSPDraw(drawsp,PETSC_TRUE);
814: PetscDrawSPSave(drawsp);
815: PetscDrawSPDestroy(&drawsp);
816: }
817: PetscFree2(r,c);
818: }
820: PetscOptionsGetViewer(PetscObjectComm((PetscObject)ksp),((PetscObject)ksp)->prefix,"-ksp_view_mat_explicit",NULL,NULL,&flag2);
821: if (flag2) {
822: Mat A,B;
823: PCGetOperators(ksp->pc,&A,NULL);
824: MatComputeExplicitOperator(A,&B);
825: MatViewFromOptions(B,(PetscObject)ksp,"-ksp_view_mat_explicit");
826: MatDestroy(&B);
827: }
828: PetscOptionsGetViewer(PetscObjectComm((PetscObject)ksp),((PetscObject)ksp)->prefix,"-ksp_view_preconditioned_operator_explicit",NULL,NULL,&flag2);
829: if (flag2) {
830: Mat B;
831: KSPComputeExplicitOperator(ksp,&B);
832: MatViewFromOptions(B,(PetscObject)ksp,"-ksp_view_preconditioned_operator_explicit");
833: MatDestroy(&B);
834: }
835: KSPViewFromOptions(ksp,NULL,"-ksp_view");
837: PetscOptionsGetViewer(PetscObjectComm((PetscObject)ksp),((PetscObject)ksp)->prefix,"-ksp_final_residual",NULL,NULL,&flg);
838: if (flg) {
839: Mat A;
840: Vec t;
841: PetscReal norm;
842: if (ksp->dscale && !ksp->dscalefix) SETERRQ(comm,PETSC_ERR_ARG_WRONGSTATE,"Cannot compute final scale with -ksp_diagonal_scale except also with -ksp_diagonal_scale_fix");
843: PCGetOperators(ksp->pc,&A,NULL);
844: VecDuplicate(ksp->vec_rhs,&t);
845: KSP_MatMult(ksp,A,ksp->vec_sol,t);
846: VecAYPX(t, -1.0, ksp->vec_rhs);
847: VecNorm(t,NORM_2,&norm);
848: VecDestroy(&t);
849: PetscPrintf(comm,"KSP final norm of residual %g\n",(double)norm);
850: }
851: VecViewFromOptions(ksp->vec_sol,(PetscObject)ksp,"-ksp_view_solution");
853: if (inXisinB) {
854: VecCopy(x,b);
855: VecDestroy(&x);
856: }
857: PetscObjectSAWsBlock((PetscObject)ksp);
858: if (ksp->errorifnotconverged && ksp->reason < 0) SETERRQ(comm,PETSC_ERR_NOT_CONVERGED,"KSPSolve has not converged");
859: return(0);
860: }
862: /*@
863: KSPSolveTranspose - Solves the transpose of a linear system.
865: Collective on KSP
867: Input Parameter:
868: + ksp - iterative context obtained from KSPCreate()
869: . b - right hand side vector
870: - x - solution vector
872: Notes: For complex numbers this solve the non-Hermitian transpose system.
874: This currently does NOT correctly use the null space of the operator and its transpose for solving singular systems.
876: Developer Notes: We need to implement a KSPSolveHermitianTranspose()
878: Level: developer
880: .keywords: KSP, solve, linear system
882: .seealso: KSPCreate(), KSPSetUp(), KSPDestroy(), KSPSetTolerances(), KSPConvergedDefault(),
883: KSPSolve()
884: @*/
886: PetscErrorCode KSPSolveTranspose(KSP ksp,Vec b,Vec x)
887: {
889: PetscBool inXisinB=PETSC_FALSE;
890: Vec vec_rhs = 0,btmp;
891: Mat mat,pmat;
892: MatNullSpace nullsp;
898: if (x == b) {
899: VecDuplicate(b,&x);
900: inXisinB = PETSC_TRUE;
901: }
902: PetscObjectReference((PetscObject)b);
903: PetscObjectReference((PetscObject)x);
904: VecDestroy(&ksp->vec_rhs);
905: VecDestroy(&ksp->vec_sol);
907: ksp->vec_rhs = b;
908: ksp->vec_sol = x;
909: ksp->transpose_solve = PETSC_TRUE;
911: KSPSetUp(ksp);
912: KSPSetUpOnBlocks(ksp);
913: if (ksp->guess_zero) { VecSet(ksp->vec_sol,0.0);}
915: PCGetOperators(ksp->pc,&mat,&pmat);
916: MatGetNullSpace(pmat,&nullsp);
917: if (nullsp) {
918: VecDuplicate(ksp->vec_rhs,&btmp);
919: VecCopy(ksp->vec_rhs,btmp);
920: MatNullSpaceRemove(nullsp,btmp);
921: vec_rhs = ksp->vec_rhs;
922: ksp->vec_rhs = btmp;
923: }
925: (*ksp->ops->solve)(ksp);
926: if (nullsp) {
927: ksp->vec_rhs = vec_rhs;
928: VecDestroy(&btmp);
929: }
930: if (!ksp->reason) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_PLIB,"Internal error, solver returned without setting converged reason");
931: KSPReasonViewFromOptions(ksp);
933: MatViewFromOptions(mat,(PetscObject)ksp,"-ksp_view_mat");
934: MatViewFromOptions(pmat,(PetscObject)ksp,"-ksp_view_pmat");
935: VecViewFromOptions(ksp->vec_rhs,(PetscObject)ksp,"-ksp_view_rhs");
936: VecViewFromOptions(ksp->vec_sol,(PetscObject)ksp,"-ksp_view_solution");
938: if (inXisinB) {
939: VecCopy(x,b);
940: VecDestroy(&x);
941: }
942: if (ksp->errorifnotconverged && ksp->reason < 0) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_NOT_CONVERGED,"KSPSolve has not converged");
943: return(0);
944: }
946: /*@
947: KSPReset - Resets a KSP context to the kspsetupcalled = 0 state and removes any allocated Vecs and Mats
949: Collective on KSP
951: Input Parameter:
952: . ksp - iterative context obtained from KSPCreate()
954: Level: beginner
956: .keywords: KSP, destroy
958: .seealso: KSPCreate(), KSPSetUp(), KSPSolve()
959: @*/
960: PetscErrorCode KSPReset(KSP ksp)
961: {
966: if (!ksp) return(0);
967: if (ksp->ops->reset) {
968: (*ksp->ops->reset)(ksp);
969: }
970: if (ksp->pc) {PCReset(ksp->pc);}
971: if (ksp->guess) {
972: KSPGuess guess = ksp->guess;
973: if (guess->ops->reset) { (*guess->ops->reset)(guess); }
974: }
975: VecDestroyVecs(ksp->nwork,&ksp->work);
976: VecDestroy(&ksp->vec_rhs);
977: VecDestroy(&ksp->vec_sol);
978: VecDestroy(&ksp->diagonal);
979: VecDestroy(&ksp->truediagonal);
981: ksp->setupstage = KSP_SETUP_NEW;
982: return(0);
983: }
985: /*@
986: KSPDestroy - Destroys KSP context.
