1: /*
2: PEP routines related to options that can be set via the command-line
3: or procedurally.
5: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
6: SLEPc - Scalable Library for Eigenvalue Problem Computations
7: Copyright (c) 2002-2015, Universitat Politecnica de Valencia, Spain
9: This file is part of SLEPc.
11: SLEPc is free software: you can redistribute it and/or modify it under the
12: terms of version 3 of the GNU Lesser General Public License as published by
13: the Free Software Foundation.
15: SLEPc is distributed in the hope that it will be useful, but WITHOUT ANY
16: WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
17: FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for
18: more details.
20: You should have received a copy of the GNU Lesser General Public License
21: along with SLEPc. If not, see <http://www.gnu.org/licenses/>.
22: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
23: */
25: #include <slepc/private/pepimpl.h> /*I "slepcpep.h" I*/
29: /*@
30: PEPSetFromOptions - Sets PEP options from the options database.
31: This routine must be called before PEPSetUp() if the user is to be
32: allowed to set the solver type.
34: Collective on PEP 36: Input Parameters:
37: . pep - the polynomial eigensolver context
39: Notes:
40: To see all options, run your program with the -help option.
42: Level: beginner
43: @*/
44: PetscErrorCode PEPSetFromOptions(PEP pep) 45: {
46: PetscErrorCode ierr;
47: char type[256],monfilename[PETSC_MAX_PATH_LEN];
48: PetscBool flg,flg1,flg2,flg3,flg4;
49: PetscReal r,t;
50: PetscScalar s;
51: PetscInt i,j,k;
52: PetscViewer monviewer;
53: SlepcConvMonitor ctx;
57: PEPRegisterAll();
58: PetscObjectOptionsBegin((PetscObject)pep);
59: PetscOptionsFList("-pep_type","Polynomial Eigenvalue Problem method","PEPSetType",PEPList,(char*)(((PetscObject)pep)->type_name?((PetscObject)pep)->type_name:PEPTOAR),type,256,&flg);
60: if (flg) {
61: PEPSetType(pep,type);
62: } else if (!((PetscObject)pep)->type_name) {
63: PEPSetType(pep,PEPTOAR);
64: }
66: PetscOptionsBoolGroupBegin("-pep_general","general polynomial eigenvalue problem","PEPSetProblemType",&flg);
67: if (flg) { PEPSetProblemType(pep,PEP_GENERAL); }
68: PetscOptionsBoolGroup("-pep_hermitian","hermitian polynomial eigenvalue problem","PEPSetProblemType",&flg);
69: if (flg) { PEPSetProblemType(pep,PEP_HERMITIAN); }
70: PetscOptionsBoolGroupEnd("-pep_gyroscopic","gyroscopic polynomial eigenvalue problem","PEPSetProblemType",&flg);
71: if (flg) { PEPSetProblemType(pep,PEP_GYROSCOPIC); }
73: PetscOptionsEnum("-pep_scale","Scaling strategy","PEPSetScale",PEPScaleTypes,(PetscEnum)pep->scale,(PetscEnum*)&pep->scale,NULL);
75: r = pep->sfactor;
76: PetscOptionsReal("-pep_scale_factor","Scale factor","PEPSetScale",pep->sfactor,&r,&flg1);
77: j = pep->sits;
78: PetscOptionsInt("-pep_scale_its","Number of iterations in diagonal scaling","PEPSetScale",pep->sits,&j,&flg2);
79: t = pep->slambda;
80: PetscOptionsReal("-pep_scale_lambda","Estimate of eigenvalue (modulus) for diagonal scaling","PEPSetScale",pep->slambda,&t,&flg3);
81: if (flg1 || flg2 || flg3) {
82: PEPSetScale(pep,pep->scale,r,NULL,NULL,j,t);
83: }
85: PetscOptionsEnum("-pep_extract","Extraction method","PEPSetExtract",PEPExtractTypes,(PetscEnum)pep->extract,(PetscEnum*)&pep->extract,NULL);
87: PetscOptionsEnum("-pep_refine","Iterative refinement method","PEPSetRefine",PEPRefineTypes,(PetscEnum)pep->refine,(PetscEnum*)&pep->refine,NULL);
89: i = pep->npart;
90: PetscOptionsInt("-pep_refine_partitions","Number of partitions of the communicator for iterative refinement","PEPSetRefine",pep->npart,&i,&flg1);
91: r = pep->rtol;
92: PetscOptionsReal("-pep_refine_tol","Tolerance for iterative refinement","PEPSetRefine",pep->rtol,&r,&flg2);
93: j = pep->rits;
94: PetscOptionsInt("-pep_refine_its","Maximum number of iterations for iterative refinement","PEPSetRefine",pep->rits,&j,&flg3);
95: flg = pep->schur;
96: PetscOptionsBool("-pep_refine_schur","Use Schur complement for iterative refinement","PEPSetRefine",pep->schur,&flg,&flg4);
97: if (flg1 || flg2 || flg3 || flg4) {
98: PEPSetRefine(pep,pep->refine,i,r,j,flg);
99: }
101: i = pep->max_it? pep->max_it: PETSC_DEFAULT;
102: PetscOptionsInt("-pep_max_it","Maximum number of iterations","PEPSetTolerances",pep->max_it,&i,&flg1);
103: r = pep->tol;
104: PetscOptionsReal("-pep_tol","Tolerance","PEPSetTolerances",pep->tol==PETSC_DEFAULT?SLEPC_DEFAULT_TOL:pep->tol,&r,&flg2);
105: if (flg1 || flg2) {
106: PEPSetTolerances(pep,r,i);
107: }
109: PetscOptionsBoolGroupBegin("-pep_conv_eig","Relative error convergence test","PEPSetConvergenceTest",&flg);
110: if (flg) { PEPSetConvergenceTest(pep,PEP_CONV_EIG); }
111: PetscOptionsBoolGroup("-pep_conv_linear","Convergence test related to the linearized eigenproblem","PEPSetConvergenceTest",&flg);
112: if (flg) { PEPSetConvergenceTest(pep,PEP_CONV_LINEAR); }
113: PetscOptionsBoolGroupBegin("-pep_conv_norm","Convergence test related to the matrix norms","PEPSetConvergenceTest",&flg);
114: if (flg) { PEPSetConvergenceTest(pep,PEP_CONV_NORM); }
115: PetscOptionsBoolGroup("-pep_conv_abs","Absolute error convergence test","PEPSetConvergenceTest",&flg);
