Actual source code: nepopts.c
1: /*
2: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
3: SLEPc - Scalable Library for Eigenvalue Problem Computations
4: Copyright (c) 2002-, Universitat Politecnica de Valencia, Spain
6: This file is part of SLEPc.
7: SLEPc is distributed under a 2-clause BSD license (see LICENSE).
8: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
9: */
10: /*
11: NEP routines related to options that can be set via the command-line
12: or procedurally
13: */
15: #include <slepc/private/nepimpl.h>
16: #include <petscdraw.h>
18: /*@C
19: NEPMonitorSetFromOptions - Sets a monitor function and viewer appropriate for the type
20: indicated by the user.
22: Collective
24: Input Parameters:
25: + nep - the nonlinear eigensolver context
26: . opt - the command line option for this monitor
27: . name - the monitor type one is seeking
28: . ctx - an optional user context for the monitor, or NULL
29: - trackall - whether this monitor tracks all eigenvalues or not
31: Level: developer
33: .seealso: `NEPMonitorSet()`, `NEPSetTrackAll()`
34: @*/
35: PetscErrorCode NEPMonitorSetFromOptions(NEP nep,const char opt[],const char name[],void *ctx,PetscBool trackall)
36: {
37: PetscErrorCode (*mfunc)(NEP,PetscInt,PetscInt,PetscScalar*,PetscScalar*,PetscReal*,PetscInt,void*);
38: PetscErrorCode (*cfunc)(PetscViewer,PetscViewerFormat,void*,PetscViewerAndFormat**);
39: PetscErrorCode (*dfunc)(PetscViewerAndFormat**);
40: PetscViewerAndFormat *vf;
41: PetscViewer viewer;
42: PetscViewerFormat format;
43: PetscViewerType vtype;
44: char key[PETSC_MAX_PATH_LEN];
45: PetscBool flg;
47: PetscFunctionBegin;
48: PetscCall(PetscOptionsCreateViewer(PetscObjectComm((PetscObject)nep),((PetscObject)nep)->options,((PetscObject)nep)->prefix,opt,&viewer,&format,&flg));
49: if (!flg) PetscFunctionReturn(PETSC_SUCCESS);
51: PetscCall(PetscViewerGetType(viewer,&vtype));
52: PetscCall(SlepcMonitorMakeKey_Internal(name,vtype,format,key));
53: PetscCall(PetscFunctionListFind(NEPMonitorList,key,&mfunc));
54: PetscCheck(mfunc,PetscObjectComm((PetscObject)nep),PETSC_ERR_SUP,"Specified viewer and format not supported");
55: PetscCall(PetscFunctionListFind(NEPMonitorCreateList,key,&cfunc));
56: PetscCall(PetscFunctionListFind(NEPMonitorDestroyList,key,&dfunc));
57: if (!cfunc) cfunc = PetscViewerAndFormatCreate_Internal;
58: if (!dfunc) dfunc = PetscViewerAndFormatDestroy;
60: PetscCall((*cfunc)(viewer,format,ctx,&vf));
61: PetscCall(PetscViewerDestroy(&viewer));
62: PetscCall(NEPMonitorSet(nep,mfunc,vf,(PetscCtxDestroyFn*)dfunc));
63: if (trackall) PetscCall(NEPSetTrackAll(nep,PETSC_TRUE));
64: PetscFunctionReturn(PETSC_SUCCESS);
65: }
67: /*@
68: NEPSetFromOptions - Sets NEP options from the options database.
69: This routine must be called before NEPSetUp() if the user is to be
70: allowed to set the solver type.
72: Collective
74: Input Parameters:
75: . nep - the nonlinear eigensolver context
77: Notes:
78: To see all options, run your program with the -help option.