988: Collective on KSP
990: Input Parameter:
991: . ksp - iterative context obtained from KSPCreate()
993: Level: beginner
995: .keywords: KSP, destroy
997: .seealso: KSPCreate(), KSPSetUp(), KSPSolve()
998: @*/
999: PetscErrorCode KSPDestroy(KSP *ksp)
1000: {
1002: PC pc;
1005: if (!*ksp) return(0);
1007: if (--((PetscObject)(*ksp))->refct > 0) {*ksp = 0; return(0);}
1009: PetscObjectSAWsViewOff((PetscObject)*ksp);
1010: /*
1011: Avoid a cascading call to PCReset(ksp->pc) from the following call:
1012: PCReset() shouldn't be called from KSPDestroy() as it is unprotected by pc's
1013: refcount (and may be shared, e.g., by other ksps).
1014: */
1015: pc = (*ksp)->pc;
1016: (*ksp)->pc = NULL;
1017: KSPReset((*ksp));
1018: (*ksp)->pc = pc;
1019: if ((*ksp)->ops->destroy) {(*(*ksp)->ops->destroy)(*ksp);}
1021: DMDestroy(&(*ksp)->dm);
1022: PCDestroy(&(*ksp)->pc);
1023: PetscFree((*ksp)->res_hist_alloc);
1024: if ((*ksp)->convergeddestroy) {
1025: (*(*ksp)->convergeddestroy)((*ksp)->cnvP);
1026: }
1027: KSPMonitorCancel((*ksp));
1028: PetscViewerDestroy(&(*ksp)->eigviewer);
1029: PetscHeaderDestroy(ksp);
1030: return(0);
1031: }
1033: /*@
1034: KSPSetPCSide - Sets the preconditioning side.
1036: Logically Collective on KSP
1038: Input Parameter:
1039: . ksp - iterative context obtained from KSPCreate()
1041: Output Parameter:
1042: . side - the preconditioning side, where side is one of
1043: .vb
1044: PC_LEFT - left preconditioning (default)
1045: PC_RIGHT - right preconditioning
1046: PC_SYMMETRIC - symmetric preconditioning
1047: .ve
1049: Options Database Keys:
1050: . -ksp_pc_side <right,left,symmetric>
1052: Notes:
1053: Left preconditioning is used by default for most Krylov methods except KSPFGMRES which only supports right preconditioning.
1055: For methods changing the side of the preconditioner changes the norm type that is used, see KSPSetNormType().
1057: Symmetric preconditioning is currently available only for the KSPQCG method. Note, however, that
1058: symmetric preconditioning can be emulated by using either right or left
1059: preconditioning and a pre or post processing step.
1061: Setting the PC side often affects the default norm type. See KSPSetNormType() for details.
1063: Level: intermediate
1065: .keywords: KSP, set, right, left, symmetric, side, preconditioner, flag
1067: .seealso: KSPGetPCSide(), KSPSetNormType(), KSPGetNormType()
1068: @*/
1069: PetscErrorCode KSPSetPCSide(KSP ksp,PCSide side)
1070: {
1074: ksp->pc_side = ksp->pc_side_set = side;
1075: return(0);
1076: }
1078: /*@
1079: KSPGetPCSide - Gets the preconditioning side.
1081: Not Collective
1083: Input Parameter:
1084: . ksp - iterative context obtained from KSPCreate()
1086: Output Parameter:
1087: . side - the preconditioning side, where side is one of
1088: .vb
1089: PC_LEFT - left preconditioning (default)
1090: PC_RIGHT - right preconditioning
1091: PC_SYMMETRIC - symmetric preconditioning
1092: .ve
1094: Level: intermediate
1096: .keywords: KSP, get, right, left, symmetric, side, preconditioner, flag
1098: .seealso: KSPSetPCSide()
1099: @*/
1100: PetscErrorCode KSPGetPCSide(KSP ksp,PCSide *side)
1101: {
1107: KSPSetUpNorms_Private(ksp,PETSC_TRUE,&ksp->normtype,&ksp->pc_side);
1108: *side = ksp->pc_side;
1109: return(0);
1110: }
1112: /*@
1113: KSPGetTolerances - Gets the relative, absolute, divergence, and maximum
1114: iteration tolerances used by the default KSP convergence tests.
1116: Not Collective
1118: Input Parameter:
1119: . ksp - the Krylov subspace context
1121: Output Parameters:
1122: + rtol - the relative convergence tolerance
1123: . abstol - the absolute convergence tolerance
1124: . dtol - the divergence tolerance
1125: - maxits - maximum number of iterations
1127: Notes:
1128: The user can specify NULL for any parameter that is not needed.
1130: Level: intermediate
1132: .keywords: KSP, get, tolerance, absolute, relative, divergence, convergence,
1133: maximum, iterations
1135: .seealso: KSPSetTolerances()
1136: @*/
1137: PetscErrorCode KSPGetTolerances(KSP ksp,PetscReal *rtol,PetscReal *abstol,PetscReal *dtol,PetscInt *maxits)
1138: {
1141: if (abstol) *abstol = ksp->abstol;
1142: if (rtol) *rtol = ksp->rtol;
1143: if (dtol) *dtol = ksp->divtol;
1144: if (maxits) *maxits = ksp->max_it;
1145: return(0);
1146: }
1148: /*@
1149: KSPSetTolerances - Sets the relative, absolute, divergence, and maximum
1150: iteration tolerances used by the default KSP convergence testers.
1152: Logically Collective on KSP
1154: Input Parameters:
1155: + ksp - the Krylov subspace context
1156: . rtol - the relative convergence tolerance, relative decrease in the (possibly preconditioned) residual norm
1157: . abstol - the absolute convergence tolerance absolute size of the (possibly preconditioned) residual norm
1158: . dtol - the divergence tolerance, amount (possibly preconditioned) residual norm can increase before KSPConvergedDefault() concludes that the method is diverging
1159: - maxits - maximum number of iterations to use
1161: Options Database Keys:
1162: + -ksp_atol <abstol> - Sets abstol
1163: . -ksp_rtol <rtol> - Sets rtol
1164: . -ksp_divtol <dtol> - Sets dtol
1165: - -ksp_max_it <maxits> - Sets maxits
1167: Notes:
1168: Use PETSC_DEFAULT to retain the default value of any of the tolerances.
