Actual source code: itfunc.c
petsc-dev 2014-02-02
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,&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 KSPConvergedDefault()
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(), KSPConvergedDefault(),
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: Mat mat,premat;
359: if (x && x == b) {
360: if (!ksp->guess_zero) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_INCOMP,"Cannot use x == b with nonzero initial guess");
361: VecDuplicate(b,&x);
362: inXisinB = PETSC_TRUE;
363: }
364: if (b) {
365: PetscObjectReference((PetscObject)b);
366: VecDestroy(&ksp->vec_rhs);
367: ksp->vec_rhs = b;
368: }
369: if (x) {
370: PetscObjectReference((PetscObject)x);
371: VecDestroy(&ksp->vec_sol);
372: ksp->vec_sol = x;
373: }
374: KSPViewFromOptions(ksp,NULL,"-ksp_view_pre");
376: if (ksp->presolve) {
377: (*ksp->presolve)(ksp,ksp->vec_rhs,ksp->vec_sol,ksp->prectx);
378: }
379: PetscLogEventBegin(KSP_Solve,ksp,ksp->vec_rhs,ksp->vec_sol,0);
381: /* reset the residual history list if requested */
382: if (ksp->res_hist_reset) ksp->res_hist_len = 0;
383: ksp->transpose_solve = PETSC_FALSE;
385: if (ksp->guess) {
386: KSPFischerGuessFormGuess(ksp->guess,ksp->vec_rhs,ksp->vec_sol);
387: ksp->guess_zero = PETSC_FALSE;
388: }
389: /* KSPSetUp() scales the matrix if needed */
390: KSPSetUp(ksp);
391: KSPSetUpOnBlocks(ksp);
393: /* diagonal scale RHS if called for */
394: if (ksp->dscale) {
395: VecPointwiseMult(ksp->vec_rhs,ksp->vec_rhs,ksp->diagonal);
396: /* second time in, but matrix was scaled back to original */
397: if (ksp->dscalefix && ksp->dscalefix2) {
398: Mat mat,pmat;
400: PCGetOperators(ksp->pc,&mat,&pmat,NULL);
401: MatDiagonalScale(pmat,ksp->diagonal,ksp->diagonal);
402: if (mat != pmat) {MatDiagonalScale(mat,ksp->diagonal,ksp->diagonal);}
403: }
405: /* scale initial guess */
406: if (!ksp->guess_zero) {
407: if (!ksp->truediagonal) {
408: VecDuplicate(ksp->diagonal,&ksp->truediagonal);
409: VecCopy(ksp->diagonal,ksp->truediagonal);
410: VecReciprocal(ksp->truediagonal);
411: }
412: VecPointwiseMult(ksp->vec_sol,ksp->vec_sol,ksp->truediagonal);
413: }
414: }
415: PCPreSolve(ksp->pc,ksp);
417: if (ksp->guess_zero) { VecSet(ksp->vec_sol,0.0);}
418: if (ksp->guess_knoll) {
419: PCApply(ksp->pc,ksp->vec_rhs,ksp->vec_sol);
420: KSP_RemoveNullSpace(ksp,ksp->vec_sol);
421: ksp->guess_zero = PETSC_FALSE;
422: }
424: /* can we mark the initial guess as zero for this solve? */
425: guess_zero = ksp->guess_zero;
426: if (!ksp->guess_zero) {
427: PetscReal norm;
429: VecNormAvailable(ksp->vec_sol,NORM_2,&flg,&norm);
430: if (flg && !norm) ksp->guess_zero = PETSC_TRUE;
431: }
432: (*ksp->ops->solve)(ksp);
433: ksp->guess_zero = guess_zero;
435: if (!ksp->reason) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_PLIB,"Internal error, solver returned without setting converged reason");
436: if (ksp->printreason) {
437: PetscViewerASCIIAddTab(PETSC_VIEWER_STDOUT_(PetscObjectComm((PetscObject)ksp)),((PetscObject)ksp)->tablevel);
438: if (ksp->reason > 0) {
439: PetscViewerASCIIPrintf(PETSC_VIEWER_STDOUT_(PetscObjectComm((PetscObject)ksp)),"Linear solve converged due to %s iterations %D\n",KSPConvergedReasons[ksp->reason],ksp->its);
440: } else {
441: PetscViewerASCIIPrintf(PETSC_VIEWER_STDOUT_(PetscObjectComm((PetscObject)ksp)),"Linear solve did not converge due to %s iterations %D\n",KSPConvergedReasons[ksp->reason],ksp->its);
442: }
443: PetscViewerASCIISubtractTab(PETSC_VIEWER_STDOUT_(PetscObjectComm((PetscObject)ksp)),((PetscObject)ksp)->tablevel);
444: }
445: PCPostSolve(ksp->pc,ksp);
447: /* diagonal scale solution if called for */
448: if (ksp->dscale) {
449: VecPointwiseMult(ksp->vec_sol,ksp->vec_sol,ksp->diagonal);
450: /* unscale right hand side and matrix */
451: if (ksp->dscalefix) {
452: Mat mat,pmat;
454: VecReciprocal(ksp->diagonal);
455: VecPointwiseMult(ksp->vec_rhs,ksp->vec_rhs,ksp->diagonal);
456: PCGetOperators(ksp->pc,&mat,&pmat,NULL);
457: MatDiagonalScale(pmat,ksp->diagonal,ksp->diagonal);
458: if (mat != pmat) {MatDiagonalScale(mat,ksp->diagonal,ksp->diagonal);}
459: VecReciprocal(ksp->diagonal);
460: ksp->dscalefix2 = PETSC_TRUE;
461: }
462: }
463: PetscLogEventEnd(KSP_Solve,ksp,ksp->vec_rhs,ksp->vec_sol,0);
464: if (ksp->postsolve) {
465: (*ksp->postsolve)(ksp,ksp->vec_rhs,ksp->vec_sol,ksp->postctx);
466: }
468: if (ksp->guess) {
469: KSPFischerGuessUpdate(ksp->guess,ksp->vec_sol);
470: }
472: MPI_Comm_rank(PetscObjectComm((PetscObject)ksp),&rank);
474: PCGetOperators(ksp->pc,&mat,&premat,NULL);
475: MatViewFromOptions(mat,((PetscObject)ksp)->prefix,"-ksp_view_mat");
476: MatViewFromOptions(premat,((PetscObject)ksp)->prefix,"-ksp_view_pmat");
477: VecViewFromOptions(ksp->vec_rhs,((PetscObject)ksp)->prefix,"-ksp_view_rhs");
479: flag1 = PETSC_FALSE;
480: flag2 = PETSC_FALSE;
481: flag3 = PETSC_FALSE;
482: PetscOptionsGetBool(((PetscObject)ksp)->prefix,"-ksp_compute_eigenvalues",&flag1,NULL);
483: PetscOptionsGetBool(((PetscObject)ksp)->prefix,"-ksp_plot_eigenvalues",&flag2,NULL);
484: PetscOptionsGetBool(((PetscObject)ksp)->prefix,"-ksp_plot_eigencontours",&flag3,NULL);
485: if (flag1 || flag2 || flag3) {
486: PetscInt nits,n,i,neig;