116: if (flg) { PEPSetConvergenceTest(pep,PEP_CONV_ABS); }
117: PetscOptionsBoolGroupEnd("-pep_conv_user","User-defined convergence test","PEPSetConvergenceTest",&flg);
118: if (flg) { PEPSetConvergenceTest(pep,PEP_CONV_USER); }
120: i = pep->nev;
121: PetscOptionsInt("-pep_nev","Number of eigenvalues to compute","PEPSetDimensions",pep->nev,&i,&flg1);
122: j = pep->ncv? pep->ncv: PETSC_DEFAULT;
123: PetscOptionsInt("-pep_ncv","Number of basis vectors","PEPSetDimensions",pep->ncv,&j,&flg2);
124: k = pep->mpd? pep->mpd: PETSC_DEFAULT;
125: PetscOptionsInt("-pep_mpd","Maximum dimension of projected problem","PEPSetDimensions",pep->mpd,&k,&flg3);
126: if (flg1 || flg2 || flg3) {
127: PEPSetDimensions(pep,i,j,k);
128: }
130: PetscOptionsScalar("-pep_target","Value of the target","PEPSetTarget",pep->target,&s,&flg);
131: if (flg) {
132: PEPSetWhichEigenpairs(pep,PEP_TARGET_MAGNITUDE);
133: PEPSetTarget(pep,s);
134: }
136: PetscOptionsEnum("-pep_basis","Polynomial basis","PEPSetBasis",PEPBasisTypes,(PetscEnum)pep->basis,(PetscEnum*)&pep->basis,NULL);
138: /* -----------------------------------------------------------------------*/
139: /*
140: Cancels all monitors hardwired into code before call to PEPSetFromOptions()
141: */
142: flg = PETSC_FALSE;
143: PetscOptionsBool("-pep_monitor_cancel","Remove any hardwired monitor routines","PEPMonitorCancel",flg,&flg,NULL);
144: if (flg) {
145: PEPMonitorCancel(pep);
146: }
147: /*
148: Prints approximate eigenvalues and error estimates at each iteration
149: */
150: PetscOptionsString("-pep_monitor","Monitor first unconverged approximate eigenvalue and error estimate","PEPMonitorSet","stdout",monfilename,PETSC_MAX_PATH_LEN,&flg);
151: if (flg) {
152: PetscViewerASCIIOpen(PetscObjectComm((PetscObject)pep),monfilename,&monviewer);
153: PEPMonitorSet(pep,PEPMonitorFirst,monviewer,(PetscErrorCode (*)(void**))PetscViewerDestroy);
154: }
155: PetscOptionsString("-pep_monitor_conv","Monitor approximate eigenvalues and error estimates as they converge","PEPMonitorSet","stdout",monfilename,PETSC_MAX_PATH_LEN,&flg);
156: if (flg) {
157: PetscNew(&ctx);
158: PetscViewerASCIIOpen(PetscObjectComm((PetscObject)pep),monfilename,&ctx->viewer);
159: PEPMonitorSet(pep,PEPMonitorConverged,ctx,(PetscErrorCode (*)(void**))SlepcConvMonitorDestroy);
160: }
161: PetscOptionsString("-pep_monitor_all","Monitor approximate eigenvalues and error estimates","PEPMonitorSet","stdout",monfilename,PETSC_MAX_PATH_LEN,&flg);
162: if (flg) {
163: PetscViewerASCIIOpen(PetscObjectComm((PetscObject)pep),monfilename,&monviewer);
164: PEPMonitorSet(pep,PEPMonitorAll,monviewer,(PetscErrorCode (*)(void**))PetscViewerDestroy);
165: PEPSetTrackAll(pep,PETSC_TRUE);
166: }
167: flg = PETSC_FALSE;
168: PetscOptionsBool("-pep_monitor_lg","Monitor first unconverged approximate error estimate graphically","PEPMonitorSet",flg,&flg,NULL);
169: if (flg) {
170: PEPMonitorSet(pep,PEPMonitorLG,NULL,NULL);
171: }
172: flg = PETSC_FALSE;
173: PetscOptionsBool("-pep_monitor_lg_all","Monitor error estimates graphically","PEPMonitorSet",flg,&flg,NULL);
174: if (flg) {
175: PEPMonitorSet(pep,PEPMonitorLGAll,NULL,NULL);
176: PEPSetTrackAll(pep,PETSC_TRUE);
177: }
178: /* -----------------------------------------------------------------------*/
180: PetscOptionsBoolGroupBegin("-pep_largest_magnitude","compute largest eigenvalues in magnitude","PEPSetWhichEigenpairs",&flg);
181: if (flg) { PEPSetWhichEigenpairs(pep,PEP_LARGEST_MAGNITUDE); }
182: PetscOptionsBoolGroup("-pep_smallest_magnitude","compute smallest eigenvalues in magnitude","PEPSetWhichEigenpairs",&flg);
183: if (flg) { PEPSetWhichEigenpairs(pep,PEP_SMALLEST_MAGNITUDE); }
184: PetscOptionsBoolGroup("-pep_largest_real","compute largest real parts","PEPSetWhichEigenpairs",&flg);
185: if (flg) { PEPSetWhichEigenpairs(pep,PEP_LARGEST_REAL); }
186: PetscOptionsBoolGroup("-pep_smallest_real","compute smallest real parts","PEPSetWhichEigenpairs",&flg);
187: if (flg) { PEPSetWhichEigenpairs(pep,PEP_SMALLEST_REAL); }
188: PetscOptionsBoolGroup("-pep_largest_imaginary","compute largest imaginary parts","PEPSetWhichEigenpairs",&flg);
189: if (flg) { PEPSetWhichEigenpairs(pep,PEP_LARGEST_IMAGINARY); }
190: PetscOptionsBoolGroup("-pep_smallest_imaginary","compute smallest imaginary parts","PEPSetWhichEigenpairs",&flg);
191: if (flg) { PEPSetWhichEigenpairs(pep,PEP_SMALLEST_IMAGINARY); }
192: PetscOptionsBoolGroup("-pep_target_magnitude","compute nearest eigenvalues to target","PEPSetWhichEigenpairs",&flg);
193: if (flg) { PEPSetWhichEigenpairs(pep,PEP_TARGET_MAGNITUDE); }
194: PetscOptionsBoolGroup("-pep_target_real","compute eigenvalues with real parts close to target","PEPSetWhichEigenpairs",&flg);
195: if (flg) { PEPSetWhichEigenpairs(pep,PEP_TARGET_REAL); }
196: PetscOptionsBoolGroupEnd("-pep_target_imaginary","compute eigenvalues with imaginary parts close to target","PEPSetWhichEigenpairs",&flg);
197: if (flg) { PEPSetWhichEigenpairs(pep,PEP_TARGET_IMAGINARY); }
199: PetscOptionsName("-pep_view","Print detailed information on solver used","PEPView",0);
200: PetscOptionsName("-pep_view_vectors","View computed eigenvectors","PEPVectorsView",0);