1170: See KSPConvergedDefault() for details how these parameters are used in the default convergence test. See also KSPSetConvergenceTest()
1171: for setting user-defined stopping criteria.
1173: Level: intermediate
1175: .keywords: KSP, set, tolerance, absolute, relative, divergence,
1176: convergence, maximum, iterations
1178: .seealso: KSPGetTolerances(), KSPConvergedDefault(), KSPSetConvergenceTest()
1179: @*/
1180: PetscErrorCode KSPSetTolerances(KSP ksp,PetscReal rtol,PetscReal abstol,PetscReal dtol,PetscInt maxits)
1181: {
1189: if (rtol != PETSC_DEFAULT) {
1190: 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);
1191: ksp->rtol = rtol;
1192: }
1193: if (abstol != PETSC_DEFAULT) {
1194: if (abstol < 0.0) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Absolute tolerance %g must be non-negative",(double)abstol);
1195: ksp->abstol = abstol;
1196: }
1197: if (dtol != PETSC_DEFAULT) {
1198: if (dtol < 0.0) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Divergence tolerance %g must be larger than 1.0",(double)dtol);
1199: ksp->divtol = dtol;
1200: }
1201: if (maxits != PETSC_DEFAULT) {
1202: if (maxits < 0) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Maximum number of iterations %D must be non-negative",maxits);
1203: ksp->max_it = maxits;
1204: }
1205: return(0);
1206: }
1208: /*@
1209: KSPSetInitialGuessNonzero - Tells the iterative solver that the
1210: initial guess is nonzero; otherwise KSP assumes the initial guess
1211: is to be zero (and thus zeros it out before solving).
1213: Logically Collective on KSP
1215: Input Parameters:
1216: + ksp - iterative context obtained from KSPCreate()
1217: - flg - PETSC_TRUE indicates the guess is non-zero, PETSC_FALSE indicates the guess is zero
1219: Options database keys:
1220: . -ksp_initial_guess_nonzero : use nonzero initial guess; this takes an optional truth value (0/1/no/yes/true/false)
1222: Level: beginner
1224: Notes:
1225: If this is not called the X vector is zeroed in the call to KSPSolve().
1227: .keywords: KSP, set, initial guess, nonzero
1229: .seealso: KSPGetInitialGuessNonzero(), KSPSetGuessType(), KSPGuessType
1230: @*/
1231: PetscErrorCode KSPSetInitialGuessNonzero(KSP ksp,PetscBool flg)
1232: {
1236: ksp->guess_zero = (PetscBool) !(int)flg;
1237: return(0);
1238: }
1240: /*@
1241: KSPGetInitialGuessNonzero - Determines whether the KSP solver is using
1242: a zero initial guess.
1244: Not Collective
1246: Input Parameter:
1247: . ksp - iterative context obtained from KSPCreate()
1249: Output Parameter:
1250: . flag - PETSC_TRUE if guess is nonzero, else PETSC_FALSE
1252: Level: intermediate
1254: .keywords: KSP, set, initial guess, nonzero
1256: .seealso: KSPSetInitialGuessNonzero()
1257: @*/
1258: PetscErrorCode KSPGetInitialGuessNonzero(KSP ksp,PetscBool *flag)
1259: {
1263: if (ksp->guess_zero) *flag = PETSC_FALSE;
1264: else *flag = PETSC_TRUE;
1265: return(0);
1266: }
1268: /*@
1269: KSPSetErrorIfNotConverged - Causes KSPSolve() to generate an error if the solver has not converged.
1271: Logically Collective on KSP
1273: Input Parameters:
1274: + ksp - iterative context obtained from KSPCreate()
1275: - flg - PETSC_TRUE indicates you want the error generated
1277: Options database keys:
1278: . -ksp_error_if_not_converged : this takes an optional truth value (0/1/no/yes/true/false)
1280: Level: intermediate
1282: Notes:
1283: Normally PETSc continues if a linear solver fails to converge, you can call KSPGetConvergedReason() after a KSPSolve()
1284: to determine if it has converged.
1286: .keywords: KSP
1288: .seealso: KSPGetErrorIfNotConverged()
1289: @*/
1290: PetscErrorCode KSPSetErrorIfNotConverged(KSP ksp,PetscBool flg)
1291: {
1295: ksp->errorifnotconverged = flg;
1296: return(0);
1297: }
1299: /*@
1300: KSPGetErrorIfNotConverged - Will KSPSolve() generate an error if the solver does not converge?
1302: Not Collective
1304: Input Parameter:
1305: . ksp - iterative context obtained from KSPCreate()
1307: Output Parameter:
1308: . flag - PETSC_TRUE if it will generate an error, else PETSC_FALSE
1310: Level: intermediate
1312: .keywords: KSP
1314: .seealso: KSPSetErrorIfNotConverged()
1315: @*/
1316: PetscErrorCode KSPGetErrorIfNotConverged(KSP ksp,PetscBool *flag)
1317: {
1321: *flag = ksp->errorifnotconverged;
1322: return(0);
1323: }
1325: /*@
1326: KSPSetInitialGuessKnoll - Tells the iterative solver to use PCApply(pc,b,..) to compute the initial guess (The Knoll trick)
1328: Logically Collective on KSP
1330: Input Parameters:
1331: + ksp - iterative context obtained from KSPCreate()
1332: - flg - PETSC_TRUE or PETSC_FALSE
1334: Level: advanced
1336: Developer Note: the Knoll trick is not currently implemented using the KSPGuess class
1338: .keywords: KSP, set, initial guess, nonzero
1340: .seealso: KSPGetInitialGuessKnoll(), KSPSetInitialGuessNonzero(), KSPGetInitialGuessNonzero()
1341: @*/
1342: PetscErrorCode KSPSetInitialGuessKnoll(KSP ksp,PetscBool flg)
1343: {
1347: ksp->guess_knoll = flg;
1348: return(0);
1349: }
1351: /*@
1352: KSPGetInitialGuessKnoll - Determines whether the KSP solver is using the Knoll trick (using PCApply(pc,b,...) to compute
1353: the initial guess
1355: Not Collective
1357: Input Parameter:
1358: . ksp - iterative context obtained from KSPCreate()
1360: Output Parameter:
1361: . flag - PETSC_TRUE if using Knoll trick, else PETSC_FALSE
1363: Level: advanced
1365: .keywords: KSP, set, initial guess, nonzero
1367: .seealso: KSPSetInitialGuessKnoll(), KSPSetInitialGuessNonzero(), KSPGetInitialGuessNonzero()
1368: @*/
1369: PetscErrorCode KSPGetInitialGuessKnoll(KSP ksp,PetscBool *flag)
1370: {
1374: *flag = ksp->guess_knoll;
1375: return(0);
1376: }
1378: /*@
1379: KSPGetComputeSingularValues - Gets the flag indicating whether the extreme singular
1380: values will be calculated via a Lanczos or Arnoldi process as the linear
1381: system is solved.