80: Level: beginner
82: .seealso: `NEPSetOptionsPrefix()`
83: @*/
84: PetscErrorCode NEPSetFromOptions(NEP nep)
85: {
86: char type[256];
87: PetscBool set,flg,flg1,flg2,flg3,flg4,flg5,bval;
88: PetscReal r;
89: PetscScalar s;
90: PetscInt i,j,k;
91: NEPRefine refine;
92: NEPRefineScheme scheme;
94: PetscFunctionBegin;
96: PetscCall(NEPRegisterAll());
97: PetscObjectOptionsBegin((PetscObject)nep);
98: PetscCall(PetscOptionsFList("-nep_type","Nonlinear eigensolver method","NEPSetType",NEPList,(char*)(((PetscObject)nep)->type_name?((PetscObject)nep)->type_name:NEPRII),type,sizeof(type),&flg));
99: if (flg) PetscCall(NEPSetType(nep,type));
100: else if (!((PetscObject)nep)->type_name) PetscCall(NEPSetType(nep,NEPRII));
102: PetscCall(PetscOptionsBoolGroupBegin("-nep_general","General nonlinear eigenvalue problem","NEPSetProblemType",&flg));
103: if (flg) PetscCall(NEPSetProblemType(nep,NEP_GENERAL));
104: PetscCall(PetscOptionsBoolGroupEnd("-nep_rational","Rational eigenvalue problem","NEPSetProblemType",&flg));
105: if (flg) PetscCall(NEPSetProblemType(nep,NEP_RATIONAL));
107: refine = nep->refine;
108: PetscCall(PetscOptionsEnum("-nep_refine","Iterative refinement method","NEPSetRefine",NEPRefineTypes,(PetscEnum)refine,(PetscEnum*)&refine,&flg1));
109: i = nep->npart;
110: PetscCall(PetscOptionsInt("-nep_refine_partitions","Number of partitions of the communicator for iterative refinement","NEPSetRefine",nep->npart,&i,&flg2));
111: r = nep->rtol;
112: PetscCall(PetscOptionsReal("-nep_refine_tol","Tolerance for iterative refinement","NEPSetRefine",nep->rtol==(PetscReal)PETSC_DETERMINE?SLEPC_DEFAULT_TOL/1000:nep->rtol,&r,&flg3));
113: j = nep->rits;
114: PetscCall(PetscOptionsInt("-nep_refine_its","Maximum number of iterations for iterative refinement","NEPSetRefine",nep->rits,&j,&flg4));
115: scheme = nep->scheme;
116: PetscCall(PetscOptionsEnum("-nep_refine_scheme","Scheme used for linear systems within iterative refinement","NEPSetRefine",NEPRefineSchemes,(PetscEnum)scheme,(PetscEnum*)&scheme,&flg5));
117: if (flg1 || flg2 || flg3 || flg4 || flg5) PetscCall(NEPSetRefine(nep,refine,i,r,j,scheme));
119: i = nep->max_it;
120: PetscCall(PetscOptionsInt("-nep_max_it","Maximum number of iterations","NEPSetTolerances",nep->max_it,&i,&flg1));
121: r = nep->tol;
122: PetscCall(PetscOptionsReal("-nep_tol","Tolerance","NEPSetTolerances",SlepcDefaultTol(nep->tol),&r,&flg2));
123: if (flg1 || flg2) PetscCall(NEPSetTolerances(nep,r,i));
125: PetscCall(PetscOptionsBoolGroupBegin("-nep_conv_rel","Relative error convergence test","NEPSetConvergenceTest",&flg));
126: if (flg) PetscCall(NEPSetConvergenceTest(nep,NEP_CONV_REL));
127: PetscCall(PetscOptionsBoolGroup("-nep_conv_norm","Convergence test relative to the matrix norms","NEPSetConvergenceTest",&flg));
128: if (flg) PetscCall(NEPSetConvergenceTest(nep,NEP_CONV_NORM));
129: PetscCall(PetscOptionsBoolGroup("-nep_conv_abs","Absolute error convergence test","NEPSetConvergenceTest",&flg));
130: if (flg) PetscCall(NEPSetConvergenceTest(nep,NEP_CONV_ABS));
131: PetscCall(PetscOptionsBoolGroupEnd("-nep_conv_user","User-defined convergence test","NEPSetConvergenceTest",&flg));
132: if (flg) PetscCall(NEPSetConvergenceTest(nep,NEP_CONV_USER));
134: PetscCall(PetscOptionsBoolGroupBegin("-nep_stop_basic","Stop iteration if all eigenvalues converged or max_it reached","NEPSetStoppingTest",&flg));
135: if (flg) PetscCall(NEPSetStoppingTest(nep,NEP_STOP_BASIC));