487: PetscReal *r,*c;
489: KSPGetIterationNumber(ksp,&nits);
490: n = nits+2;
492: if (!nits) {
493: PetscPrintf(PetscObjectComm((PetscObject)ksp),"Zero iterations in solver, cannot approximate any eigenvalues\n");
494: } else {
495: PetscMalloc2(n,&r,n,&c);
496: KSPComputeEigenvalues(ksp,n,r,c,&neig);
497: if (flag1) {
498: PetscPrintf(PetscObjectComm((PetscObject)ksp),"Iteratively computed eigenvalues\n");
499: for (i=0; i<neig; i++) {
500: if (c[i] >= 0.0) {
501: PetscPrintf(PetscObjectComm((PetscObject)ksp),"%g + %gi\n",(double)r[i],(double)c[i]);
502: } else {
503: PetscPrintf(PetscObjectComm((PetscObject)ksp),"%g - %gi\n",(double)r[i],-(double)c[i]);
504: }
505: }
506: }
507: if (flag2 && !rank) {
508: PetscDraw draw;
509: PetscDrawSP drawsp;
511: if (!ksp->eigviewer) {
512: PetscViewerDrawOpen(PETSC_COMM_SELF,0,"Iteratively Computed Eigenvalues",PETSC_DECIDE,PETSC_DECIDE,400,400,&ksp->eigviewer);
513: }
514: PetscViewerDrawGetDraw(ksp->eigviewer,0,&draw);
515: PetscDrawSPCreate(draw,1,&drawsp);
516: PetscDrawSPReset(drawsp);
517: for (i=0; i<neig; i++) {
518: PetscDrawSPAddPoint(drawsp,r+i,c+i);
519: }
520: PetscDrawSPDraw(drawsp,PETSC_TRUE);
521: PetscDrawSPDestroy(&drawsp);
522: }
523: if (flag3 && !rank) {
524: KSPPlotEigenContours_Private(ksp,neig,r,c);
525: }
526: PetscFree2(r,c);
527: }
528: }
530: flag1 = PETSC_FALSE;
531: PetscOptionsGetBool(((PetscObject)ksp)->prefix,"-ksp_compute_singularvalues",&flag1,NULL);
532: if (flag1) {
533: PetscInt nits;
535: KSPGetIterationNumber(ksp,&nits);
536: if (!nits) {
537: PetscPrintf(PetscObjectComm((PetscObject)ksp),"Zero iterations in solver, cannot approximate any singular values\n");
538: } else {
539: PetscReal emax,emin;
541: KSPComputeExtremeSingularValues(ksp,&emax,&emin);
542: PetscPrintf(PetscObjectComm((PetscObject)ksp),"Iteratively computed extreme singular values: max %g min %g max/min %g\n",(double)emax,(double)emin,(double)(emax/emin));
543: }
544: }
547: flag1 = PETSC_FALSE;
548: flag2 = PETSC_FALSE;
549: PetscOptionsGetBool(((PetscObject)ksp)->prefix,"-ksp_compute_eigenvalues_explicitly",&flag1,NULL);
550: PetscOptionsGetBool(((PetscObject)ksp)->prefix,"-ksp_plot_eigenvalues_explicitly",&flag2,NULL);
551: if (flag1 || flag2) {
552: PetscInt n,i;
553: PetscReal *r,*c;
554: VecGetSize(ksp->vec_sol,&n);
555: PetscMalloc2(n,&r,n,&c);
556: KSPComputeEigenvaluesExplicitly(ksp,n,r,c);
557: if (flag1) {
558: PetscPrintf(PetscObjectComm((PetscObject)ksp),"Explicitly computed eigenvalues\n");
559: for (i=0; i<n; i++) {
560: if (c[i] >= 0.0) {
561: PetscPrintf(PetscObjectComm((PetscObject)ksp),"%g + %gi\n",(double)r[i],(double)c[i]);
562: } else {
563: PetscPrintf(PetscObjectComm((PetscObject)ksp),"%g - %gi\n",(double)r[i],-(double)c[i]);
564: }
565: }
566: }
567: if (flag2 && !rank) {
568: PetscDraw draw;
569: PetscDrawSP drawsp;
571: if (!ksp->eigviewer) {
572: PetscViewerDrawOpen(PETSC_COMM_SELF,0,"Explicitly Computed Eigenvalues",0,320,400,400,&ksp->eigviewer);
573: }
574: PetscViewerDrawGetDraw(ksp->eigviewer,0,&draw);
575: PetscDrawSPCreate(draw,1,&drawsp);
576: PetscDrawSPReset(drawsp);
577: for (i=0; i<n; i++) {
578: PetscDrawSPAddPoint(drawsp,r+i,c+i);
579: }
580: PetscDrawSPDraw(drawsp,PETSC_TRUE);
581: PetscDrawSPDestroy(&drawsp);
582: }
583: PetscFree2(r,c);
584: }
586: PetscOptionsHasName(((PetscObject)ksp)->prefix,"-ksp_view_mat_explicit",&flag2);
587: if (flag2) {
588: Mat A,B;
589: PCGetOperators(ksp->pc,&A,NULL,NULL);
590: MatComputeExplicitOperator(A,&B);
591: MatViewFromOptions(B,((PetscObject)ksp)->prefix,"-ksp_view_mat_explicit");
592: MatDestroy(&B);
593: }
594: PetscOptionsHasName(((PetscObject)ksp)->prefix,"-ksp_view_preconditioned_operator_explicit",&flag2);
595: if (flag2) {
596: Mat B;
597: KSPComputeExplicitOperator(ksp,&B);
598: MatViewFromOptions(B,((PetscObject)ksp)->prefix,"-ksp_view_preconditioned_operator_explicit");
599: MatDestroy(&B);
600: }
601: KSPViewFromOptions(ksp,NULL,"-ksp_view");
603: flg = PETSC_FALSE;
604: PetscOptionsGetBool(((PetscObject)ksp)->prefix,"-ksp_final_residual",&flg,NULL);
605: if (flg) {
606: Mat A;
607: Vec t;
608: PetscReal norm;
609: 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");
610: PCGetOperators(ksp->pc,&A,0,0);
611: VecDuplicate(ksp->vec_rhs,&t);
612: KSP_MatMult(ksp,A,ksp->vec_sol,t);
613: VecAYPX(t, -1.0, ksp->vec_rhs);
614: VecNorm(t,NORM_2,&norm);
615: VecDestroy(&t);
616: PetscPrintf(PetscObjectComm((PetscObject)ksp),"KSP final norm of residual %g\n",(double)norm);
617: }
618: VecViewFromOptions(ksp->vec_sol,((PetscObject)ksp)->prefix,"-ksp_view_solution");
620: if (inXisinB) {
621: VecCopy(x,b);
622: VecDestroy(&x);
623: }
624: PetscObjectSAWsBlock((PetscObject)ksp);
625: if (ksp->errorifnotconverged && ksp->reason < 0) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_NOT_CONVERGED,"KSPSolve has not converged");
626: return(0);
627: }
631: /*@
632: KSPSolveTranspose - Solves the transpose of a linear system.
634: Collective on KSP
636: Input Parameter:
637: + ksp - iterative context obtained from KSPCreate()
638: . b - right hand side vector
639: - x - solution vector
641: Notes: For complex numbers this solve the non-Hermitian transpose system.