1383: Not Collective
1385: Input Parameter:
1386: . ksp - iterative context obtained from KSPCreate()
1388: Output Parameter:
1389: . flg - PETSC_TRUE or PETSC_FALSE
1391: Options Database Key:
1392: . -ksp_monitor_singular_value - Activates KSPSetComputeSingularValues()
1394: Notes:
1395: Currently this option is not valid for all iterative methods.
1397: Many users may just want to use the monitoring routine
1398: KSPMonitorSingularValue() (which can be set with option -ksp_monitor_singular_value)
1399: to print the singular values at each iteration of the linear solve.
1401: Level: advanced
1403: .keywords: KSP, set, compute, singular values
1405: .seealso: KSPComputeExtremeSingularValues(), KSPMonitorSingularValue()
1406: @*/
1407: PetscErrorCode KSPGetComputeSingularValues(KSP ksp,PetscBool *flg)
1408: {
1412: *flg = ksp->calc_sings;
1413: return(0);
1414: }
1416: /*@
1417: KSPSetComputeSingularValues - Sets a flag so that the extreme singular
1418: values will be calculated via a Lanczos or Arnoldi process as the linear
1419: system is solved.
1421: Logically Collective on KSP
1423: Input Parameters:
1424: + ksp - iterative context obtained from KSPCreate()
1425: - flg - PETSC_TRUE or PETSC_FALSE
1427: Options Database Key:
1428: . -ksp_monitor_singular_value - Activates KSPSetComputeSingularValues()
1430: Notes:
1431: Currently this option is not valid for all iterative methods.
1433: Many users may just want to use the monitoring routine
1434: KSPMonitorSingularValue() (which can be set with option -ksp_monitor_singular_value)
1435: to print the singular values at each iteration of the linear solve.
1437: Level: advanced
1439: .keywords: KSP, set, compute, singular values
1441: .seealso: KSPComputeExtremeSingularValues(), KSPMonitorSingularValue()
1442: @*/
1443: PetscErrorCode KSPSetComputeSingularValues(KSP ksp,PetscBool flg)
1444: {
1448: ksp->calc_sings = flg;
1449: return(0);
1450: }
1452: /*@
1453: KSPGetComputeEigenvalues - Gets the flag indicating that the extreme eigenvalues
1454: values will be calculated via a Lanczos or Arnoldi process as the linear
1455: system is solved.
1457: Not Collective
1459: Input Parameter:
1460: . ksp - iterative context obtained from KSPCreate()
1462: Output Parameter:
1463: . flg - PETSC_TRUE or PETSC_FALSE
1465: Notes:
1466: Currently this option is not valid for all iterative methods.
1468: Level: advanced
1470: .keywords: KSP, set, compute, eigenvalues
1472: .seealso: KSPComputeEigenvalues(), KSPComputeEigenvaluesExplicitly()
1473: @*/
1474: PetscErrorCode KSPGetComputeEigenvalues(KSP ksp,PetscBool *flg)
1475: {
1479: *flg = ksp->calc_sings;
1480: return(0);
1481: }
1483: /*@
1484: KSPSetComputeEigenvalues - Sets a flag so that the extreme eigenvalues
1485: values will be calculated via a Lanczos or Arnoldi process as the linear
1486: system is solved.
1488: Logically Collective on KSP
1490: Input Parameters:
1491: + ksp - iterative context obtained from KSPCreate()
1492: - flg - PETSC_TRUE or PETSC_FALSE
1494: Notes:
1495: Currently this option is not valid for all iterative methods.
1497: Level: advanced
1499: .keywords: KSP, set, compute, eigenvalues
1501: .seealso: KSPComputeEigenvalues(), KSPComputeEigenvaluesExplicitly()
1502: @*/
1503: PetscErrorCode KSPSetComputeEigenvalues(KSP ksp,PetscBool flg)
1504: {
1508: ksp->calc_sings = flg;
1509: return(0);
1510: }
1512: /*@
1513: KSPSetComputeRitz - Sets a flag so that the Ritz or harmonic Ritz pairs
1514: will be calculated via a Lanczos or Arnoldi process as the linear
1515: system is solved.
1517: Logically Collective on KSP
1519: Input Parameters:
1520: + ksp - iterative context obtained from KSPCreate()
1521: - flg - PETSC_TRUE or PETSC_FALSE
1523: Notes:
1524: Currently this option is only valid for the GMRES method.
1526: Level: advanced
1528: .keywords: KSP, set, compute, ritz
1530: .seealso: KSPComputeRitz()
1531: @*/
1532: PetscErrorCode KSPSetComputeRitz(KSP ksp, PetscBool flg)
1533: {
1537: ksp->calc_ritz = flg;
1538: return(0);
1539: }
1541: /*@
1542: KSPGetRhs - Gets the right-hand-side vector for the linear system to
1543: be solved.
1545: Not Collective
1547: Input Parameter:
1548: . ksp - iterative context obtained from KSPCreate()
1550: Output Parameter:
1551: . r - right-hand-side vector
1553: Level: developer
1555: .keywords: KSP, get, right-hand-side, rhs
1557: .seealso: KSPGetSolution(), KSPSolve()
1558: @*/
1559: PetscErrorCode KSPGetRhs(KSP ksp,Vec *r)
1560: {
1564: *r = ksp->vec_rhs;
1565: return(0);
1566: }
1568: /*@
1569: KSPGetSolution - Gets the location of the solution for the
1570: linear system to be solved. Note that this may not be where the solution
1571: is stored during the iterative process; see KSPBuildSolution().
1573: Not Collective
1575: Input Parameters:
1576: . ksp - iterative context obtained from KSPCreate()
1578: Output Parameters:
1579: . v - solution vector
1581: Level: developer
1583: .keywords: KSP, get, solution
1585: .seealso: KSPGetRhs(), KSPBuildSolution(), KSPSolve()
1586: @*/
1587: PetscErrorCode KSPGetSolution(KSP ksp,Vec *v)
1588: {
1592: *v = ksp->vec_sol;
1593: return(0);
1594: }
1596: /*@
1597: KSPSetPC - Sets the preconditioner to be used to calculate the
1598: application of the preconditioner on a vector.