136: PetscCall(PetscOptionsBoolGroupEnd("-nep_stop_user","User-defined stopping test","NEPSetStoppingTest",&flg));
137: if (flg) PetscCall(NEPSetStoppingTest(nep,NEP_STOP_USER));
139: i = nep->nev;
140: PetscCall(PetscOptionsInt("-nep_nev","Number of eigenvalues to compute","NEPSetDimensions",nep->nev,&i,&flg1));
141: j = nep->ncv;
142: PetscCall(PetscOptionsInt("-nep_ncv","Number of basis vectors","NEPSetDimensions",nep->ncv,&j,&flg2));
143: k = nep->mpd;
144: PetscCall(PetscOptionsInt("-nep_mpd","Maximum dimension of projected problem","NEPSetDimensions",nep->mpd,&k,&flg3));
145: if (flg1 || flg2 || flg3) PetscCall(NEPSetDimensions(nep,i,j,k));
147: PetscCall(PetscOptionsBoolGroupBegin("-nep_largest_magnitude","Compute largest eigenvalues in magnitude","NEPSetWhichEigenpairs",&flg));
148: if (flg) PetscCall(NEPSetWhichEigenpairs(nep,NEP_LARGEST_MAGNITUDE));
149: PetscCall(PetscOptionsBoolGroup("-nep_smallest_magnitude","Compute smallest eigenvalues in magnitude","NEPSetWhichEigenpairs",&flg));
150: if (flg) PetscCall(NEPSetWhichEigenpairs(nep,NEP_SMALLEST_MAGNITUDE));
151: PetscCall(PetscOptionsBoolGroup("-nep_largest_real","Compute eigenvalues with largest real parts","NEPSetWhichEigenpairs",&flg));
152: if (flg) PetscCall(NEPSetWhichEigenpairs(nep,NEP_LARGEST_REAL));
153: PetscCall(PetscOptionsBoolGroup("-nep_smallest_real","Compute eigenvalues with smallest real parts","NEPSetWhichEigenpairs",&flg));
154: if (flg) PetscCall(NEPSetWhichEigenpairs(nep,NEP_SMALLEST_REAL));
155: PetscCall(PetscOptionsBoolGroup("-nep_largest_imaginary","Compute eigenvalues with largest imaginary parts","NEPSetWhichEigenpairs",&flg));
156: if (flg) PetscCall(NEPSetWhichEigenpairs(nep,NEP_LARGEST_IMAGINARY));
157: PetscCall(PetscOptionsBoolGroup("-nep_smallest_imaginary","Compute eigenvalues with smallest imaginary parts","NEPSetWhichEigenpairs",&flg));
158: if (flg) PetscCall(NEPSetWhichEigenpairs(nep,NEP_SMALLEST_IMAGINARY));
159: PetscCall(PetscOptionsBoolGroup("-nep_target_magnitude","Compute eigenvalues closest to target","NEPSetWhichEigenpairs",&flg));
160: if (flg) PetscCall(NEPSetWhichEigenpairs(nep,NEP_TARGET_MAGNITUDE));
161: PetscCall(PetscOptionsBoolGroup("-nep_target_real","Compute eigenvalues with real parts closest to target","NEPSetWhichEigenpairs",&flg));
162: if (flg) PetscCall(NEPSetWhichEigenpairs(nep,NEP_TARGET_REAL));
163: PetscCall(PetscOptionsBoolGroup("-nep_target_imaginary","Compute eigenvalues with imaginary parts closest to target","NEPSetWhichEigenpairs",&flg));
164: if (flg) PetscCall(NEPSetWhichEigenpairs(nep,NEP_TARGET_IMAGINARY));
165: PetscCall(PetscOptionsBoolGroupEnd("-nep_all","Compute all eigenvalues in a region","NEPSetWhichEigenpairs",&flg));
166: if (flg) PetscCall(NEPSetWhichEigenpairs(nep,NEP_ALL));
168: PetscCall(PetscOptionsScalar("-nep_target","Value of the target","NEPSetTarget",nep->target,&s,&flg));
169: if (flg) {
170: if (nep->which!=NEP_TARGET_REAL && nep->which!=NEP_TARGET_IMAGINARY) PetscCall(NEPSetWhichEigenpairs(nep,NEP_TARGET_MAGNITUDE));
171: PetscCall(NEPSetTarget(nep,s));
172: }
174: PetscCall(PetscOptionsBool("-nep_two_sided","Use two-sided variant (to compute left eigenvectors)","NEPSetTwoSided",nep->twosided,&bval,&flg));
175: if (flg) PetscCall(NEPSetTwoSided(nep,bval));
177: /* -----------------------------------------------------------------------*/
178: /*
179: Cancels all monitors hardwired into code before call to NEPSetFromOptions()
180: */
181: PetscCall(PetscOptionsBool("-nep_monitor_cancel","Remove any hardwired monitor routines","NEPMonitorCancel",PETSC_FALSE,&flg,&set));