201: PetscOptionsName("-pep_view_values","View computed eigenvalues","PEPValuesView",0);
202: PetscOptionsName("-pep_converged_reason","Print reason for convergence, and number of iterations","PEPReasonView",0);
203: PetscOptionsName("-pep_error_absolute","Print absolute errors of each eigenpair","PEPErrorView",0);
204: PetscOptionsName("-pep_error_relative","Print relative errors of each eigenpair","PEPErrorView",0);
205: PetscOptionsName("-pep_error_backward","Print backward errors of each eigenpair","PEPErrorView",0);
207: if (pep->ops->setfromoptions) {
208: (*pep->ops->setfromoptions)(PetscOptionsObject,pep);
209: }
210: PetscObjectProcessOptionsHandlers((PetscObject)pep);
211: PetscOptionsEnd();
213: if (!pep->V) { PEPGetBV(pep,&pep->V); }
214: BVSetFromOptions(pep->V);
215: if (!pep->rg) { PEPGetRG(pep,&pep->rg); }
216: RGSetFromOptions(pep->rg);
217: if (!pep->ds) { PEPGetDS(pep,&pep->ds); }
218: DSSetFromOptions(pep->ds);
219: if (!pep->st) { PEPGetST(pep,&pep->st); }
220: STSetFromOptions(pep->st);
221: if (!pep->refineksp) { PEPRefineGetKSP(pep,&pep->refineksp); }
222: KSPSetFromOptions(pep->refineksp);
223: PetscRandomSetFromOptions(pep->rand);
224: return(0);
225: }
229: /*@
230: PEPGetTolerances - Gets the tolerance and maximum iteration count used
231: by the PEP convergence tests.
233: Not Collective
235: Input Parameter:
236: . pep - the polynomial eigensolver context
238: Output Parameters:
239: + tol - the convergence tolerance
240: - maxits - maximum number of iterations
242: Notes:
243: The user can specify NULL for any parameter that is not needed.
245: Level: intermediate
247: .seealso: PEPSetTolerances()
248: @*/
249: PetscErrorCode PEPGetTolerances(PEP pep,PetscReal *tol,PetscInt *maxits)250: {
253: if (tol) *tol = pep->tol;
254: if (maxits) *maxits = pep->max_it;
255: return(0);
256: }
260: /*@
261: PEPSetTolerances - Sets the tolerance and maximum iteration count used
262: by the PEP convergence tests.
264: Logically Collective on PEP266: Input Parameters:
267: + pep - the polynomial eigensolver context
268: . tol - the convergence tolerance
269: - maxits - maximum number of iterations to use
271: Options Database Keys:
272: + -pep_tol <tol> - Sets the convergence tolerance
273: - -pep_max_it <maxits> - Sets the maximum number of iterations allowed
275: Notes:
276: Use PETSC_DEFAULT for either argument to assign a reasonably good value.
278: Level: intermediate
280: .seealso: PEPGetTolerances()
281: @*/
282: PetscErrorCode PEPSetTolerances(PEP pep,PetscReal tol,PetscInt maxits)283: {
288: if (tol == PETSC_DEFAULT) {
289: pep->tol = PETSC_DEFAULT;
290: pep->state = PEP_STATE_INITIAL;
291: } else {
292: if (tol <= 0.0) SETERRQ(PetscObjectComm((PetscObject)pep),PETSC_ERR_ARG_OUTOFRANGE,"Illegal value of tol. Must be > 0");
293: pep->tol = tol;
294: }
295: if (maxits == PETSC_DEFAULT || maxits == PETSC_DECIDE) {
296: pep->max_it = 0;
297: pep->state = PEP_STATE_INITIAL;
298: } else {
299: if (maxits <= 0) SETERRQ(PetscObjectComm((PetscObject)pep),PETSC_ERR_ARG_OUTOFRANGE,"Illegal value of maxits. Must be > 0");
300: pep->max_it = maxits;
301: }
302: return(0);
303: }
307: /*@
308: PEPGetDimensions - Gets the number of eigenvalues to compute
309: and the dimension of the subspace.
311: Not Collective
313: Input Parameter:
314: . pep - the polynomial eigensolver context
316: Output Parameters:
317: + nev - number of eigenvalues to compute
318: . ncv - the maximum dimension of the subspace to be used by the solver
319: - mpd - the maximum dimension allowed for the projected problem
321: Notes:
322: The user can specify NULL for any parameter that is not needed.
324: Level: intermediate
326: .seealso: PEPSetDimensions()
327: @*/
328: PetscErrorCode PEPGetDimensions(PEP pep,PetscInt *nev,PetscInt *ncv,PetscInt *mpd)329: {
332: if (nev) *nev = pep->nev;
333: if (ncv) *ncv = pep->ncv;
334: if (mpd) *mpd = pep->mpd;
335: return(0);
336: }
340: /*@
341: PEPSetDimensions - Sets the number of eigenvalues to compute
342: and the dimension of the subspace.
344: Logically Collective on PEP346: Input Parameters:
347: + pep - the polynomial eigensolver context
348: . nev - number of eigenvalues to compute
349: . ncv - the maximum dimension of the subspace to be used by the solver
350: - mpd - the maximum dimension allowed for the projected problem
352: Options Database Keys:
353: + -pep_nev <nev> - Sets the number of eigenvalues
354: . -pep_ncv <ncv> - Sets the dimension of the subspace
355: - -pep_mpd <mpd> - Sets the maximum projected dimension
357: Notes:
358: Use PETSC_DEFAULT for ncv and mpd to assign a reasonably good value, which is
359: dependent on the solution method.
361: The parameters ncv and mpd are intimately related, so that the user is advised
362: to set one of them at most. Normal usage is that
363: (a) in cases where nev is small, the user sets ncv (a reasonable default is 2*nev); and
364: (b) in cases where nev is large, the user sets mpd.
366: The value of ncv should always be between nev and (nev+mpd), typically
367: ncv=nev+mpd. If nev is not too large, mpd=nev is a reasonable choice, otherwise
368: a smaller value should be used.