1600: Collective on KSP
1602: Input Parameters:
1603: + ksp - iterative context obtained from KSPCreate()
1604: - pc - the preconditioner object
1606: Notes:
1607: Use KSPGetPC() to retrieve the preconditioner context (for example,
1608: to free it at the end of the computations).
1610: Level: developer
1612: .keywords: KSP, set, precondition, Binv
1614: .seealso: KSPGetPC()
1615: @*/
1616: PetscErrorCode KSPSetPC(KSP ksp,PC pc)
1617: {
1624: PetscObjectReference((PetscObject)pc);
1625: PCDestroy(&ksp->pc);
1626: ksp->pc = pc;
1627: PetscLogObjectParent((PetscObject)ksp,(PetscObject)ksp->pc);
1628: return(0);
1629: }
1631: /*@
1632: KSPGetPC - Returns a pointer to the preconditioner context
1633: set with KSPSetPC().
1635: Not Collective
1637: Input Parameters:
1638: . ksp - iterative context obtained from KSPCreate()
1640: Output Parameter:
1641: . pc - preconditioner context
1643: Level: developer
1645: .keywords: KSP, get, preconditioner, Binv
1647: .seealso: KSPSetPC()
1648: @*/
1649: PetscErrorCode KSPGetPC(KSP ksp,PC *pc)
1650: {
1656: if (!ksp->pc) {
1657: PCCreate(PetscObjectComm((PetscObject)ksp),&ksp->pc);
1658: PetscObjectIncrementTabLevel((PetscObject)ksp->pc,(PetscObject)ksp,0);
1659: PetscLogObjectParent((PetscObject)ksp,(PetscObject)ksp->pc);
1660: }
1661: *pc = ksp->pc;
1662: return(0);
1663: }
1665: /*@
1666: KSPMonitor - runs the user provided monitor routines, if they exist
1668: Collective on KSP
1670: Input Parameters:
1671: + ksp - iterative context obtained from KSPCreate()
1672: . it - iteration number
1673: - rnorm - relative norm of the residual
1675: Notes:
1676: This routine is called by the KSP implementations.
1677: It does not typically need to be called by the user.
1679: Level: developer
1681: .seealso: KSPMonitorSet()
1682: @*/
1683: PetscErrorCode KSPMonitor(KSP ksp,PetscInt it,PetscReal rnorm)
1684: {
1685: PetscInt i, n = ksp->numbermonitors;
1689: for (i=0; i<n; i++) {
1690: (*ksp->monitor[i])(ksp,it,rnorm,ksp->monitorcontext[i]);
1691: }
1692: return(0);
1693: }
1695: /*
1697: Checks if two monitors are identical; if they are then it destroys the new one
1698: */
1699: PetscErrorCode PetscMonitorCompare(PetscErrorCode (*nmon)(void),void *nmctx,PetscErrorCode (*nmdestroy)(void**),PetscErrorCode (*mon)(void),void *mctx,PetscErrorCode (*mdestroy)(void**),PetscBool *identical)
1700: {
1701: *identical = PETSC_FALSE;
1702: if (nmon == mon && nmdestroy == mdestroy) {
1703: if (nmctx == mctx) *identical = PETSC_TRUE;
1704: else if (nmdestroy == (PetscErrorCode (*)(void**)) PetscViewerAndFormatDestroy) {
1705: PetscViewerAndFormat *old = (PetscViewerAndFormat*)mctx, *newo = (PetscViewerAndFormat*)nmctx;
1706: if (old->viewer == newo->viewer && old->format == newo->format) *identical = PETSC_TRUE;
1707: }
1708: if (*identical) {
1709: if (mdestroy) {
1711: (*mdestroy)(&nmctx);
1712: }
1713: }
1714: }
1715: return(0);
1716: }
1718: /*@C
1719: KSPMonitorSet - Sets an ADDITIONAL function to be called at every iteration to monitor
1720: the residual/error etc.
1722: Logically Collective on KSP
1724: Input Parameters:
1725: + ksp - iterative context obtained from KSPCreate()
1726: . monitor - pointer to function (if this is NULL, it turns off monitoring
1727: . mctx - [optional] context for private data for the
1728: monitor routine (use NULL if no context is desired)
1729: - monitordestroy - [optional] routine that frees monitor context
1730: (may be NULL)
1732: Calling Sequence of monitor:
1733: $ monitor (KSP ksp, int it, PetscReal rnorm, void *mctx)
1735: + ksp - iterative context obtained from KSPCreate()
1736: . it - iteration number
1737: . rnorm - (estimated) 2-norm of (preconditioned) residual
1738: - mctx - optional monitoring context, as set by KSPMonitorSet()
1740: Options Database Keys:
1741: + -ksp_monitor - sets KSPMonitorDefault()
1742: . -ksp_monitor_true_residual - sets KSPMonitorTrueResidualNorm()
1743: . -ksp_monitor_max - sets KSPMonitorTrueResidualMaxNorm()
1744: . -ksp_monitor_lg_residualnorm - sets line graph monitor,
1745: uses KSPMonitorLGResidualNormCreate()
1746: . -ksp_monitor_lg_true_residualnorm - sets line graph monitor,
1747: uses KSPMonitorLGResidualNormCreate()
1748: . -ksp_monitor_singular_value - sets KSPMonitorSingularValue()
1749: - -ksp_monitor_cancel - cancels all monitors that have
1750: been hardwired into a code by
1751: calls to KSPMonitorSet(), but
1752: does not cancel those set via
1753: the options database.
1755: Notes:
1756: The default is to do nothing. To print the residual, or preconditioned
1757: residual if KSPSetNormType(ksp,KSP_NORM_PRECONDITIONED) was called, use
1758: KSPMonitorDefault() as the monitoring routine, with a ASCII viewer as the
1759: context.
1761: Several different monitoring routines may be set by calling
1762: KSPMonitorSet() multiple times; all will be called in the
1763: order in which they were set.