182: if (set && flg) PetscCall(NEPMonitorCancel(nep));
183: PetscCall(NEPMonitorSetFromOptions(nep,"-nep_monitor","first_approximation",NULL,PETSC_FALSE));
184: PetscCall(NEPMonitorSetFromOptions(nep,"-nep_monitor_all","all_approximations",NULL,PETSC_TRUE));
185: PetscCall(NEPMonitorSetFromOptions(nep,"-nep_monitor_conv","convergence_history",NULL,PETSC_FALSE));
187: /* -----------------------------------------------------------------------*/
188: PetscCall(PetscOptionsName("-nep_view","Print detailed information on solver used","NEPView",&set));
189: PetscCall(PetscOptionsName("-nep_view_vectors","View computed eigenvectors","NEPVectorsView",&set));
190: PetscCall(PetscOptionsName("-nep_view_values","View computed eigenvalues","NEPValuesView",&set));
191: PetscCall(PetscOptionsName("-nep_converged_reason","Print reason for convergence, and number of iterations","NEPConvergedReasonView",&set));
192: PetscCall(PetscOptionsName("-nep_error_absolute","Print absolute errors of each eigenpair","NEPErrorView",&set));
193: PetscCall(PetscOptionsName("-nep_error_relative","Print relative errors of each eigenpair","NEPErrorView",&set));
195: PetscTryTypeMethod(nep,setfromoptions,PetscOptionsObject);
196: PetscCall(PetscObjectProcessOptionsHandlers((PetscObject)nep,PetscOptionsObject));
197: PetscOptionsEnd();
199: if (!nep->V) PetscCall(NEPGetBV(nep,&nep->V));
200: PetscCall(BVSetFromOptions(nep->V));
201: if (!nep->rg) PetscCall(NEPGetRG(nep,&nep->rg));
202: PetscCall(RGSetFromOptions(nep->rg));
203: if (nep->useds) {
204: if (!nep->ds) PetscCall(NEPGetDS(nep,&nep->ds));
205: PetscCall(NEPSetDSType(nep));
206: PetscCall(DSSetFromOptions(nep->ds));
207: }
208: if (!nep->refineksp) PetscCall(NEPRefineGetKSP(nep,&nep->refineksp));
209: PetscCall(KSPSetFromOptions(nep->refineksp));
210: if (nep->fui==NEP_USER_INTERFACE_SPLIT) for (i=0;i<nep->nt;i++) PetscCall(FNSetFromOptions(nep->f[i]));
211: PetscFunctionReturn(PETSC_SUCCESS);
212: }
214: /*@
215: NEPGetTolerances - Gets the tolerance and maximum iteration count used
216: by the NEP convergence tests.
218: Not Collective
220: Input Parameter:
221: . nep - the nonlinear eigensolver context
223: Output Parameters:
224: + tol - the convergence tolerance
225: - maxits - maximum number of iterations
227: Notes:
228: The user can specify NULL for any parameter that is not needed.
230: Level: intermediate
232: .seealso: `NEPSetTolerances()`
233: @*/
234: PetscErrorCode NEPGetTolerances(NEP nep,PetscReal *tol,PetscInt *maxits)
235: {
236: PetscFunctionBegin;
238: if (tol) *tol = nep->tol;
239: if (maxits) *maxits = nep->max_it;
240: PetscFunctionReturn(PETSC_SUCCESS);
241: }
243: /*@
244: NEPSetTolerances - Sets the tolerance and maximum iteration count used
245: by the NEP convergence tests.
247: Logically Collective
249: Input Parameters:
250: + nep - the nonlinear eigensolver context
251: . tol - the convergence tolerance
252: - maxits - maximum number of iterations to use
254: Options Database Keys:
255: + -nep_tol <tol> - Sets the convergence tolerance
256: - -nep_max_it <maxits> - Sets the maximum number of iterations allowed
258: Notes:
259: Use PETSC_CURRENT to retain the current value of any of the parameters.
260: Use PETSC_DETERMINE for either argument to assign a default value computed
261: internally (may be different in each solver).
262: For maxits use PETSC_UMLIMITED to indicate there is no upper bound on this value.