370: Level: intermediate
372: .seealso: PEPGetDimensions()
373: @*/
374: PetscErrorCode PEPSetDimensions(PEP pep,PetscInt nev,PetscInt ncv,PetscInt mpd)375: {
381: if (nev<1) SETERRQ(PetscObjectComm((PetscObject)pep),PETSC_ERR_ARG_OUTOFRANGE,"Illegal value of nev. Must be > 0");
382: pep->nev = nev;
383: if (ncv == PETSC_DECIDE || ncv == PETSC_DEFAULT) {
384: pep->ncv = 0;
385: } else {
386: if (ncv<1) SETERRQ(PetscObjectComm((PetscObject)pep),PETSC_ERR_ARG_OUTOFRANGE,"Illegal value of ncv. Must be > 0");
387: pep->ncv = ncv;
388: }
389: if (mpd == PETSC_DECIDE || mpd == PETSC_DEFAULT) {
390: pep->mpd = 0;
391: } else {
392: if (mpd<1) SETERRQ(PetscObjectComm((PetscObject)pep),PETSC_ERR_ARG_OUTOFRANGE,"Illegal value of mpd. Must be > 0");
393: pep->mpd = mpd;
394: }
395: pep->state = PEP_STATE_INITIAL;
396: return(0);
397: }
401: /*@
402: PEPSetWhichEigenpairs - Specifies which portion of the spectrum is
403: to be sought.
405: Logically Collective on PEP407: Input Parameters:
408: + pep - eigensolver context obtained from PEPCreate()
409: - which - the portion of the spectrum to be sought
411: Possible values:
412: The parameter 'which' can have one of these values
414: + PEP_LARGEST_MAGNITUDE - largest eigenvalues in magnitude (default)
415: . PEP_SMALLEST_MAGNITUDE - smallest eigenvalues in magnitude
416: . PEP_LARGEST_REAL - largest real parts
417: . PEP_SMALLEST_REAL - smallest real parts
418: . PEP_LARGEST_IMAGINARY - largest imaginary parts
419: . PEP_SMALLEST_IMAGINARY - smallest imaginary parts
420: . PEP_TARGET_MAGNITUDE - eigenvalues closest to the target (in magnitude)
421: . PEP_TARGET_REAL - eigenvalues with real part closest to target
422: . PEP_TARGET_IMAGINARY - eigenvalues with imaginary part closest to target
423: - PEP_WHICH_USER - user defined ordering set with PEPSetEigenvalueComparison()
425: Options Database Keys:
426: + -pep_largest_magnitude - Sets largest eigenvalues in magnitude
427: . -pep_smallest_magnitude - Sets smallest eigenvalues in magnitude
428: . -pep_largest_real - Sets largest real parts
429: . -pep_smallest_real - Sets smallest real parts
430: . -pep_largest_imaginary - Sets largest imaginary parts
431: . -pep_smallest_imaginary - Sets smallest imaginary parts
432: . -pep_target_magnitude - Sets eigenvalues closest to target
433: . -pep_target_real - Sets real parts closest to target
434: - -pep_target_imaginary - Sets imaginary parts closest to target
436: Notes:
437: Not all eigensolvers implemented in PEP account for all the possible values
438: stated above. If SLEPc is compiled for real numbers PEP_LARGEST_IMAGINARY
439: and PEP_SMALLEST_IMAGINARY use the absolute value of the imaginary part
440: for eigenvalue selection.
442: The target is a scalar value provided with PEPSetTarget().
444: The criterion PEP_TARGET_IMAGINARY is available only in case PETSc and
445: SLEPc have been built with complex scalars.
447: Level: intermediate
449: .seealso: PEPGetWhichEigenpairs(), PEPSetTarget(), PEPSetEigenvalueComparison(), PEPWhich450: @*/
451: PetscErrorCode PEPSetWhichEigenpairs(PEP pep,PEPWhich which)452: {
456: switch (which) {
457: case PEP_LARGEST_MAGNITUDE:
458: case PEP_SMALLEST_MAGNITUDE:
459: case PEP_LARGEST_REAL:
460: case PEP_SMALLEST_REAL:
461: case PEP_LARGEST_IMAGINARY:
462: case PEP_SMALLEST_IMAGINARY:
463: case PEP_TARGET_MAGNITUDE:
464: case PEP_TARGET_REAL:
465: #if defined(PETSC_USE_COMPLEX)
466: case PEP_TARGET_IMAGINARY:
467: #endif
468: case PEP_WHICH_USER:
469: if (pep->which != which) {
470: pep->state = PEP_STATE_INITIAL;
471: pep->which = which;
472: }
473: break;
474: default:475: SETERRQ(PetscObjectComm((PetscObject)pep),PETSC_ERR_ARG_OUTOFRANGE,"Invalid 'which' value");
476: }
477: return(0);
478: }
482: /*@
483: PEPGetWhichEigenpairs - Returns which portion of the spectrum is to be
484: sought.
486: Not Collective
488: Input Parameter:
489: . pep - eigensolver context obtained from PEPCreate()
491: Output Parameter:
492: . which - the portion of the spectrum to be sought
494: Notes:
495: See PEPSetWhichEigenpairs() for possible values of 'which'.
497: Level: intermediate
499: .seealso: PEPSetWhichEigenpairs(), PEPWhich500: @*/
501: PetscErrorCode PEPGetWhichEigenpairs(PEP pep,PEPWhich *which)502: {
506: *which = pep->which;
507: return(0);
508: }
512: /*@C
513: PEPSetEigenvalueComparison - Specifies the eigenvalue comparison function
514: when PEPSetWhichEigenpairs() is set to PEP_WHICH_USER.