643: Developer Notes: We need to implement a KSPSolveHermitianTranspose()
645: Level: developer
647: .keywords: KSP, solve, linear system
649: .seealso: KSPCreate(), KSPSetUp(), KSPDestroy(), KSPSetTolerances(), KSPConvergedDefault(),
650: KSPSolve()
651: @*/
653: PetscErrorCode KSPSolveTranspose(KSP ksp,Vec b,Vec x)
654: {
656: PetscBool inXisinB=PETSC_FALSE;
662: if (x == b) {
663: VecDuplicate(b,&x);
664: inXisinB = PETSC_TRUE;
665: }
666: PetscObjectReference((PetscObject)b);
667: PetscObjectReference((PetscObject)x);
668: VecDestroy(&ksp->vec_rhs);
669: VecDestroy(&ksp->vec_sol);
671: ksp->vec_rhs = b;
672: ksp->vec_sol = x;
673: ksp->transpose_solve = PETSC_TRUE;
675: KSPSetUp(ksp);
676: if (ksp->guess_zero) { VecSet(ksp->vec_sol,0.0);}
677: (*ksp->ops->solve)(ksp);
678: if (!ksp->reason) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_PLIB,"Internal error, solver returned without setting converged reason");
679: if (ksp->printreason) {
680: if (ksp->reason > 0) {
681: PetscPrintf(PetscObjectComm((PetscObject)ksp),"Linear solve converged due to %s iterations %D\n",KSPConvergedReasons[ksp->reason],ksp->its);
682: } else {
683: PetscPrintf(PetscObjectComm((PetscObject)ksp),"Linear solve did not converge due to %s iterations %D\n",KSPConvergedReasons[ksp->reason],ksp->its);
684: }
685: }
686: if (inXisinB) {
687: VecCopy(x,b);
688: VecDestroy(&x);
689: }
690: if (ksp->errorifnotconverged && ksp->reason < 0) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_NOT_CONVERGED,"KSPSolve has not converged");
691: return(0);
692: }
696: /*@
697: KSPReset - Resets a KSP context to the kspsetupcalled = 0 state and removes any allocated Vecs and Mats
699: Collective on KSP
701: Input Parameter:
702: . ksp - iterative context obtained from KSPCreate()
704: Level: beginner
706: .keywords: KSP, destroy
708: .seealso: KSPCreate(), KSPSetUp(), KSPSolve()
709: @*/
710: PetscErrorCode KSPReset(KSP ksp)
711: {
716: if (!ksp) return(0);
717: if (ksp->ops->reset) {
718: (*ksp->ops->reset)(ksp);
719: }
720: if (ksp->pc) {PCReset(ksp->pc);}
721: KSPFischerGuessDestroy(&ksp->guess);
722: VecDestroyVecs(ksp->nwork,&ksp->work);
723: VecDestroy(&ksp->vec_rhs);
724: VecDestroy(&ksp->vec_sol);
725: VecDestroy(&ksp->diagonal);
726: VecDestroy(&ksp->truediagonal);
727: MatNullSpaceDestroy(&ksp->nullsp);
729: ksp->setupstage = KSP_SETUP_NEW;
730: return(0);
731: }
735: /*@
736: KSPDestroy - Destroys KSP context.
738: Collective on KSP
740: Input Parameter:
741: . ksp - iterative context obtained from KSPCreate()
743: Level: beginner
745: .keywords: KSP, destroy
747: .seealso: KSPCreate(), KSPSetUp(), KSPSolve()
748: @*/
749: PetscErrorCode KSPDestroy(KSP *ksp)
750: {
752: PC pc;
755: if (!*ksp) return(0);
757: if (--((PetscObject)(*ksp))->refct > 0) {*ksp = 0; return(0);}
759: PetscObjectSAWsViewOff((PetscObject)*ksp);
760: /*
761: Avoid a cascading call to PCReset(ksp->pc) from the following call:
762: PCReset() shouldn't be called from KSPDestroy() as it is unprotected by pc's
763: refcount (and may be shared, e.g., by other ksps).
764: */
765: pc = (*ksp)->pc;
766: (*ksp)->pc = NULL;
767: KSPReset((*ksp));
768: (*ksp)->pc = pc;
769: if ((*ksp)->ops->destroy) {(*(*ksp)->ops->destroy)(*ksp);}
771: DMDestroy(&(*ksp)->dm);
772: PCDestroy(&(*ksp)->pc);
773: PetscFree((*ksp)->res_hist_alloc);
774: if ((*ksp)->convergeddestroy) {
775: (*(*ksp)->convergeddestroy)((*ksp)->cnvP);
776: }
777: KSPMonitorCancel((*ksp));
778: PetscViewerDestroy(&(*ksp)->eigviewer);
779: PetscHeaderDestroy(ksp);
780: return(0);
781: }
785: /*@
786: KSPSetPCSide - Sets the preconditioning side.
788: Logically Collective on KSP
790: Input Parameter:
791: . ksp - iterative context obtained from KSPCreate()
793: Output Parameter:
794: . side - the preconditioning side, where side is one of
795: .vb
796: PC_LEFT - left preconditioning (default)
797: PC_RIGHT - right preconditioning
798: PC_SYMMETRIC - symmetric preconditioning
799: .ve
801: Options Database Keys:
802: . -ksp_pc_side <right,left,symmetric>
804: Notes:
805: Left preconditioning is used by default for most Krylov methods except KSPFGMRES which only supports right preconditioning.
806: Symmetric preconditioning is currently available only for the KSPQCG method. Note, however, that
807: symmetric preconditioning can be emulated by using either right or left
808: preconditioning and a pre or post processing step.
810: Level: intermediate
812: .keywords: KSP, set, right, left, symmetric, side, preconditioner, flag
814: .seealso: KSPGetPCSide()
815: @*/
816: PetscErrorCode KSPSetPCSide(KSP ksp,PCSide side)
817: {
821: ksp->pc_side = side;
822: return(0);
823: }
827: /*@
828: KSPGetPCSide - Gets the preconditioning side.
830: Not Collective
832: Input Parameter:
833: . ksp - iterative context obtained from KSPCreate()
835: Output Parameter:
836: . side - the preconditioning side, where side is one of
837: .vb
838: PC_LEFT - left preconditioning (default)
839: PC_RIGHT - right preconditioning
840: PC_SYMMETRIC - symmetric preconditioning
841: .ve
843: Level: intermediate
845: .keywords: KSP, get, right, left, symmetric, side, preconditioner, flag
847: .seealso: KSPSetPCSide()
848: @*/
849: PetscErrorCode KSPGetPCSide(KSP ksp,PCSide *side)
850: {
856: KSPSetUpNorms_Private(ksp,&ksp->normtype,&ksp->pc_side);
857: *side = ksp->pc_side;
858: return(0);
859: }
863: /*@
864: KSPGetTolerances - Gets the relative, absolute, divergence, and maximum
865: iteration tolerances used by the default KSP convergence tests.
867: Not Collective
869: Input Parameter:
870: . ksp - the Krylov subspace context
872: Output Parameters:
873: + rtol - the relative convergence tolerance
874: . abstol - the absolute convergence tolerance
875: . dtol - the divergence tolerance
876: - maxits - maximum number of iterations
878: Notes:
879: The user can specify NULL for any parameter that is not needed.
881: Level: intermediate
883: .keywords: KSP, get, tolerance, absolute, relative, divergence, convergence,
884: maximum, iterations
886: .seealso: KSPSetTolerances()
887: @*/
888: PetscErrorCode KSPGetTolerances(KSP ksp,PetscReal *rtol,PetscReal *abstol,PetscReal *dtol,PetscInt *maxits)
889: {
892: if (abstol) *abstol = ksp->abstol;
893: if (rtol) *rtol = ksp->rtol;
894: if (dtol) *dtol = ksp->divtol;
895: if (maxits) *maxits = ksp->max_it;
896: return(0);
897: }
901: /*@
902: KSPSetTolerances - Sets the relative, absolute, divergence, and maximum
903: iteration tolerances used by the default KSP convergence testers.