264: Level: intermediate
266: .seealso: `NEPGetTolerances()`
267: @*/
268: PetscErrorCode NEPSetTolerances(NEP nep,PetscReal tol,PetscInt maxits)
269: {
270: PetscFunctionBegin;
274: if (tol == (PetscReal)PETSC_DETERMINE) {
275: nep->tol = PETSC_DETERMINE;
276: nep->state = NEP_STATE_INITIAL;
277: } else if (tol != (PetscReal)PETSC_CURRENT) {
278: PetscCheck(tol>0.0,PetscObjectComm((PetscObject)nep),PETSC_ERR_ARG_OUTOFRANGE,"Illegal value of tol. Must be > 0");
279: nep->tol = tol;
280: }
281: if (maxits == PETSC_DETERMINE) {
282: nep->max_it = PETSC_DETERMINE;
283: nep->state = NEP_STATE_INITIAL;
284: } else if (maxits == PETSC_UNLIMITED) {
285: nep->max_it = PETSC_INT_MAX;
286: } else if (maxits != PETSC_CURRENT) {
287: PetscCheck(maxits>0,PetscObjectComm((PetscObject)nep),PETSC_ERR_ARG_OUTOFRANGE,"Illegal value of maxits. Must be > 0");
288: nep->max_it = maxits;
289: }
290: PetscFunctionReturn(PETSC_SUCCESS);
291: }
293: /*@
294: NEPGetDimensions - Gets the number of eigenvalues to compute
295: and the dimension of the subspace.
297: Not Collective
299: Input Parameter:
300: . nep - the nonlinear eigensolver context
302: Output Parameters:
303: + nev - number of eigenvalues to compute
304: . ncv - the maximum dimension of the subspace to be used by the solver
305: - mpd - the maximum dimension allowed for the projected problem
307: Notes:
308: The user can specify NULL for any parameter that is not needed.
310: Level: intermediate
312: .seealso: `NEPSetDimensions()`
313: @*/
314: PetscErrorCode NEPGetDimensions(NEP nep,PetscInt *nev,PetscInt *ncv,PetscInt *mpd)
315: {
316: PetscFunctionBegin;
318: if (nev) *nev = nep->nev;
319: if (ncv) *ncv = nep->ncv;
320: if (mpd) *mpd = nep->mpd;
321: PetscFunctionReturn(PETSC_SUCCESS);
322: }
324: /*@
325: NEPSetDimensions - Sets the number of eigenvalues to compute
326: and the dimension of the subspace.
328: Logically Collective
330: Input Parameters:
331: + nep - the nonlinear eigensolver context
332: . nev - number of eigenvalues to compute
333: . ncv - the maximum dimension of the subspace to be used by the solver
334: - mpd - the maximum dimension allowed for the projected problem
336: Options Database Keys:
337: + -nep_nev <nev> - Sets the number of eigenvalues
338: . -nep_ncv <ncv> - Sets the dimension of the subspace
339: - -nep_mpd <mpd> - Sets the maximum projected dimension
341: Notes:
342: Use PETSC_DETERMINE for ncv and mpd to assign a reasonably good value, which is
343: dependent on the solution method. For any of the arguments, use PETSC_CURRENT
344: to preserve the current value.
346: The parameters ncv and mpd are intimately related, so that the user is advised
347: to set one of them at most. Normal usage is that
348: (a) in cases where nev is small, the user sets ncv (a reasonable default is 2*nev); and
349: (b) in cases where nev is large, the user sets mpd.
351: The value of ncv should always be between nev and (nev+mpd), typically
352: ncv=nev+mpd. If nev is not too large, mpd=nev is a reasonable choice, otherwise
353: a smaller value should be used.
355: Level: intermediate
357: .seealso: `NEPGetDimensions()`
358: @*/
359: PetscErrorCode NEPSetDimensions(NEP nep,PetscInt nev,PetscInt ncv,PetscInt mpd)
360: {
361: PetscFunctionBegin;
366: if (nev != PETSC_CURRENT) {
367: PetscCheck(nev>0,PetscObjectComm((PetscObject)nep),PETSC_ERR_ARG_OUTOFRANGE,"Illegal value of nev. Must be > 0");
368: nep->nev = nev;
369: }
370: if (ncv == PETSC_DETERMINE) {
371: nep->ncv = PETSC_DETERMINE;
372: } else if (ncv != PETSC_CURRENT) {
373: PetscCheck(ncv>0,PetscObjectComm((PetscObject)nep),PETSC_ERR_ARG_OUTOFRANGE,"Illegal value of ncv. Must be > 0");
374: nep->ncv = ncv;
375: }
376: if (mpd == PETSC_DETERMINE) {
377: nep->mpd = PETSC_DETERMINE;
378: } else if (mpd != PETSC_CURRENT) {
379: PetscCheck(mpd>0,PetscObjectComm((PetscObject)nep),PETSC_ERR_ARG_OUTOFRANGE,"Illegal value of mpd. Must be > 0");
380: nep->mpd = mpd;
381: }
382: nep->state = NEP_STATE_INITIAL;
383: PetscFunctionReturn(PETSC_SUCCESS);
384: }
386: /*@
387: NEPSetWhichEigenpairs - Specifies which portion of the spectrum is
388: to be sought.