516: Logically Collective on PEP518: Input Parameters:
519: + pep - eigensolver context obtained from PEPCreate()
520: . func - a pointer to the comparison function
521: - ctx - a context pointer (the last parameter to the comparison function)
523: Calling Sequence of func:
524: $ func(PetscScalar ar,PetscScalar ai,PetscScalar br,PetscScalar bi,PetscInt *res,void *ctx)
526: + ar - real part of the 1st eigenvalue
527: . ai - imaginary part of the 1st eigenvalue
528: . br - real part of the 2nd eigenvalue
529: . bi - imaginary part of the 2nd eigenvalue
530: . res - result of comparison
531: - ctx - optional context, as set by PEPSetEigenvalueComparison()
533: Note:
534: The returning parameter 'res' can be:
535: + negative - if the 1st eigenvalue is preferred to the 2st one
536: . zero - if both eigenvalues are equally preferred
537: - positive - if the 2st eigenvalue is preferred to the 1st one
539: Level: advanced
541: .seealso: PEPSetWhichEigenpairs(), PEPWhich542: @*/
543: PetscErrorCode PEPSetEigenvalueComparison(PEP pep,PetscErrorCode (*func)(PetscScalar,PetscScalar,PetscScalar,PetscScalar,PetscInt*,void*),void* ctx)544: {
547: pep->sc->comparison = func;
548: pep->sc->comparisonctx = ctx;
549: pep->which = PEP_WHICH_USER;
550: return(0);
551: }
555: /*@
556: PEPSetProblemType - Specifies the type of the polynomial eigenvalue problem.
558: Logically Collective on PEP560: Input Parameters:
561: + pep - the polynomial eigensolver context
562: - type - a known type of polynomial eigenvalue problem
564: Options Database Keys:
565: + -pep_general - general problem with no particular structure
566: . -pep_hermitian - problem whose coefficient matrices are Hermitian
567: - -pep_gyroscopic - problem with Hamiltonian structure
569: Notes:
570: Allowed values for the problem type are: general (PEP_GENERAL), Hermitian
571: (PEP_HERMITIAN), and gyroscopic (PEP_GYROSCOPIC).
573: This function is used to instruct SLEPc to exploit certain structure in
574: the polynomial eigenproblem. By default, no particular structure is assumed.
576: If the problem matrices are Hermitian (symmetric in the real case) or
577: Hermitian/skew-Hermitian then the solver can exploit this fact to perform
578: less operations or provide better stability.
580: Level: intermediate
582: .seealso: PEPSetOperators(), PEPSetType(), PEPGetProblemType(), PEPProblemType583: @*/
584: PetscErrorCode PEPSetProblemType(PEP pep,PEPProblemType type)585: {
589: if (type!=PEP_GENERAL && type!=PEP_HERMITIAN && type!=PEP_GYROSCOPIC) SETERRQ(PetscObjectComm((PetscObject)pep),PETSC_ERR_ARG_WRONG,"Unknown eigenvalue problem type");
590: pep->problem_type = type;
591: return(0);
592: }
596: /*@
597: PEPGetProblemType - Gets the problem type from the PEP object.
599: Not Collective
601: Input Parameter:
602: . pep - the polynomial eigensolver context
604: Output Parameter:
605: . type - name of PEP problem type
607: Level: intermediate
609: .seealso: PEPSetProblemType(), PEPProblemType610: @*/
611: PetscErrorCode PEPGetProblemType(PEP pep,PEPProblemType *type)612: {
616: *type = pep->problem_type;
617: return(0);
618: }
622: /*@
623: PEPSetBasis - Specifies the type of polynomial basis used to describe the
624: polynomial eigenvalue problem.
626: Logically Collective on PEP628: Input Parameters:
629: + pep - the polynomial eigensolver context
630: - basis - the type of polynomial basis
632: Options Database Key:
633: . -pep_basis <basis> - Select the basis type
635: Notes:
636: By default, the coefficient matrices passed via PEPSetOperators() are
637: expressed in the monomial basis, i.e.
638: P(lambda) = A_0 + lambda*A_1 + lambda^2*A_2 + ... + lambda^d*A_d.
639: Other polynomial bases may have better numerical behaviour, but the user
640: must then pass the coefficient matrices accordingly.
642: Level: intermediate
644: .seealso: PEPSetOperators(), PEPGetBasis(), PEPBasis645: @*/
646: PetscErrorCode PEPSetBasis(PEP pep,PEPBasis basis)647: {
651: pep->basis = basis;
652: return(0);
653: }
657: /*@
658: PEPGetBasis - Gets the type of polynomial basis from the PEP object.
660: Not Collective
662: Input Parameter:
663: . pep - the polynomial eigensolver context
665: Output Parameter:
666: . basis - the polynomial basis
668: Level: intermediate
670: .seealso: PEPSetBasis(), PEPBasis671: @*/
672: PetscErrorCode PEPGetBasis(PEP pep,PEPBasis *basis)673: {
677: *basis = pep->basis;
678: return(0);
679: }
683: /*@
684: PEPSetTrackAll - Specifies if the solver must compute the residual of all
685: approximate eigenpairs or not.
687: Logically Collective on PEP689: Input Parameters:
690: + pep - the eigensolver context
691: - trackall - whether compute all residuals or not
693: Notes:
694: If the user sets trackall=PETSC_TRUE then the solver explicitly computes
695: the residual for each eigenpair approximation. Computing the residual is
696: usually an expensive operation and solvers commonly compute the associated
697: residual to the first unconverged eigenpair.
698: The options '-pep_monitor_all' and '-pep_monitor_lg_all' automatically
699: activate this option.
701: Level: developer
703: .seealso: PEPGetTrackAll()
704: @*/
705: PetscErrorCode PEPSetTrackAll(PEP pep,PetscBool trackall)706: {
710: pep->trackall = trackall;
711: return(0);
712: }
716: /*@
717: PEPGetTrackAll - Returns the flag indicating whether all residual norms must
718: be computed or not.
720: Not Collective
722: Input Parameter:
723: . pep - the eigensolver context
725: Output Parameter:
726: . trackall - the returned flag
728: Level: developer
730: .seealso: PEPSetTrackAll()
731: @*/
732: PetscErrorCode PEPGetTrackAll(PEP pep,PetscBool *trackall)733: {
737: *trackall = pep->trackall;
738: return(0);
739: }
743: /*@C
744: PEPSetConvergenceTestFunction - Sets a function to compute the error estimate
745: used in the convergence test.
747: Logically Collective on PEP749: Input Parameters:
750: + pep - eigensolver context obtained from PEPCreate()
751: . func - a pointer to the convergence test function
752: . ctx - [optional] context for private data for the convergence routine
753: - destroy - [optional] destructor for the context (may be NULL;
754: PETSC_NULL_FUNCTION in Fortran)
756: Calling Sequence of func:
757: $ func(PEP pep,PetscScalar eigr,PetscScalar eigi,PetscReal res,PetscReal *errest,void *ctx)
759: + pep - eigensolver context obtained from PEPCreate()
760: . eigr - real part of the eigenvalue
761: . eigi - imaginary part of the eigenvalue
762: . res - residual norm associated to the eigenpair
763: . errest - (output) computed error estimate
764: - ctx - optional context, as set by PEPSetConvergenceTest()
766: Note:
767: If the error estimate returned by the convergence test function is less than
768: the tolerance, then the eigenvalue is accepted as converged.