1765: Fortran notes: Only a single monitor function can be set for each KSP object
1767: Level: beginner
1769: .keywords: KSP, set, monitor
1771: .seealso: KSPMonitorDefault(), KSPMonitorLGResidualNormCreate(), KSPMonitorCancel()
1772: @*/
1773: PetscErrorCode KSPMonitorSet(KSP ksp,PetscErrorCode (*monitor)(KSP,PetscInt,PetscReal,void*),void *mctx,PetscErrorCode (*monitordestroy)(void**))
1774: {
1775: PetscInt i;
1777: PetscBool identical;
1781: for (i=0; i<ksp->numbermonitors;i++) {
1782: PetscMonitorCompare((PetscErrorCode (*)(void))monitor,mctx,monitordestroy,(PetscErrorCode (*)(void))ksp->monitor[i],ksp->monitorcontext[i],ksp->monitordestroy[i],&identical);
1783: if (identical) return(0);
1784: }
1785: if (ksp->numbermonitors >= MAXKSPMONITORS) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Too many KSP monitors set");
1786: ksp->monitor[ksp->numbermonitors] = monitor;
1787: ksp->monitordestroy[ksp->numbermonitors] = monitordestroy;
1788: ksp->monitorcontext[ksp->numbermonitors++] = (void*)mctx;
1789: return(0);
1790: }
1792: /*@
1793: KSPMonitorCancel - Clears all monitors for a KSP object.
1795: Logically Collective on KSP
1797: Input Parameters:
1798: . ksp - iterative context obtained from KSPCreate()
1800: Options Database Key:
1801: . -ksp_monitor_cancel - Cancels all monitors that have
1802: been hardwired into a code by calls to KSPMonitorSet(),
1803: but does not cancel those set via the options database.
1805: Level: intermediate
1807: .keywords: KSP, set, monitor
1809: .seealso: KSPMonitorDefault(), KSPMonitorLGResidualNormCreate(), KSPMonitorSet()
1810: @*/
1811: PetscErrorCode KSPMonitorCancel(KSP ksp)
1812: {
1814: PetscInt i;
1818: for (i=0; i<ksp->numbermonitors; i++) {
1819: if (ksp->monitordestroy[i]) {
1820: (*ksp->monitordestroy[i])(&ksp->monitorcontext[i]);
1821: }
1822: }
1823: ksp->numbermonitors = 0;
1824: return(0);
1825: }
1827: /*@C
1828: KSPGetMonitorContext - Gets the monitoring context, as set by
1829: KSPMonitorSet() for the FIRST monitor only.
1831: Not Collective
1833: Input Parameter:
1834: . ksp - iterative context obtained from KSPCreate()
1836: Output Parameter:
1837: . ctx - monitoring context
1839: Level: intermediate
1841: .keywords: KSP, get, monitor, context
1843: .seealso: KSPMonitorDefault(), KSPMonitorLGResidualNormCreate()
1844: @*/
1845: PetscErrorCode KSPGetMonitorContext(KSP ksp,void **ctx)
1846: {
1849: *ctx = (ksp->monitorcontext[0]);
1850: return(0);
1851: }
1853: /*@
1854: KSPSetResidualHistory - Sets the array used to hold the residual history.
1855: If set, this array will contain the residual norms computed at each
1856: iteration of the solver.
1858: Not Collective
1860: Input Parameters:
1861: + ksp - iterative context obtained from KSPCreate()
1862: . a - array to hold history
1863: . na - size of a
1864: - reset - PETSC_TRUE indicates the history counter is reset to zero
1865: for each new linear solve
1867: Level: advanced
1869: Notes: The array is NOT freed by PETSc so the user needs to keep track of
1870: it and destroy once the KSP object is destroyed.
1872: If 'a' is NULL then space is allocated for the history. If 'na' PETSC_DECIDE or PETSC_DEFAULT then a
1873: default array of length 10000 is allocated.
1875: .keywords: KSP, set, residual, history, norm
1877: .seealso: KSPGetResidualHistory()
1879: @*/
1880: PetscErrorCode KSPSetResidualHistory(KSP ksp,PetscReal a[],PetscInt na,PetscBool reset)
1881: {
1887: PetscFree(ksp->res_hist_alloc);
1888: if (na != PETSC_DECIDE && na != PETSC_DEFAULT && a) {
1889: ksp->res_hist = a;
1890: ksp->res_hist_max = na;
1891: } else {
1892: if (na != PETSC_DECIDE && na != PETSC_DEFAULT) ksp->res_hist_max = na;
1893: else ksp->res_hist_max = 10000; /* like default ksp->max_it */
1894: PetscCalloc1(ksp->res_hist_max,&ksp->res_hist_alloc);
1896: ksp->res_hist = ksp->res_hist_alloc;
1897: }
1898: ksp->res_hist_len = 0;
1899: ksp->res_hist_reset = reset;
1900: return(0);
1901: }
1903: /*@C
1904: KSPGetResidualHistory - Gets the array used to hold the residual history
1905: and the number of residuals it contains.
1907: Not Collective
1909: Input Parameter:
1910: . ksp - iterative context obtained from KSPCreate()
1912: Output Parameters:
1913: + a - pointer to array to hold history (or NULL)
1914: - na - number of used entries in a (or NULL)
1916: Level: advanced
1918: Notes:
1919: Can only be called after a KSPSetResidualHistory() otherwise a and na are set to zero
1921: The Fortran version of this routine has a calling sequence
1922: $ call KSPGetResidualHistory(KSP ksp, integer na, integer ierr)
1923: note that you have passed a Fortran array into KSPSetResidualHistory() and you need
1924: to access the residual values from this Fortran array you provided. Only the na (number of
1925: residual norms currently held) is set.
1927: .keywords: KSP, get, residual, history, norm
1929: .seealso: KSPGetResidualHistory()
1931: @*/
1932: PetscErrorCode KSPGetResidualHistory(KSP ksp,PetscReal *a[],PetscInt *na)
1933: {
1936: if (a) *a = ksp->res_hist;
1937: if (na) *na = ksp->res_hist_len;
1938: return(0);
1939: }
1941: /*@C
1942: KSPSetConvergenceTest - Sets the function to be used to determine
1943: convergence.
1945: Logically Collective on KSP
1947: Input Parameters:
1948: + ksp - iterative context obtained from KSPCreate()
1949: . converge - pointer to int function
1950: . cctx - context for private data for the convergence routine (may be null)
1951: - destroy - a routine for destroying the context (may be null)
1953: Calling sequence of converge:
1954: $ converge (KSP ksp, int it, PetscReal rnorm, KSPConvergedReason *reason,void *mctx)
1956: + ksp - iterative context obtained from KSPCreate()
1957: . it - iteration number
1958: . rnorm - (estimated) 2-norm of (preconditioned) residual
1959: . reason - the reason why it has converged or diverged
1960: - cctx - optional convergence context, as set by KSPSetConvergenceTest()
1963: Notes:
1964: Must be called after the KSP type has been set so put this after
1965: a call to KSPSetType(), or KSPSetFromOptions().