905: Logically Collective on KSP
907: Input Parameters:
908: + ksp - the Krylov subspace context
909: . rtol - the relative convergence tolerance
910: (relative decrease in the residual norm)
911: . abstol - the absolute convergence tolerance
912: (absolute size of the residual norm)
913: . dtol - the divergence tolerance
914: (amount residual can increase before KSPConvergedDefault()
915: concludes that the method is diverging)
916: - maxits - maximum number of iterations to use
918: Options Database Keys:
919: + -ksp_atol <abstol> - Sets abstol
920: . -ksp_rtol <rtol> - Sets rtol
921: . -ksp_divtol <dtol> - Sets dtol
922: - -ksp_max_it <maxits> - Sets maxits
924: Notes:
925: Use PETSC_DEFAULT to retain the default value of any of the tolerances.
927: See KSPConvergedDefault() for details on the use of these parameters
928: in the default convergence test. See also KSPSetConvergenceTest()
929: for setting user-defined stopping criteria.
931: Level: intermediate
933: .keywords: KSP, set, tolerance, absolute, relative, divergence,
934: convergence, maximum, iterations
936: .seealso: KSPGetTolerances(), KSPConvergedDefault(), KSPSetConvergenceTest()
937: @*/
938: PetscErrorCode KSPSetTolerances(KSP ksp,PetscReal rtol,PetscReal abstol,PetscReal dtol,PetscInt maxits)
939: {
947: if (rtol != PETSC_DEFAULT) {
948: 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);
949: ksp->rtol = rtol;
950: }
951: if (abstol != PETSC_DEFAULT) {
952: if (abstol < 0.0) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Absolute tolerance %g must be non-negative",(double)abstol);
953: ksp->abstol = abstol;
954: }
955: if (dtol != PETSC_DEFAULT) {
956: if (dtol < 0.0) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Divergence tolerance %g must be larger than 1.0",(double)dtol);
957: ksp->divtol = dtol;
958: }
959: if (maxits != PETSC_DEFAULT) {
960: if (maxits < 0) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Maximum number of iterations %D must be non-negative",maxits);
961: ksp->max_it = maxits;
962: }
963: return(0);
964: }
968: /*@
969: KSPSetInitialGuessNonzero - Tells the iterative solver that the
970: initial guess is nonzero; otherwise KSP assumes the initial guess
971: is to be zero (and thus zeros it out before solving).
973: Logically Collective on KSP
975: Input Parameters:
976: + ksp - iterative context obtained from KSPCreate()
977: - flg - PETSC_TRUE indicates the guess is non-zero, PETSC_FALSE indicates the guess is zero
979: Options database keys:
980: . -ksp_initial_guess_nonzero : use nonzero initial guess; this takes an optional truth value (0/1/no/yes/true/false)
982: Level: beginner
984: Notes:
985: If this is not called the X vector is zeroed in the call to KSPSolve().
987: .keywords: KSP, set, initial guess, nonzero
989: .seealso: KSPGetInitialGuessNonzero(), KSPSetInitialGuessKnoll(), KSPGetInitialGuessKnoll()
990: @*/
991: PetscErrorCode KSPSetInitialGuessNonzero(KSP ksp,PetscBool flg)
992: {
996: ksp->guess_zero = (PetscBool) !(int)flg;
997: return(0);
998: }
1002: /*@
1003: KSPGetInitialGuessNonzero - Determines whether the KSP solver is using
1004: a zero initial guess.
1006: Not Collective
1008: Input Parameter:
1009: . ksp - iterative context obtained from KSPCreate()
1011: Output Parameter:
1012: . flag - PETSC_TRUE if guess is nonzero, else PETSC_FALSE
1014: Level: intermediate
1016: .keywords: KSP, set, initial guess, nonzero
1018: .seealso: KSPSetInitialGuessNonzero(), KSPSetInitialGuessKnoll(), KSPGetInitialGuessKnoll()
1019: @*/
1020: PetscErrorCode KSPGetInitialGuessNonzero(KSP ksp,PetscBool *flag)
1021: {
1025: if (ksp->guess_zero) *flag = PETSC_FALSE;
1026: else *flag = PETSC_TRUE;
1027: return(0);
1028: }
1032: /*@
1033: KSPSetErrorIfNotConverged - Causes KSPSolve() to generate an error if the solver has not converged.
1035: Logically Collective on KSP
1037: Input Parameters:
1038: + ksp - iterative context obtained from KSPCreate()
1039: - flg - PETSC_TRUE indicates you want the error generated
1041: Options database keys:
1042: . -ksp_error_if_not_converged : this takes an optional truth value (0/1/no/yes/true/false)
1044: Level: intermediate
1046: Notes:
1047: Normally PETSc continues if a linear solver fails to converge, you can call KSPGetConvergedReason() after a KSPSolve()
1048: to determine if it has converged.
1050: .keywords: KSP, set, initial guess, nonzero
1052: .seealso: KSPGetInitialGuessNonzero(), KSPSetInitialGuessKnoll(), KSPGetInitialGuessKnoll(), KSPGetErrorIfNotConverged()
1053: @*/
1054: PetscErrorCode KSPSetErrorIfNotConverged(KSP ksp,PetscBool flg)
1055: {
1059: ksp->errorifnotconverged = flg;
1060: return(0);
1061: }
1065: /*@
1066: KSPGetErrorIfNotConverged - Will KSPSolve() generate an error if the solver does not converge?
1068: Not Collective
1070: Input Parameter:
1071: . ksp - iterative context obtained from KSPCreate()
1073: Output Parameter:
1074: . flag - PETSC_TRUE if it will generate an error, else PETSC_FALSE
1076: Level: intermediate
1078: .keywords: KSP, set, initial guess, nonzero
1080: .seealso: KSPSetInitialGuessNonzero(), KSPSetInitialGuessKnoll(), KSPGetInitialGuessKnoll(), KSPSetErrorIfNotConverged()
1081: @*/
1082: PetscErrorCode KSPGetErrorIfNotConverged(KSP ksp,PetscBool *flag)
1083: {
1087: *flag = ksp->errorifnotconverged;
1088: return(0);
1089: }
1093: /*@
1094: KSPSetInitialGuessKnoll - Tells the iterative solver to use PCApply(pc,b,..) to compute the initial guess (The Knoll trick)
1096: Logically Collective on KSP
1098: Input Parameters:
1099: + ksp - iterative context obtained from KSPCreate()
1100: - flg - PETSC_TRUE or PETSC_FALSE
1102: Level: advanced
1105: .keywords: KSP, set, initial guess, nonzero
1107: .seealso: KSPGetInitialGuessKnoll(), KSPSetInitialGuessNonzero(), KSPGetInitialGuessNonzero()
1108: @*/
1109: PetscErrorCode KSPSetInitialGuessKnoll(KSP ksp,PetscBool flg)
1110: {
1114: ksp->guess_knoll = flg;
1115: return(0);
1116: }
1120: /*@
1121: KSPGetInitialGuessKnoll - Determines whether the KSP solver is using the Knoll trick (using PCApply(pc,b,...) to compute
1122: the initial guess
1124: Not Collective
1126: Input Parameter:
1127: . ksp - iterative context obtained from KSPCreate()
1129: Output Parameter:
1130: . flag - PETSC_TRUE if using Knoll trick, else PETSC_FALSE
1132: Level: advanced
1134: .keywords: KSP, set, initial guess, nonzero
1136: .seealso: KSPSetInitialGuessKnoll(), KSPSetInitialGuessNonzero(), KSPGetInitialGuessNonzero()
1137: @*/
1138: PetscErrorCode KSPGetInitialGuessKnoll(KSP ksp,PetscBool *flag)
1139: {
1143: *flag = ksp->guess_knoll;
1144: return(0);
1145: }
1149: /*@
1150: KSPGetComputeSingularValues - Gets the flag indicating whether the extreme singular
1151: values will be calculated via a Lanczos or Arnoldi process as the linear
1152: system is solved.