390: Logically Collective
392: Input Parameters:
393: + nep - eigensolver context obtained from NEPCreate()
394: - which - the portion of the spectrum to be sought
396: Options Database Keys:
397: + -nep_largest_magnitude - Sets largest eigenvalues in magnitude
398: . -nep_smallest_magnitude - Sets smallest eigenvalues in magnitude
399: . -nep_largest_real - Sets largest real parts
400: . -nep_smallest_real - Sets smallest real parts
401: . -nep_largest_imaginary - Sets largest imaginary parts
402: . -nep_smallest_imaginary - Sets smallest imaginary parts
403: . -nep_target_magnitude - Sets eigenvalues closest to target
404: . -nep_target_real - Sets real parts closest to target
405: . -nep_target_imaginary - Sets imaginary parts closest to target
406: - -nep_all - Sets all eigenvalues in a region
408: Notes:
409: The parameter 'which' can have one of these values
411: + NEP_LARGEST_MAGNITUDE - largest eigenvalues in magnitude (default)
412: . NEP_SMALLEST_MAGNITUDE - smallest eigenvalues in magnitude
413: . NEP_LARGEST_REAL - largest real parts
414: . NEP_SMALLEST_REAL - smallest real parts
415: . NEP_LARGEST_IMAGINARY - largest imaginary parts
416: . NEP_SMALLEST_IMAGINARY - smallest imaginary parts
417: . NEP_TARGET_MAGNITUDE - eigenvalues closest to the target (in magnitude)
418: . NEP_TARGET_REAL - eigenvalues with real part closest to target
419: . NEP_TARGET_IMAGINARY - eigenvalues with imaginary part closest to target
420: . NEP_ALL - all eigenvalues contained in a given region
421: - NEP_WHICH_USER - user defined ordering set with NEPSetEigenvalueComparison()
423: Not all eigensolvers implemented in NEP account for all the possible values
424: stated above. If SLEPc is compiled for real numbers NEP_LARGEST_IMAGINARY
425: and NEP_SMALLEST_IMAGINARY use the absolute value of the imaginary part
426: for eigenvalue selection.
428: The target is a scalar value provided with NEPSetTarget().
430: NEP_ALL is intended for use in the context of the CISS solver for
431: computing all eigenvalues in a region.
433: Level: intermediate
435: .seealso: `NEPGetWhichEigenpairs()`, `NEPSetTarget()`, `NEPSetEigenvalueComparison()`, `NEPWhich`
436: @*/
437: PetscErrorCode NEPSetWhichEigenpairs(NEP nep,NEPWhich which)
438: {
439: PetscFunctionBegin;
442: switch (which) {
443: case NEP_LARGEST_MAGNITUDE:
444: case NEP_SMALLEST_MAGNITUDE:
445: case NEP_LARGEST_REAL:
446: case NEP_SMALLEST_REAL:
447: case NEP_LARGEST_IMAGINARY:
448: case NEP_SMALLEST_IMAGINARY:
449: case NEP_TARGET_MAGNITUDE:
450: case NEP_TARGET_REAL:
451: #if defined(PETSC_USE_COMPLEX)
452: case NEP_TARGET_IMAGINARY:
453: #endif
454: case NEP_ALL:
455: case NEP_WHICH_USER:
456: if (nep->which != which) {
457: nep->state = NEP_STATE_INITIAL;
458: nep->which = which;
459: }
460: break;
461: #if !defined(PETSC_USE_COMPLEX)
462: case NEP_TARGET_IMAGINARY:
463: SETERRQ(PetscObjectComm((PetscObject)nep),PETSC_ERR_SUP,"NEP_TARGET_IMAGINARY can be used only with complex scalars");
464: #endif
465: default:
466: SETERRQ(PetscObjectComm((PetscObject)nep),PETSC_ERR_ARG_OUTOFRANGE,"Invalid 'which' value");
467: }
468: PetscFunctionReturn(PETSC_SUCCESS);
469: }
471: /*@
472: NEPGetWhichEigenpairs - Returns which portion of the spectrum is to be
473: sought.