1967: The default convergence test, KSPConvergedDefault(), aborts if the
1968: residual grows to more than 10000 times the initial residual.
1970: The default is a combination of relative and absolute tolerances.
1971: The residual value that is tested may be an approximation; routines
1972: that need exact values should compute them.
1974: In the default PETSc convergence test, the precise values of reason
1975: are macros such as KSP_CONVERGED_RTOL, which are defined in petscksp.h.
1977: Level: advanced
1979: .keywords: KSP, set, convergence, test, context
1981: .seealso: KSPConvergedDefault(), KSPGetConvergenceContext(), KSPSetTolerances()
1982: @*/
1983: PetscErrorCode KSPSetConvergenceTest(KSP ksp,PetscErrorCode (*converge)(KSP,PetscInt,PetscReal,KSPConvergedReason*,void*),void *cctx,PetscErrorCode (*destroy)(void*))
1984: {
1989: if (ksp->convergeddestroy) {
1990: (*ksp->convergeddestroy)(ksp->cnvP);
1991: }
1992: ksp->converged = converge;
1993: ksp->convergeddestroy = destroy;
1994: ksp->cnvP = (void*)cctx;
1995: return(0);
1996: }
1998: /*@C
1999: KSPGetConvergenceContext - Gets the convergence context set with
2000: KSPSetConvergenceTest().
2002: Not Collective
2004: Input Parameter:
2005: . ksp - iterative context obtained from KSPCreate()
2007: Output Parameter:
2008: . ctx - monitoring context
2010: Level: advanced
2012: .keywords: KSP, get, convergence, test, context
2014: .seealso: KSPConvergedDefault(), KSPSetConvergenceTest()
2015: @*/
2016: PetscErrorCode KSPGetConvergenceContext(KSP ksp,void **ctx)
2017: {
2020: *ctx = ksp->cnvP;
2021: return(0);
2022: }
2024: /*@C
2025: KSPBuildSolution - Builds the approximate solution in a vector provided.
2026: This routine is NOT commonly needed (see KSPSolve()).
2028: Collective on KSP
2030: Input Parameter:
2031: . ctx - iterative context obtained from KSPCreate()
2033: Output Parameter:
2034: Provide exactly one of
2035: + v - location to stash solution.
2036: - V - the solution is returned in this location. This vector is created
2037: internally. This vector should NOT be destroyed by the user with
2038: VecDestroy().
2040: Notes:
2041: This routine can be used in one of two ways
2042: .vb
2043: KSPBuildSolution(ksp,NULL,&V);
2044: or
2045: KSPBuildSolution(ksp,v,NULL); or KSPBuildSolution(ksp,v,&v);
2046: .ve
2047: In the first case an internal vector is allocated to store the solution
2048: (the user cannot destroy this vector). In the second case the solution
2049: is generated in the vector that the user provides. Note that for certain
2050: methods, such as KSPCG, the second case requires a copy of the solution,
2051: while in the first case the call is essentially free since it simply
2052: returns the vector where the solution already is stored. For some methods
2053: like GMRES this is a reasonably expensive operation and should only be
2054: used in truly needed.
2056: Level: advanced
2058: .keywords: KSP, build, solution
2060: .seealso: KSPGetSolution(), KSPBuildResidual()
2061: @*/
2062: PetscErrorCode KSPBuildSolution(KSP ksp,Vec v,Vec *V)
2063: {
2068: if (!V && !v) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_WRONG,"Must provide either v or V");
2069: if (!V) V = &v;
2070: (*ksp->ops->buildsolution)(ksp,v,V);
2071: return(0);
2072: }
2074: /*@C
2075: KSPBuildResidual - Builds the residual in a vector provided.
2077: Collective on KSP
2079: Input Parameter:
2080: . ksp - iterative context obtained from KSPCreate()
2082: Output Parameters:
2083: + v - optional location to stash residual. If v is not provided,
2084: then a location is generated.
2085: . t - work vector. If not provided then one is generated.
2086: - V - the residual
2088: Notes:
2089: Regardless of whether or not v is provided, the residual is
2090: returned in V.
2092: Level: advanced
2094: .keywords: KSP, build, residual
2096: .seealso: KSPBuildSolution()
2097: @*/
2098: PetscErrorCode KSPBuildResidual(KSP ksp,Vec t,Vec v,Vec *V)
2099: {
2101: PetscBool flag = PETSC_FALSE;
2102: Vec w = v,tt = t;
2106: if (!w) {
2107: VecDuplicate(ksp->vec_rhs,&w);
2108: PetscLogObjectParent((PetscObject)ksp,(PetscObject)w);
2109: }
2110: if (!tt) {
2111: VecDuplicate(ksp->vec_sol,&tt); flag = PETSC_TRUE;
2112: PetscLogObjectParent((PetscObject)ksp,(PetscObject)tt);
2113: }
2114: (*ksp->ops->buildresidual)(ksp,tt,w,V);
2115: if (flag) {VecDestroy(&tt);}
2116: return(0);
2117: }
2119: /*@
2120: KSPSetDiagonalScale - Tells KSP to symmetrically diagonally scale the system
2121: before solving. This actually CHANGES the matrix (and right hand side).
2123: Logically Collective on KSP
2125: Input Parameter:
2126: + ksp - the KSP context
2127: - scale - PETSC_TRUE or PETSC_FALSE
2129: Options Database Key:
2130: + -ksp_diagonal_scale -
2131: - -ksp_diagonal_scale_fix - scale the matrix back AFTER the solve
2134: Notes: Scales the matrix by D^(-1/2) A D^(-1/2) [D^(1/2) x ] = D^(-1/2) b
2135: where D_{ii} is 1/abs(A_{ii}) unless A_{ii} is zero and then it is 1.
2137: BE CAREFUL with this routine: it actually scales the matrix and right
2138: hand side that define the system. After the system is solved the matrix
2139: and right hand side remain scaled unless you use KSPSetDiagonalScaleFix()
2141: This should NOT be used within the SNES solves if you are using a line
2142: search.
2144: If you use this with the PCType Eisenstat preconditioner than you can
2145: use the PCEisenstatSetNoDiagonalScaling() option, or -pc_eisenstat_no_diagonal_scaling
2146: to save some unneeded, redundant flops.