770: Level: advanced
772: .seealso: PEPSetConvergenceTest(), PEPSetTolerances()
773: @*/
774: PetscErrorCode PEPSetConvergenceTestFunction(PEP pep,PetscErrorCode (*func)(PEP,PetscScalar,PetscScalar,PetscReal,PetscReal*,void*),void* ctx,PetscErrorCode (*destroy)(void*))775: {
780: if (pep->convergeddestroy) {
781: (*pep->convergeddestroy)(pep->convergedctx);
782: }
783: pep->converged = func;
784: pep->convergeddestroy = destroy;
785: pep->convergedctx = ctx;
786: if (func == PEPConvergedEigRelative) pep->conv = PEP_CONV_EIG;
787: else if (func == PEPConvergedLinear) pep->conv = PEP_CONV_LINEAR;
788: else if (func == PEPConvergedNorm) pep->conv = PEP_CONV_NORM;
789: else if (func == PEPConvergedAbsolute) pep->conv = PEP_CONV_ABS;
790: else pep->conv = PEP_CONV_USER;
791: return(0);
792: }
796: /*@
797: PEPSetConvergenceTest - Specifies how to compute the error estimate
798: used in the convergence test.
800: Logically Collective on PEP802: Input Parameters:
803: + pep - eigensolver context obtained from PEPCreate()
804: - conv - the type of convergence test
806: Options Database Keys:
807: + -pep_conv_abs - Sets the absolute convergence test
808: . -pep_conv_eig - Sets the convergence test relative to the eigenvalue
809: . -pep_conv_linear - Sets the convergence test related to the linearized eigenproblem
810: - -pep_conv_user - Selects the user-defined convergence test
812: Note:
813: The parameter 'conv' can have one of these values
814: + PEP_CONV_ABS - absolute error ||r||
815: . PEP_CONV_EIG - error relative to the eigenvalue l, ||r||/|l|
816: . PEP_CONV_LINEAR - error related to the linearized eigenproblem
817: . PEP_CONV_NORM - error relative matrix norms, ||r||/sum_i(l^i*||A_i||)
818: - PEP_CONV_USER - function set by PEPSetConvergenceTestFunction()
820: Level: intermediate
822: .seealso: PEPGetConvergenceTest(), PEPSetConvergenceTestFunction(), PEPConv823: @*/
824: PetscErrorCode PEPSetConvergenceTest(PEP pep,PEPConv conv)825: {
829: switch (conv) {
830: case PEP_CONV_ABS: pep->converged = PEPConvergedAbsolute; break;
831: case PEP_CONV_EIG: pep->converged = PEPConvergedEigRelative; break;
832: case PEP_CONV_LINEAR: pep->converged = PEPConvergedLinear; break;
833: case PEP_CONV_NORM: pep->converged = PEPConvergedNorm; break;
834: case PEP_CONV_USER: break;
835: default:836: SETERRQ(PetscObjectComm((PetscObject)pep),PETSC_ERR_ARG_OUTOFRANGE,"Invalid 'conv' value");
837: }
838: pep->conv = conv;
839: return(0);
840: }
844: /*@
845: PEPGetConvergenceTest - Gets the method used to compute the error estimate
846: used in the convergence test.
848: Not Collective
850: Input Parameters:
851: . pep - eigensolver context obtained from PEPCreate()
853: Output Parameters:
854: . conv - the type of convergence test
856: Level: intermediate
858: .seealso: PEPSetConvergenceTest(), PEPConv859: @*/
860: PetscErrorCode PEPGetConvergenceTest(PEP pep,PEPConv *conv)861: {
865: *conv = pep->conv;
866: return(0);
867: }
871: /*@
872: PEPSetScale - Specifies the scaling strategy to be used.
874: Logically Collective on PEP876: Input Parameters:
877: + pep - the eigensolver context
878: . scale - scaling strategy
879: . alpha - the scaling factor used in the scalar strategy
880: . Dl - the left diagonal matrix of the diagonal scaling algorithm
881: . Dr - the right diagonal matrix of the diagonal scaling algorithm
882: . its - number of iterations of the diagonal scaling algorithm
883: - lambda - approximation to wanted eigenvalues (modulus)
885: Options Database Keys:
886: + -pep_scale <type> - scaling type, one of <none,scalar,diagonal,both>
887: . -pep_scale_factor <alpha> - the scaling factor
888: . -pep_scale_its <its> - number of iterations
889: - -pep_scale_lambda <lambda> - approximation to eigenvalues
891: Notes:
892: There are two non-exclusive scaling strategies: scalar and diagonal.
894: In the scalar strategy, scaling is applied to the eigenvalue, that is,
895: mu = lambda/alpha is the new eigenvalue and all matrices are scaled
896: accordingly. After solving the scaled problem, the original lambda is
897: recovered. Parameter 'alpha' must be positive. Use PETSC_DECIDE to let
898: the solver compute a reasonable scaling factor.
900: In the diagonal strategy, the solver works implicitly with matrix Dl*A*Dr,
901: where Dl and Dr are appropriate diagonal matrices. This improves the accuracy
902: of the computed results in some cases. The user may provide the Dr and Dl
903: matrices represented as Vec objects storing diagonal elements. If not
904: provided, these matrices are computed internally. This option requires
905: that the polynomial coefficient matrices are of MATAIJ type.
906: The parameter 'its' is the number of iterations performed by the method.
907: Parameter 'lambda' must be positive. Use PETSC_DECIDE or set lambda = 1.0 if
908: no information about eigenvalues is available.