1154: Not Collective
1156: Input Parameter:
1157: . ksp - iterative context obtained from KSPCreate()
1159: Output Parameter:
1160: . flg - PETSC_TRUE or PETSC_FALSE
1162: Options Database Key:
1163: . -ksp_monitor_singular_value - Activates KSPSetComputeSingularValues()
1165: Notes:
1166: Currently this option is not valid for all iterative methods.
1168: Many users may just want to use the monitoring routine
1169: KSPMonitorSingularValue() (which can be set with option -ksp_monitor_singular_value)
1170: to print the singular values at each iteration of the linear solve.
1172: Level: advanced
1174: .keywords: KSP, set, compute, singular values
1176: .seealso: KSPComputeExtremeSingularValues(), KSPMonitorSingularValue()
1177: @*/
1178: PetscErrorCode KSPGetComputeSingularValues(KSP ksp,PetscBool *flg)
1179: {
1183: *flg = ksp->calc_sings;
1184: return(0);
1185: }
1189: /*@
1190: KSPSetComputeSingularValues - Sets a flag so that the extreme singular
1191: values will be calculated via a Lanczos or Arnoldi process as the linear
1192: system is solved.
1194: Logically Collective on KSP
1196: Input Parameters:
1197: + ksp - iterative context obtained from KSPCreate()
1198: - flg - PETSC_TRUE or PETSC_FALSE
1200: Options Database Key:
1201: . -ksp_monitor_singular_value - Activates KSPSetComputeSingularValues()
1203: Notes:
1204: Currently this option is not valid for all iterative methods.
1206: Many users may just want to use the monitoring routine
1207: KSPMonitorSingularValue() (which can be set with option -ksp_monitor_singular_value)
1208: to print the singular values at each iteration of the linear solve.
1210: Level: advanced
1212: .keywords: KSP, set, compute, singular values
1214: .seealso: KSPComputeExtremeSingularValues(), KSPMonitorSingularValue()
1215: @*/
1216: PetscErrorCode KSPSetComputeSingularValues(KSP ksp,PetscBool flg)
1217: {
1221: ksp->calc_sings = flg;
1222: return(0);
1223: }
1227: /*@
1228: KSPGetComputeEigenvalues - Gets the flag indicating that the extreme eigenvalues
1229: values will be calculated via a Lanczos or Arnoldi process as the linear
1230: system is solved.
1232: Not Collective
1234: Input Parameter:
1235: . ksp - iterative context obtained from KSPCreate()
1237: Output Parameter:
1238: . flg - PETSC_TRUE or PETSC_FALSE
1240: Notes:
1241: Currently this option is not valid for all iterative methods.
1243: Level: advanced
1245: .keywords: KSP, set, compute, eigenvalues
1247: .seealso: KSPComputeEigenvalues(), KSPComputeEigenvaluesExplicitly()
1248: @*/
1249: PetscErrorCode KSPGetComputeEigenvalues(KSP ksp,PetscBool *flg)
1250: {
1254: *flg = ksp->calc_sings;
1255: return(0);
1256: }
1260: /*@
1261: KSPSetComputeEigenvalues - Sets a flag so that the extreme eigenvalues
1262: values will be calculated via a Lanczos or Arnoldi process as the linear
1263: system is solved.
1265: Logically Collective on KSP
1267: Input Parameters:
1268: + ksp - iterative context obtained from KSPCreate()
1269: - flg - PETSC_TRUE or PETSC_FALSE
1271: Notes:
1272: Currently this option is not valid for all iterative methods.
1274: Level: advanced
1276: .keywords: KSP, set, compute, eigenvalues
1278: .seealso: KSPComputeEigenvalues(), KSPComputeEigenvaluesExplicitly()
1279: @*/
1280: PetscErrorCode KSPSetComputeEigenvalues(KSP ksp,PetscBool flg)
1281: {
1285: ksp->calc_sings = flg;
1286: return(0);
1287: }
1291: /*@
1292: KSPGetRhs - Gets the right-hand-side vector for the linear system to
1293: be solved.
1295: Not Collective
1297: Input Parameter:
1298: . ksp - iterative context obtained from KSPCreate()
1300: Output Parameter:
1301: . r - right-hand-side vector
1303: Level: developer
1305: .keywords: KSP, get, right-hand-side, rhs
1307: .seealso: KSPGetSolution(), KSPSolve()
1308: @*/
1309: PetscErrorCode KSPGetRhs(KSP ksp,Vec *r)
1310: {
1314: *r = ksp->vec_rhs;
1315: return(0);
1316: }
1320: /*@
1321: KSPGetSolution - Gets the location of the solution for the
1322: linear system to be solved. Note that this may not be where the solution
1323: is stored during the iterative process; see KSPBuildSolution().
1325: Not Collective
1327: Input Parameters:
1328: . ksp - iterative context obtained from KSPCreate()
1330: Output Parameters:
1331: . v - solution vector
1333: Level: developer
1335: .keywords: KSP, get, solution
1337: .seealso: KSPGetRhs(), KSPBuildSolution(), KSPSolve()
1338: @*/
1339: PetscErrorCode KSPGetSolution(KSP ksp,Vec *v)
1340: {
1344: *v = ksp->vec_sol;
1345: return(0);
1346: }
1350: /*@
1351: KSPSetPC - Sets the preconditioner to be used to calculate the
1352: application of the preconditioner on a vector.
1354: Collective on KSP
1356: Input Parameters:
1357: + ksp - iterative context obtained from KSPCreate()
1358: - pc - the preconditioner object
1360: Notes:
1361: Use KSPGetPC() to retrieve the preconditioner context (for example,
1362: to free it at the end of the computations).
1364: Level: developer
1366: .keywords: KSP, set, precondition, Binv
1368: .seealso: KSPGetPC()
1369: @*/
1370: PetscErrorCode KSPSetPC(KSP ksp,PC pc)
1371: {
1378: PetscObjectReference((PetscObject)pc);
1379: PCDestroy(&ksp->pc);
1380: ksp->pc = pc;
1381: PetscLogObjectParent((PetscObject)ksp,(PetscObject)ksp->pc);
1382: return(0);
1383: }
1387: /*@
1388: KSPGetPC - Returns a pointer to the preconditioner context
1389: set with KSPSetPC().
1391: Not Collective
1393: Input Parameters:
1394: . ksp - iterative context obtained from KSPCreate()
1396: Output Parameter:
1397: . pc - preconditioner context
1399: Level: developer
1401: .keywords: KSP, get, preconditioner, Binv
1403: .seealso: KSPSetPC()
1404: @*/
1405: PetscErrorCode KSPGetPC(KSP ksp,PC *pc)
1406: {
1412: if (!ksp->pc) {
1413: PCCreate(PetscObjectComm((PetscObject)ksp),&ksp->pc);
1414: PetscObjectIncrementTabLevel((PetscObject)ksp->pc,(PetscObject)ksp,0);
1415: PetscLogObjectParent((PetscObject)ksp,(PetscObject)ksp->pc);
1416: }
1417: *pc = ksp->pc;
1418: return(0);
1419: }
1423: /*@
1424: KSPMonitor - runs the user provided monitor routines, if they exist
1426: Collective on KSP
1428: Input Parameters:
1429: + ksp - iterative context obtained from KSPCreate()
1430: . it - iteration number
1431: - rnorm - relative norm of the residual
1433: Notes:
1434: This routine is called by the KSP implementations.