2148: Level: intermediate
2150: .keywords: KSP, set, options, prefix, database
2152: .seealso: KSPGetDiagonalScale(), KSPSetDiagonalScaleFix()
2153: @*/
2154: PetscErrorCode KSPSetDiagonalScale(KSP ksp,PetscBool scale)
2155: {
2159: ksp->dscale = scale;
2160: return(0);
2161: }
2163: /*@
2164: KSPGetDiagonalScale - Checks if KSP solver scales the matrix and
2165: right hand side
2167: Not Collective
2169: Input Parameter:
2170: . ksp - the KSP context
2172: Output Parameter:
2173: . scale - PETSC_TRUE or PETSC_FALSE
2175: Notes:
2176: BE CAREFUL with this routine: it actually scales the matrix and right
2177: hand side that define the system. After the system is solved the matrix
2178: and right hand side remain scaled unless you use KSPSetDiagonalScaleFix()
2180: Level: intermediate
2182: .keywords: KSP, set, options, prefix, database
2184: .seealso: KSPSetDiagonalScale(), KSPSetDiagonalScaleFix()
2185: @*/
2186: PetscErrorCode KSPGetDiagonalScale(KSP ksp,PetscBool *scale)
2187: {
2191: *scale = ksp->dscale;
2192: return(0);
2193: }
2195: /*@
2196: KSPSetDiagonalScaleFix - Tells KSP to diagonally scale the system
2197: back after solving.
2199: Logically Collective on KSP
2201: Input Parameter:
2202: + ksp - the KSP context
2203: - fix - PETSC_TRUE to scale back after the system solve, PETSC_FALSE to not
2204: rescale (default)
2206: Notes:
2207: Must be called after KSPSetDiagonalScale()
2209: Using this will slow things down, because it rescales the matrix before and
2210: after each linear solve. This is intended mainly for testing to allow one
2211: to easily get back the original system to make sure the solution computed is
2212: accurate enough.
2214: Level: intermediate
2216: .keywords: KSP, set, options, prefix, database
2218: .seealso: KSPGetDiagonalScale(), KSPSetDiagonalScale(), KSPGetDiagonalScaleFix()
2219: @*/
2220: PetscErrorCode KSPSetDiagonalScaleFix(KSP ksp,PetscBool fix)
2221: {
2225: ksp->dscalefix = fix;
2226: return(0);
2227: }
2229: /*@
2230: KSPGetDiagonalScaleFix - Determines if KSP diagonally scales the system
2231: back after solving.
2233: Not Collective
2235: Input Parameter:
2236: . ksp - the KSP context
2238: Output Parameter:
2239: . fix - PETSC_TRUE to scale back after the system solve, PETSC_FALSE to not
2240: rescale (default)
2242: Notes:
2243: Must be called after KSPSetDiagonalScale()
2245: If PETSC_TRUE will slow things down, because it rescales the matrix before and
2246: after each linear solve. This is intended mainly for testing to allow one
2247: to easily get back the original system to make sure the solution computed is
2248: accurate enough.
2250: Level: intermediate
2252: .keywords: KSP, set, options, prefix, database
2254: .seealso: KSPGetDiagonalScale(), KSPSetDiagonalScale(), KSPSetDiagonalScaleFix()
2255: @*/
2256: PetscErrorCode KSPGetDiagonalScaleFix(KSP ksp,PetscBool *fix)
2257: {
2261: *fix = ksp->dscalefix;
2262: return(0);
2263: }
2265: /*@C
2266: KSPSetComputeOperators - set routine to compute the linear operators
2268: Logically Collective
2270: Input Arguments:
2271: + ksp - the KSP context
2272: . func - function to compute the operators
2273: - ctx - optional context
2275: Calling sequence of func:
2276: $ func(KSP ksp,Mat A,Mat B,void *ctx)
2278: + ksp - the KSP context
2279: . A - the linear operator
2280: . B - preconditioning matrix
2281: - ctx - optional user-provided context
2283: 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
2284: unless either KSPSetComputeOperators() or KSPSetOperators() is called before that KSPSolve() is called.
2286: To reuse the same preconditioner for the next KSPSolve() and not compute a new one based on the most recently computed matrix call KSPSetReusePreconditioner()
2288: Level: beginner
2290: .seealso: KSPSetOperators(), KSPSetComputeRHS(), DMKSPSetComputeOperators(), KSPSetComputeInitialGuess()
2291: @*/
2292: PetscErrorCode KSPSetComputeOperators(KSP ksp,PetscErrorCode (*func)(KSP,Mat,Mat,void*),void *ctx)
2293: {
2295: DM dm;
2299: KSPGetDM(ksp,&dm);
2300: DMKSPSetComputeOperators(dm,func,ctx);
2301: if (ksp->setupstage == KSP_SETUP_NEWRHS) ksp->setupstage = KSP_SETUP_NEWMATRIX;
2302: return(0);
2303: }
2305: /*@C
2306: KSPSetComputeRHS - set routine to compute the right hand side of the linear system
2308: Logically Collective
2310: Input Arguments:
2311: + ksp - the KSP context
2312: . func - function to compute the right hand side
2313: - ctx - optional context
2315: Calling sequence of func:
2316: $ func(KSP ksp,Vec b,void *ctx)
2318: + ksp - the KSP context
2319: . b - right hand side of linear system
2320: - ctx - optional user-provided context
2322: Notes: The routine you provide will be called EACH you call KSPSolve() to prepare the new right hand side for that solve
2324: Level: beginner
2326: .seealso: KSPSolve(), DMKSPSetComputeRHS(), KSPSetComputeOperators()
2327: @*/
2328: PetscErrorCode KSPSetComputeRHS(KSP ksp,PetscErrorCode (*func)(KSP,Vec,void*),void *ctx)
2329: {
2331: DM dm;
2335: KSPGetDM(ksp,&dm);
2336: DMKSPSetComputeRHS(dm,func,ctx);
2337: return(0);
2338: }
2340: /*@C
2341: KSPSetComputeInitialGuess - set routine to compute the initial guess of the linear system
2343: Logically Collective
2345: Input Arguments:
2346: + ksp - the KSP context
2347: . func - function to compute the initial guess
2348: - ctx - optional context
2350: Calling sequence of func:
2351: $ func(KSP ksp,Vec x,void *ctx)
2353: + ksp - the KSP context
2354: . x - solution vector
2355: - ctx - optional user-provided context
2357: Level: beginner
2359: .seealso: KSPSolve(), KSPSetComputeRHS(), KSPSetComputeOperators(), DMKSPSetComputeInitialGuess()
2360: @*/
2361: PetscErrorCode KSPSetComputeInitialGuess(KSP ksp,PetscErrorCode (*func)(KSP,Vec,void*),void *ctx)
2362: {
2364: DM dm;
2368: KSPGetDM(ksp,&dm);
2369: DMKSPSetComputeInitialGuess(dm,func,ctx);
2370: return(0);
2371: }