910: Level: intermediate
912: .seealso: PEPGetScale()
913: @*/
914: PetscErrorCode PEPSetScale(PEP pep,PEPScale scale,PetscReal alpha,Vec Dl,Vec Dr,PetscInt its,PetscReal lambda)915: {
921: pep->scale = scale;
922: if (scale==PEP_SCALE_SCALAR || scale==PEP_SCALE_BOTH) {
924: if (alpha == PETSC_DEFAULT || alpha == PETSC_DECIDE) {
925: pep->sfactor = 0.0;
926: pep->sfactor_set = PETSC_FALSE;
927: } else {
928: if (alpha<=0.0) SETERRQ(PetscObjectComm((PetscObject)pep),PETSC_ERR_ARG_OUTOFRANGE,"Illegal value of alpha. Must be > 0");
929: pep->sfactor = alpha;
930: pep->sfactor_set = PETSC_TRUE;
931: }
932: }
933: if (scale==PEP_SCALE_DIAGONAL || scale==PEP_SCALE_BOTH) {
934: if (Dl) {
937: PetscObjectReference((PetscObject)Dl);
938: VecDestroy(&pep->Dl);
939: pep->Dl = Dl;
940: }
941: if (Dr) {
944: PetscObjectReference((PetscObject)Dr);
945: VecDestroy(&pep->Dr);
946: pep->Dr = Dr;
947: }
950: if (its==PETSC_DECIDE || its==PETSC_DEFAULT) pep->sits = 5;
951: else pep->sits = its;
952: if (lambda==PETSC_DECIDE || lambda==PETSC_DEFAULT) pep->slambda = 1.0;
953: else if (lambda<=0.0) SETERRQ(PetscObjectComm((PetscObject)pep),PETSC_ERR_ARG_OUTOFRANGE,"Illegal value of lambda. Must be > 0");
954: else pep->slambda = lambda;
955: }
956: pep->state = PEP_STATE_INITIAL;
957: return(0);
958: }
962: /*@
963: PEPGetScale - Gets the scaling strategy used by the PEP object, and the
964: associated parameters.
966: Not Collectiv, but vectors are shared by all processors that share the PEP968: Input Parameter:
969: . pep - the eigensolver context
971: Output Parameters:
972: + scale - scaling strategy
973: . alpha - the scaling factor used in the scalar strategy
974: . Dl - the left diagonal matrix of the diagonal scaling algorithm
975: . Dr - the right diagonal matrix of the diagonal scaling algorithm
976: . its - number of iterations of the diagonal scaling algorithm
977: - lambda - approximation to wanted eigenvalues (modulus)
979: Level: intermediate
981: Note:
982: The user can specify NULL for any parameter that is not needed.
984: If Dl or Dr were not set by the user, then the ones computed internally are
985: returned (or a null pointer if called before PEPSetUp).
987: .seealso: PEPSetScale(), PEPSetUp()
988: @*/
989: PetscErrorCode PEPGetScale(PEP pep,PEPScale *scale,PetscReal *alpha,Vec *Dl,Vec *Dr,PetscInt *its,PetscReal *lambda)990: {
993: if (scale) *scale = pep->scale;
994: if (alpha) *alpha = pep->sfactor;
995: if (Dl) *Dl = pep->Dl;
996: if (Dr) *Dr = pep->Dr;
997: if (its) *its = pep->sits;
998: if (lambda) *lambda = pep->slambda;
999: return(0);
1000: }
1004: /*@
1005: PEPSetExtract - Specifies the extraction strategy to be used.
1007: Logically Collective on PEP1009: Input Parameters:
1010: + pep - the eigensolver context
1011: - extract - extraction strategy
1013: Options Database Keys:
1014: . -pep_extract <type> - extraction type, one of <none,norm,residual,structured>
1016: Level: intermediate
1018: .seealso: PEPGetExtract()
1019: @*/
1020: PetscErrorCode PEPSetExtract(PEP pep,PEPExtract extract)1021: {
1025: pep->extract = extract;
1026: return(0);
1027: }
1031: /*@
1032: PEPGetExtract - Gets the extraction strategy used by the PEP object.
1034: Not Collective
1036: Input Parameter:
1037: . pep - the eigensolver context
1039: Output Parameter:
1040: . extract - extraction strategy
1042: Level: intermediate
1044: .seealso: PEPSetExtract()
1045: @*/
1046: PetscErrorCode PEPGetExtract(PEP pep,PEPExtract *extract)1047: {
1050: if (extract) *extract = pep->extract;
1051: return(0);
1052: }
1056: /*@
1057: PEPSetRefine - Specifies the refinement type (and options) to be used
1058: after the solve.
1060: Logically Collective on PEP1062: Input Parameters:
1063: + pep - the polynomial eigensolver context
1064: . refine - refinement type
1065: . npart - number of partitions of the communicator
1066: . tol - the convergence tolerance
1067: . its - maximum number of refinement iterations
1068: - schur - boolean flag to activate the Schur complement approach
1070: Options Database Keys:
1071: + -pep_refine <type> - refinement type, one of <none,simple,multiple>
1072: . -pep_refine_partitions <n> - the number of partitions
1073: . -pep_refine_tol <tol> - the tolerance
1074: . -pep_refine_its <its> - number of iterations
1075: - -pep_refine_schur - to set the Schur complement approach
1077: Notes:
1078: By default, iterative refinement is disabled, since it may be very
1079: costly. There are two possible refinement strategies: simple and multiple.
1080: The simple approach performs iterative refinement on each of the
1081: converged eigenpairs individually, whereas the multiple strategy works
1082: with the invariant pair as a whole, refining all eigenpairs simultaneously.
1083: The latter may be required for the case of multiple eigenvalues.
1085: In some cases, especially when using direct solvers within the
1086: iterative refinement method, it may be helpful for improved scalability
1087: to split the communicator in several partitions. The npart parameter
1088: indicates how many partitions to use (defaults to 1).
1090: The tol and its parameters specify the stopping criterion. In the simple
1091: method, refinement continues until the residual of each eigenpair is
1092: below the tolerance (tol defaults to the PEP tol, but may be set to a
1093: different value). In contrast, the multiple method simply performs its
1094: refinement iterations (just one by default).
1096: The schur flag is used to change the way in which linear systems are
1097: solved, so that a Schur complement approach is used instead of explicitly
1098: building the coefficient matrix.