1435: It does not typically need to be called by the user.
1437: Level: developer
1439: .seealso: KSPMonitorSet()
1440: @*/
1441: PetscErrorCode KSPMonitor(KSP ksp,PetscInt it,PetscReal rnorm)
1442: {
1443: PetscInt i, n = ksp->numbermonitors;
1447: for (i=0; i<n; i++) {
1448: (*ksp->monitor[i])(ksp,it,rnorm,ksp->monitorcontext[i]);
1449: }
1450: return(0);
1451: }
1455: /*@C
1456: KSPMonitorSet - Sets an ADDITIONAL function to be called at every iteration to monitor
1457: the residual/error etc.
1459: Logically Collective on KSP
1461: Input Parameters:
1462: + ksp - iterative context obtained from KSPCreate()
1463: . monitor - pointer to function (if this is NULL, it turns off monitoring
1464: . mctx - [optional] context for private data for the
1465: monitor routine (use NULL if no context is desired)
1466: - monitordestroy - [optional] routine that frees monitor context
1467: (may be NULL)
1469: Calling Sequence of monitor:
1470: $ monitor (KSP ksp, int it, PetscReal rnorm, void *mctx)
1472: + ksp - iterative context obtained from KSPCreate()
1473: . it - iteration number
1474: . rnorm - (estimated) 2-norm of (preconditioned) residual
1475: - mctx - optional monitoring context, as set by KSPMonitorSet()
1477: Options Database Keys:
1478: + -ksp_monitor - sets KSPMonitorDefault()
1479: . -ksp_monitor_true_residual - sets KSPMonitorTrueResidualNorm()
1480: . -ksp_monitor_max - sets KSPMonitorTrueResidualMaxNorm()
1481: . -ksp_monitor_lg_residualnorm - sets line graph monitor,
1482: uses KSPMonitorLGResidualNormCreate()
1483: . -ksp_monitor_lg_true_residualnorm - sets line graph monitor,
1484: uses KSPMonitorLGResidualNormCreate()
1485: . -ksp_monitor_singular_value - sets KSPMonitorSingularValue()
1486: - -ksp_monitor_cancel - cancels all monitors that have
1487: been hardwired into a code by
1488: calls to KSPMonitorSet(), but
1489: does not cancel those set via
1490: the options database.
1492: Notes:
1493: The default is to do nothing. To print the residual, or preconditioned
1494: residual if KSPSetNormType(ksp,KSP_NORM_PRECONDITIONED) was called, use
1495: KSPMonitorDefault() as the monitoring routine, with a null monitoring
1496: context.
1498: Several different monitoring routines may be set by calling
1499: KSPMonitorSet() multiple times; all will be called in the
1500: order in which they were set.
1502: Fortran notes: Only a single monitor function can be set for each KSP object
1504: Level: beginner
1506: .keywords: KSP, set, monitor
1508: .seealso: KSPMonitorDefault(), KSPMonitorLGResidualNormCreate(), KSPMonitorCancel()
1509: @*/
1510: PetscErrorCode KSPMonitorSet(KSP ksp,PetscErrorCode (*monitor)(KSP,PetscInt,PetscReal,void*),void *mctx,PetscErrorCode (*monitordestroy)(void**))
1511: {
1512: PetscInt i;
1517: if (ksp->numbermonitors >= MAXKSPMONITORS) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Too many KSP monitors set");
1518: for (i=0; i<ksp->numbermonitors;i++) {
1519: if (monitor == ksp->monitor[i] && monitordestroy == ksp->monitordestroy[i] && mctx == ksp->monitorcontext[i]) {
1520: if (monitordestroy) {
1521: (*monitordestroy)(&mctx);
1522: }
1523: return(0);
1524: }
1525: }
1526: ksp->monitor[ksp->numbermonitors] = monitor;
1527: ksp->monitordestroy[ksp->numbermonitors] = monitordestroy;
1528: ksp->monitorcontext[ksp->numbermonitors++] = (void*)mctx;
1529: return(0);
1530: }
1534: /*@
1535: KSPMonitorCancel - Clears all monitors for a KSP object.
1537: Logically Collective on KSP
1539: Input Parameters:
1540: . ksp - iterative context obtained from KSPCreate()
1542: Options Database Key:
1543: . -ksp_monitor_cancel - Cancels all monitors that have
1544: been hardwired into a code by calls to KSPMonitorSet(),
1545: but does not cancel those set via the options database.
1547: Level: intermediate
1549: .keywords: KSP, set, monitor
1551: .seealso: KSPMonitorDefault(), KSPMonitorLGResidualNormCreate(), KSPMonitorSet()
1552: @*/
1553: PetscErrorCode KSPMonitorCancel(KSP ksp)
1554: {
1556: PetscInt i;
1560: for (i=0; i<ksp->numbermonitors; i++) {
1561: if (ksp->monitordestroy[i]) {
1562: (*ksp->monitordestroy[i])(&ksp->monitorcontext[i]);
1563: }
1564: }
1565: ksp->numbermonitors = 0;
1566: return(0);
1567: }
1571: /*@C
1572: KSPGetMonitorContext - Gets the monitoring context, as set by
1573: KSPMonitorSet() for the FIRST monitor only.
1575: Not Collective
1577: Input Parameter:
1578: . ksp - iterative context obtained from KSPCreate()
1580: Output Parameter:
1581: . ctx - monitoring context
1583: Level: intermediate
1585: .keywords: KSP, get, monitor, context
1587: .seealso: KSPMonitorDefault(), KSPMonitorLGResidualNormCreate()
1588: @*/
1589: PetscErrorCode KSPGetMonitorContext(KSP ksp,void **ctx)
1590: {
1593: *ctx = (ksp->monitorcontext[0]);
1594: return(0);
1595: }
1599: /*@
1600: KSPSetResidualHistory - Sets the array used to hold the residual history.
1601: If set, this array will contain the residual norms computed at each
1602: iteration of the solver.
1604: Not Collective
1606: Input Parameters:
1607: + ksp - iterative context obtained from KSPCreate()
1608: . a - array to hold history
1609: . na - size of a
1610: - reset - PETSC_TRUE indicates the history counter is reset to zero
1611: for each new linear solve
1613: Level: advanced
1615: Notes: The array is NOT freed by PETSc so the user needs to keep track of
1616: it and destroy once the KSP object is destroyed.
1618: If 'a' is NULL then space is allocated for the history. If 'na' PETSC_DECIDE or PETSC_DEFAULT then a
1619: default array of length 10000 is allocated.
1621: .keywords: KSP, set, residual, history, norm
1623: .seealso: KSPGetResidualHistory()
1625: @*/
1626: PetscErrorCode KSPSetResidualHistory(KSP ksp,PetscReal a[],PetscInt na,PetscBool reset)
1627: {
1633: PetscFree(ksp->res_hist_alloc);
1634: if (na != PETSC_DECIDE && na != PETSC_DEFAULT && a) {
1635: ksp->res_hist = a;
1636: ksp->res_hist_max = na;
1637: } else {
1638: if (na != PETSC_DECIDE && na != PETSC_DEFAULT) ksp->res_hist_max = na;
1639: else ksp->res_hist_max = 10000; /* like default ksp->max_it */
1640: PetscMalloc1(ksp->res_hist_max,&ksp->res_hist_alloc);
1642: ksp->res_hist = ksp->res_hist_alloc;
1643: }
1644: ksp->res_hist_len = 0;
1645: ksp->res_hist_reset = reset;
1646: return(0);
1647: }
1651: /*@C
1652: KSPGetResidualHistory - Gets the array used to hold the residual history
1653: and the number of residuals it contains.