475: Not Collective
477: Input Parameter:
478: . nep - eigensolver context obtained from NEPCreate()
480: Output Parameter:
481: . which - the portion of the spectrum to be sought
483: Notes:
484: See NEPSetWhichEigenpairs() for possible values of 'which'.
486: Level: intermediate
488: .seealso: `NEPSetWhichEigenpairs()`, `NEPWhich`
489: @*/
490: PetscErrorCode NEPGetWhichEigenpairs(NEP nep,NEPWhich *which)
491: {
492: PetscFunctionBegin;
494: PetscAssertPointer(which,2);
495: *which = nep->which;
496: PetscFunctionReturn(PETSC_SUCCESS);
497: }
499: /*@C
500: NEPSetEigenvalueComparison - Specifies the eigenvalue comparison function
501: when NEPSetWhichEigenpairs() is set to NEP_WHICH_USER.
503: Logically Collective
505: Input Parameters:
506: + nep - eigensolver context obtained from NEPCreate()
507: . comp - a pointer to the comparison function
508: - ctx - a context pointer (the last parameter to the comparison function)
510: Note:
511: The returning parameter 'res' can be
512: + negative - if the 1st eigenvalue is preferred to the 2st one
513: . zero - if both eigenvalues are equally preferred
514: - positive - if the 2st eigenvalue is preferred to the 1st one
516: Level: advanced
518: .seealso: `NEPSetWhichEigenpairs()`, `NEPWhich`
519: @*/
520: PetscErrorCode NEPSetEigenvalueComparison(NEP nep,SlepcEigenvalueComparisonFn *comp,void *ctx)
521: {
522: PetscFunctionBegin;
524: nep->sc->comparison = comp;
525: nep->sc->comparisonctx = ctx;
526: nep->which = NEP_WHICH_USER;
527: PetscFunctionReturn(PETSC_SUCCESS);
528: }
530: /*@
531: NEPSetProblemType - Specifies the type of the nonlinear eigenvalue problem.
533: Logically Collective
535: Input Parameters:
536: + nep - the nonlinear eigensolver context
537: - type - a known type of nonlinear eigenvalue problem
539: Options Database Keys:
540: + -nep_general - general problem with no particular structure
541: - -nep_rational - a rational eigenvalue problem defined in split form with all f_i rational
543: Notes:
544: Allowed values for the problem type are general (NEP_GENERAL), and rational
545: (NEP_RATIONAL).
547: This function is used to provide a hint to the NEP solver to exploit certain
548: properties of the nonlinear eigenproblem. This hint may be used or not,
549: depending on the solver. By default, no particular structure is assumed.
551: Level: intermediate
553: .seealso: `NEPSetType()`, `NEPGetProblemType()`, `NEPProblemType`
554: @*/
555: PetscErrorCode NEPSetProblemType(NEP nep,NEPProblemType type)
556: {
557: PetscFunctionBegin;
560: PetscCheck(type==NEP_GENERAL || type==NEP_RATIONAL,PetscObjectComm((PetscObject)nep),PETSC_ERR_ARG_WRONG,"Unknown eigenvalue problem type");
561: if (type != nep->problem_type) {
562: nep->problem_type = type;
563: nep->state = NEP_STATE_INITIAL;
564: }
565: PetscFunctionReturn(PETSC_SUCCESS);
566: }
568: /*@
569: NEPGetProblemType - Gets the problem type from the NEP object.
571: Not Collective
573: Input Parameter:
574: . nep - the nonlinear eigensolver context
576: Output Parameter:
577: . type - the problem type
579: Level: intermediate
581: .seealso: `NEPSetProblemType()`, `NEPProblemType`
582: @*/
583: PetscErrorCode NEPGetProblemType(NEP nep,NEPProblemType *type)
584: {
585: PetscFunctionBegin;
587: PetscAssertPointer(type,2);
588: *type = nep->problem_type;
589: PetscFunctionReturn(PETSC_SUCCESS);
590: }
592: /*@
593: NEPSetTwoSided - Sets the solver to use a two-sided variant so that left
594: eigenvectors are also computed.
596: Logically Collective
598: Input Parameters:
599: + nep - the eigensolver context
600: - twosided - whether the two-sided variant is to be used or not
602: Options Database Keys:
603: . -nep_two_sided <boolean> - Sets/resets the twosided flag
605: Notes:
606: If the user sets twosided=PETSC_TRUE then the solver uses a variant of
607: the algorithm that computes both right and left eigenvectors. This is
608: usually much more costly. This option is not available in all solvers.