1100: Level: intermediate
1102: .seealso: PEPGetRefine()
1103: @*/
1104: PetscErrorCode PEPSetRefine(PEP pep,PEPRefine refine,PetscInt npart,PetscReal tol,PetscInt its,PetscBool schur)1105: {
1107: PetscMPIInt size;
1116: pep->refine = refine;
1117: if (refine) { /* process parameters only if not REFINE_NONE */
1118: if (npart!=pep->npart) {
1119: PetscSubcommDestroy(&pep->refinesubc);
1120: KSPDestroy(&pep->refineksp);
1121: }
1122: if (npart == PETSC_DEFAULT || npart == PETSC_DECIDE) {
1123: pep->npart = 1;
1124: } else {
1125: MPI_Comm_size(PetscObjectComm((PetscObject)pep),&size);
1126: if (npart<1 || npart>size) SETERRQ(PetscObjectComm((PetscObject)pep),PETSC_ERR_ARG_OUTOFRANGE,"Illegal value of npart");
1127: pep->npart = npart;
1128: }
1129: if (tol == PETSC_DEFAULT || tol == PETSC_DECIDE) {
1130: pep->rtol = pep->tol;
1131: } else {
1132: if (tol<=0.0) SETERRQ(PetscObjectComm((PetscObject)pep),PETSC_ERR_ARG_OUTOFRANGE,"Illegal value of tol. Must be > 0");
1133: pep->rtol = tol;
1134: }
1135: if (its==PETSC_DECIDE || its==PETSC_DEFAULT) {
1136: pep->rits = PETSC_DEFAULT;
1137: } else {
1138: if (its<0) SETERRQ(PetscObjectComm((PetscObject)pep),PETSC_ERR_ARG_OUTOFRANGE,"Illegal value of its. Must be >= 0");
1139: pep->rits = its;
1140: }
1141: pep->schur = schur;
1142: }
1143: pep->state = PEP_STATE_INITIAL;
1144: return(0);
1145: }
1149: /*@
1150: PEPGetRefine - Gets the refinement strategy used by the PEP object, and the
1151: associated parameters.
1153: Not Collective
1155: Input Parameter:
1156: . pep - the polynomial eigensolver context
1158: Output Parameters:
1159: + refine - refinement type
1160: . npart - number of partitions of the communicator
1161: . tol - the convergence tolerance
1162: . its - maximum number of refinement iterations
1163: - schur - whether the Schur complement approach is being used
1165: Level: intermediate
1167: Note:
1168: The user can specify NULL for any parameter that is not needed.
1170: .seealso: PEPSetRefine()
1171: @*/
1172: PetscErrorCode PEPGetRefine(PEP pep,PEPRefine *refine,PetscInt *npart,PetscReal *tol,PetscInt *its,PetscBool *schur)1173: {
1176: if (refine) *refine = pep->refine;
1177: if (npart) *npart = pep->npart;
1178: if (tol) *tol = pep->rtol;
1179: if (its) *its = pep->rits;
1180: if (schur) *schur = pep->schur;
1181: return(0);
1182: }
1186: /*@C
1187: PEPSetOptionsPrefix - Sets the prefix used for searching for all
1188: PEP options in the database.
1190: Logically Collective on PEP1192: Input Parameters:
1193: + pep - the polynomial eigensolver context
1194: - prefix - the prefix string to prepend to all PEP option requests
1196: Notes:
1197: A hyphen (-) must NOT be given at the beginning of the prefix name.
1198: The first character of all runtime options is AUTOMATICALLY the
1199: hyphen.
1201: For example, to distinguish between the runtime options for two
1202: different PEP contexts, one could call
1203: .vb
1204: PEPSetOptionsPrefix(pep1,"qeig1_")
1205: PEPSetOptionsPrefix(pep2,"qeig2_")
1206: .ve
1208: Level: advanced
1210: .seealso: PEPAppendOptionsPrefix(), PEPGetOptionsPrefix()
1211: @*/
1212: PetscErrorCode PEPSetOptionsPrefix(PEP pep,const char *prefix)1213: {
1218: if (!pep->st) { PEPGetST(pep,&pep->st); }
1219: STSetOptionsPrefix(pep->st,prefix);
1220: if (!pep->V) { PEPGetBV(pep,&pep->V); }
1221: BVSetOptionsPrefix(pep->V,prefix);
1222: if (!pep->ds) { PEPGetDS(pep,&pep->ds); }
1223: DSSetOptionsPrefix(pep->ds,prefix);
1224: if (!pep->rg) { PEPGetRG(pep,&pep->rg); }
1225: RGSetOptionsPrefix(pep->rg,prefix);
1226: PetscObjectSetOptionsPrefix((PetscObject)pep,prefix);
1227: return(0);
1228: }
1232: /*@C
1233: PEPAppendOptionsPrefix - Appends to the prefix used for searching for all
1234: PEP options in the database.
1236: Logically Collective on PEP1238: Input Parameters:
1239: + pep - the polynomial eigensolver context
1240: - prefix - the prefix string to prepend to all PEP option requests
1242: Notes:
1243: A hyphen (-) must NOT be given at the beginning of the prefix name.
1244: The first character of all runtime options is AUTOMATICALLY the hyphen.
1246: Level: advanced
1248: .seealso: PEPSetOptionsPrefix(), PEPGetOptionsPrefix()
1249: @*/
1250: PetscErrorCode PEPAppendOptionsPrefix(PEP pep,const char *prefix)1251: {
1253: PetscBool flg;
1254: EPS eps;
1258: if (!pep->st) { PEPGetST(pep,&pep->st); }
1259: STAppendOptionsPrefix(pep->st,prefix);
1260: if (!pep->V) { PEPGetBV(pep,&pep->V); }
1261: BVSetOptionsPrefix(pep->V,prefix);
1262: if (!pep->ds) { PEPGetDS(pep,&pep->ds); }
1263: DSSetOptionsPrefix(pep->ds,prefix);
1264: if (!pep->rg) { PEPGetRG(pep,&pep->rg); }
1265: RGSetOptionsPrefix(pep->rg,prefix);
1266: PetscObjectAppendOptionsPrefix((PetscObject)pep,prefix);
1267: PetscObjectTypeCompare((PetscObject)pep,PEPLINEAR,&flg);
1268: if (flg) {
1269: PEPLinearGetEPS(pep,&eps);
1270: EPSSetOptionsPrefix(eps,((PetscObject)pep)->prefix);
1271: EPSAppendOptionsPrefix(eps,"pep_");
1272: }
1273: return(0);
1274: }
1278: /*@C
1279: PEPGetOptionsPrefix - Gets the prefix used for searching for all
1280: PEP options in the database.
1282: Not Collective
1284: Input Parameters:
1285: . pep - the polynomial eigensolver context
1287: Output Parameters:
1288: . prefix - pointer to the prefix string used is returned
1290: Notes: On the fortran side, the user should pass in a string 'prefix' of
1291: sufficient length to hold the prefix.
1293: Level: advanced
1295: .seealso: PEPSetOptionsPrefix(), PEPAppendOptionsPrefix()
1296: @*/
1297: PetscErrorCode PEPGetOptionsPrefix(PEP pep,const char *prefix[])1298: {
1304: PetscObjectGetOptionsPrefix((PetscObject)pep,prefix);
1305: return(0);
1306: }