1655: Not Collective
1657: Input Parameter:
1658: . ksp - iterative context obtained from KSPCreate()
1660: Output Parameters:
1661: + a - pointer to array to hold history (or NULL)
1662: - na - number of used entries in a (or NULL)
1664: Level: advanced
1666: Notes:
1667: Can only be called after a KSPSetResidualHistory() otherwise a and na are set to zero
1669: The Fortran version of this routine has a calling sequence
1670: $ call KSPGetResidualHistory(KSP ksp, integer na, integer ierr)
1671: note that you have passed a Fortran array into KSPSetResidualHistory() and you need
1672: to access the residual values from this Fortran array you provided. Only the na (number of
1673: residual norms currently held) is set.
1675: .keywords: KSP, get, residual, history, norm
1677: .seealso: KSPGetResidualHistory()
1679: @*/
1680: PetscErrorCode KSPGetResidualHistory(KSP ksp,PetscReal *a[],PetscInt *na)
1681: {
1684: if (a) *a = ksp->res_hist;
1685: if (na) *na = ksp->res_hist_len;
1686: return(0);
1687: }
1691: /*@C
1692: KSPSetConvergenceTest - Sets the function to be used to determine
1693: convergence.
1695: Logically Collective on KSP
1697: Input Parameters:
1698: + ksp - iterative context obtained from KSPCreate()
1699: . converge - pointer to int function
1700: . cctx - context for private data for the convergence routine (may be null)
1701: - destroy - a routine for destroying the context (may be null)
1703: Calling sequence of converge:
1704: $ converge (KSP ksp, int it, PetscReal rnorm, KSPConvergedReason *reason,void *mctx)
1706: + ksp - iterative context obtained from KSPCreate()
1707: . it - iteration number
1708: . rnorm - (estimated) 2-norm of (preconditioned) residual
1709: . reason - the reason why it has converged or diverged
1710: - cctx - optional convergence context, as set by KSPSetConvergenceTest()
1713: Notes:
1714: Must be called after the KSP type has been set so put this after
1715: a call to KSPSetType(), or KSPSetFromOptions().
1717: The default convergence test, KSPConvergedDefault(), aborts if the
1718: residual grows to more than 10000 times the initial residual.
1720: The default is a combination of relative and absolute tolerances.
1721: The residual value that is tested may be an approximation; routines
1722: that need exact values should compute them.
1724: In the default PETSc convergence test, the precise values of reason
1725: are macros such as KSP_CONVERGED_RTOL, which are defined in petscksp.h.
1727: Level: advanced
1729: .keywords: KSP, set, convergence, test, context
1731: .seealso: KSPConvergedDefault(), KSPGetConvergenceContext(), KSPSetTolerances()
1732: @*/
1733: PetscErrorCode KSPSetConvergenceTest(KSP ksp,PetscErrorCode (*converge)(KSP,PetscInt,PetscReal,KSPConvergedReason*,void*),void *cctx,PetscErrorCode (*destroy)(void*))
1734: {
1739: if (ksp->convergeddestroy) {
1740: (*ksp->convergeddestroy)(ksp->cnvP);
1741: }
1742: ksp->converged = converge;
1743: ksp->convergeddestroy = destroy;
1744: ksp->cnvP = (void*)cctx;
1745: return(0);
1746: }
1750: /*@C
1751: KSPGetConvergenceContext - Gets the convergence context set with
1752: KSPSetConvergenceTest().
1754: Not Collective
1756: Input Parameter:
1757: . ksp - iterative context obtained from KSPCreate()
1759: Output Parameter:
1760: . ctx - monitoring context
1762: Level: advanced
1764: .keywords: KSP, get, convergence, test, context
1766: .seealso: KSPConvergedDefault(), KSPSetConvergenceTest()
1767: @*/
1768: PetscErrorCode KSPGetConvergenceContext(KSP ksp,void **ctx)
1769: {
1772: *ctx = ksp->cnvP;
1773: return(0);
1774: }
1778: /*@C
1779: KSPBuildSolution - Builds the approximate solution in a vector provided.
1780: This routine is NOT commonly needed (see KSPSolve()).
1782: Collective on KSP
1784: Input Parameter:
1785: . ctx - iterative context obtained from KSPCreate()
1787: Output Parameter:
1788: Provide exactly one of
1789: + v - location to stash solution.
1790: - V - the solution is returned in this location. This vector is created
1791: internally. This vector should NOT be destroyed by the user with
1792: VecDestroy().
1794: Notes:
1795: This routine can be used in one of two ways
1796: .vb
1797: KSPBuildSolution(ksp,NULL,&V);
1798: or
1799: KSPBuildSolution(ksp,v,NULL); or KSPBuildSolution(ksp,v,&v);
1800: .ve
1801: In the first case an internal vector is allocated to store the solution
1802: (the user cannot destroy this vector). In the second case the solution
1803: is generated in the vector that the user provides. Note that for certain
1804: methods, such as KSPCG, the second case requires a copy of the solution,
1805: while in the first case the call is essentially free since it simply
1806: returns the vector where the solution already is stored. For some methods
1807: like GMRES this is a reasonably expensive operation and should only be
1808: used in truly needed.
1810: Level: advanced
1812: .keywords: KSP, build, solution
1814: .seealso: KSPGetSolution(), KSPBuildResidual()
1815: @*/
1816: PetscErrorCode KSPBuildSolution(KSP ksp,Vec v,Vec *V)
1817: {
1822: if (!V && !v) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_WRONG,"Must provide either v or V");
1823: if (!V) V = &v;
1824: (*ksp->ops->buildsolution)(ksp,v,V);
1825: return(0);
1826: }
1830: /*@C
1831: KSPBuildResidual - Builds the residual in a vector provided.
1833: Collective on KSP
1835: Input Parameter:
1836: . ksp - iterative context obtained from KSPCreate()
1838: Output Parameters:
1839: + v - optional location to stash residual. If v is not provided,
1840: then a location is generated.
1841: . t - work vector. If not provided then one is generated.
1842: - V - the residual
1844: Notes:
1845: Regardless of whether or not v is provided, the residual is
1846: returned in V.
1848: Level: advanced
1850: .keywords: KSP, build, residual
1852: .seealso: KSPBuildSolution()
1853: @*/
1854: PetscErrorCode KSPBuildResidual(KSP ksp,Vec t,Vec v,Vec *V)
1855: {
1857: PetscBool flag = PETSC_FALSE;
1858: Vec w = v,tt = t;
1862: if (!w) {
1863: VecDuplicate(ksp->vec_rhs,&w);
1864: PetscLogObjectParent((PetscObject)ksp,(PetscObject)w);
1865: }
1866: if (!tt) {
1867: VecDuplicate(ksp->vec_sol,&tt); flag = PETSC_TRUE;
1868: PetscLogObjectParent((PetscObject)ksp,(PetscObject)tt);
1869: }
1870: (*ksp->ops->buildresidual)(ksp,tt,w,V);
1871: if (flag) {VecDestroy(&tt);}
1872: return(0);
1873: }
1877: /*@
1878: KSPSetDiagonalScale - Tells KSP to symmetrically diagonally scale the system
1879: before solving. This actually CHANGES the matrix (and right hand side).
1881: Logically Collective on KSP
1883: Input Parameter:
1884: + ksp - the KSP context
1885: - scale - PETSC_TRUE or PETSC_FALSE
1887: Options Database Key:
1888: + -ksp_diagonal_scale -
1889: - -ksp_diagonal_scale_fix - scale the matrix back AFTER the solve
1892: Notes: Scales the matrix by D^(-1/2) A D^(-1/2) [D^(1/2) x ] = D^(-1/2) b
1893: where D_{ii} is 1/abs(A_{ii}) unless A_{ii} is zero and then it is 1.
1895: BE CAREFUL with this routine: it actually scales the matrix and right
1896: hand side that define the system. After the system is solved the matrix
1897: and right hand side remain scaled unless you use KSPSetDiagonalScaleFix()
1899: This should NOT be used within the SNES solves if you are using a line
1900: search.
1902: If you use this with the PCType Eisenstat preconditioner than you can
1903: use the PCEisenstatNoDiagonalScaling() option, or -pc_eisenstat_no_diagonal_scaling
1904: to save some unneeded, redundant flops.
1906: Level: intermediate
1908: .keywords: KSP, set, options, prefix, database
1910: .seealso: KSPGetDiagonalScale(), KSPSetDiagonalScaleFix()
1911: @*/
1912: PetscErrorCode KSPSetDiagonalScale(KSP ksp,PetscBool scale)
1913: {
1917: ksp->dscale = scale;
1918: return(0);
1919: }
1923: /*@
1924: KSPGetDiagonalScale - Checks if KSP solver scales the matrix and
1925: right hand side
1927: Not Collective
1929: Input Parameter:
1930: . ksp - the KSP context
1932: Output Parameter:
1933: . scale - PETSC_TRUE or PETSC_FALSE
1935: Notes:
1936: BE CAREFUL with this routine: it actually scales the matrix and right
1937: hand side that define the system. After the system is solved the matrix
1938: and right hand side remain scaled unless you use KSPSetDiagonalScaleFix()
1940: Level: intermediate
1942: .keywords: KSP, set, options, prefix, database
1944: .seealso: KSPSetDiagonalScale(), KSPSetDiagonalScaleFix()
1945: @*/
1946: PetscErrorCode KSPGetDiagonalScale(KSP ksp,PetscBool *scale)
1947: {
1951: *scale = ksp->dscale;
1952: return(0);
1953: }
1957: /*@
1958: KSPSetDiagonalScaleFix - Tells KSP to diagonally scale the system
1959: back after solving.
1961: Logically Collective on KSP
1963: Input Parameter:
1964: + ksp - the KSP context
1965: - fix - PETSC_TRUE to scale back after the system solve, PETSC_FALSE to not
1966: rescale (default)
1968: Notes:
1969: Must be called after KSPSetDiagonalScale()
1971: Using this will slow things down, because it rescales the matrix before and
1972: after each linear solve. This is intended mainly for testing to allow one
1973: to easily get back the original system to make sure the solution computed is
1974: accurate enough.
1976: Level: intermediate
1978: .keywords: KSP, set, options, prefix, database
1980: .seealso: KSPGetDiagonalScale(), KSPSetDiagonalScale(), KSPGetDiagonalScaleFix()
1981: @*/
1982: PetscErrorCode KSPSetDiagonalScaleFix(KSP ksp,PetscBool fix)
1983: {
1987: ksp->dscalefix = fix;
1988: return(0);
1989: }
1993: /*@
1994: KSPGetDiagonalScaleFix - Determines if KSP diagonally scales the system
1995: back after solving.
1997: Not Collective
1999: Input Parameter:
2000: . ksp - the KSP context
2002: Output Parameter:
2003: . fix - PETSC_TRUE to scale back after the system solve, PETSC_FALSE to not
2004: rescale (default)
2006: Notes:
2007: Must be called after KSPSetDiagonalScale()
2009: If PETSC_TRUE will slow things down, because it rescales the matrix before and
2010: after each linear solve. This is intended mainly for testing to allow one
2011: to easily get back the original system to make sure the solution computed is
2012: accurate enough.
2014: Level: intermediate
2016: .keywords: KSP, set, options, prefix, database
2018: .seealso: KSPGetDiagonalScale(), KSPSetDiagonalScale(), KSPSetDiagonalScaleFix()
2019: @*/
2020: PetscErrorCode KSPGetDiagonalScaleFix(KSP ksp,PetscBool *fix)
2021: {
2025: *fix = ksp->dscalefix;
2026: return(0);
2027: }
2031: /*@C
2032: KSPSetComputeOperators - set routine to compute the linear operators
2034: Logically Collective
2036: Input Arguments:
2037: + ksp - the KSP context
2038: . func - function to compute the operators
2039: - ctx - optional context
2041: Calling sequence of func:
2042: $ func(KSP ksp,Mat *A,Mat *B,MatStructure *mstruct,void *ctx)
2044: + ksp - the KSP context
2045: . A - the linear operator
2046: . B - preconditioning matrix
2047: . mstruct - flag indicating structure, same as in KSPSetOperators(), one of SAME_NONZERO_PATTERN,DIFFERENT_NONZERO_PATTERN,SAME_PRECONDITIONER
2048: - ctx - optional user-provided context
2050: Level: beginner
2052: .seealso: KSPSetOperators(), DMKSPSetComputeOperators()
2053: @*/
2054: PetscErrorCode KSPSetComputeOperators(KSP ksp,PetscErrorCode (*func)(KSP,Mat,Mat,MatStructure*,void*),void *ctx)
2055: {
2057: DM dm;
2061: KSPGetDM(ksp,&dm);
2062: DMKSPSetComputeOperators(dm,func,ctx);
2063: if (ksp->setupstage == KSP_SETUP_NEWRHS) ksp->setupstage = KSP_SETUP_NEWMATRIX;
2064: return(0);
2065: }
2069: /*@C
2070: KSPSetComputeRHS - set routine to compute the right hand side of the linear system
2072: Logically Collective
2074: Input Arguments:
2075: + ksp - the KSP context
2076: . func - function to compute the right hand side
2077: - ctx - optional context
2079: Calling sequence of func:
2080: $ func(KSP ksp,Vec b,void *ctx)
2082: + ksp - the KSP context
2083: . b - right hand side of linear system
2084: - ctx - optional user-provided context
2086: Level: beginner
2088: .seealso: KSPSolve(), DMKSPSetComputeRHS()
2089: @*/
2090: PetscErrorCode KSPSetComputeRHS(KSP ksp,PetscErrorCode (*func)(KSP,Vec,void*),void *ctx)
2091: {
2093: DM dm;
2097: KSPGetDM(ksp,&dm);
2098: DMKSPSetComputeRHS(dm,func,ctx);
2099: return(0);
2100: }
2104: /*@C
2105: KSPSetComputeInitialGuess - set routine to compute the initial guess of the linear system
2107: Logically Collective
2109: Input Arguments:
2110: + ksp - the KSP context
2111: . func - function to compute the initial guess
2112: - ctx - optional context
2114: Calling sequence of func:
2115: $ func(KSP ksp,Vec x,void *ctx)
2117: + ksp - the KSP context
2118: . x - solution vector
2119: - ctx - optional user-provided context
2121: Level: beginner
2123: .seealso: KSPSolve(), DMKSPSetComputeInitialGuess()
2124: @*/
2125: PetscErrorCode KSPSetComputeInitialGuess(KSP ksp,PetscErrorCode (*func)(KSP,Vec,void*),void *ctx)
2126: {
2128: DM dm;
2132: KSPGetDM(ksp,&dm);
2133: DMKSPSetComputeInitialGuess(dm,func,ctx);
2134: return(0);
2135: }