610: When using two-sided solvers, the problem matrices must have both the
611: MatMult and MatMultTranspose operations defined.
613: Level: advanced
615: .seealso: `NEPGetTwoSided()`, `NEPGetLeftEigenvector()`
616: @*/
617: PetscErrorCode NEPSetTwoSided(NEP nep,PetscBool twosided)
618: {
619: PetscFunctionBegin;
622: if (twosided!=nep->twosided) {
623: nep->twosided = twosided;
624: nep->state = NEP_STATE_INITIAL;
625: }
626: PetscFunctionReturn(PETSC_SUCCESS);
627: }
629: /*@
630: NEPGetTwoSided - Returns the flag indicating whether a two-sided variant
631: of the algorithm is being used or not.
633: Not Collective
635: Input Parameter:
636: . nep - the eigensolver context
638: Output Parameter:
639: . twosided - the returned flag
641: Level: advanced
643: .seealso: `NEPSetTwoSided()`
644: @*/
645: PetscErrorCode NEPGetTwoSided(NEP nep,PetscBool *twosided)
646: {
647: PetscFunctionBegin;
649: PetscAssertPointer(twosided,2);
650: *twosided = nep->twosided;
651: PetscFunctionReturn(PETSC_SUCCESS);
652: }
654: /*@C
655: NEPSetConvergenceTestFunction - Sets a function to compute the error estimate
656: used in the convergence test.
658: Logically Collective
660: Input Parameters:
661: + nep - nonlinear eigensolver context obtained from NEPCreate()
662: . conv - convergence test function, see NEPConvergenceTestFn for the calling sequence
663: . ctx - context for private data for the convergence routine (may be NULL)
664: - destroy - a routine for destroying the context (may be NULL), see PetscCtxDestroyFn for the calling sequence
666: Note:
667: If the error estimate returned by the convergence test function is less than
668: the tolerance, then the eigenvalue is accepted as converged.
670: Level: advanced
672: .seealso: `NEPSetConvergenceTest()`, `NEPSetTolerances()`
673: @*/
674: PetscErrorCode NEPSetConvergenceTestFunction(NEP nep,NEPConvergenceTestFn *conv,void *ctx,PetscCtxDestroyFn *destroy)
675: {
676: PetscFunctionBegin;
678: if (nep->convergeddestroy) PetscCall((*nep->convergeddestroy)(&nep->convergedctx));
679: nep->convergeduser = conv;
680: nep->convergeddestroy = destroy;
681: nep->convergedctx = ctx;
682: if (conv == NEPConvergedRelative) nep->conv = NEP_CONV_REL;
683: else if (conv == NEPConvergedNorm) nep->conv = NEP_CONV_NORM;
684: else if (conv == NEPConvergedAbsolute) nep->conv = NEP_CONV_ABS;
685: else {
686: nep->conv = NEP_CONV_USER;
687: nep->converged = nep->convergeduser;
688: }
689: PetscFunctionReturn(PETSC_SUCCESS);
690: }
692: /*@
693: NEPSetConvergenceTest - Specifies how to compute the error estimate
694: used in the convergence test.
696: Logically Collective
698: Input Parameters:
699: + nep - nonlinear eigensolver context obtained from NEPCreate()
700: - conv - the type of convergence test
702: Options Database Keys:
703: + -nep_conv_abs - Sets the absolute convergence test
704: . -nep_conv_rel - Sets the convergence test relative to the eigenvalue
705: - -nep_conv_user - Selects the user-defined convergence test
707: Note:
708: The parameter 'conv' can have one of these values
709: + NEP_CONV_ABS - absolute error ||r||
710: . NEP_CONV_REL - error relative to the eigenvalue l, ||r||/|l|
711: . NEP_CONV_NORM - error relative matrix norms, ||r||/sum_i(|f_i(l)|*||A_i||)
712: - NEP_CONV_USER - function set by NEPSetConvergenceTestFunction()
714: Level: intermediate
716: .seealso: `NEPGetConvergenceTest()`, `NEPSetConvergenceTestFunction()`, `NEPSetStoppingTest()`, `NEPConv`
717: @*/
718: PetscErrorCode NEPSetConvergenceTest(NEP nep,NEPConv conv)
719: {
720: PetscFunctionBegin;
723: switch (conv) {
724: case NEP_CONV_ABS: nep->converged = NEPConvergedAbsolute; break;
725: case NEP_CONV_REL: nep->converged = NEPConvergedRelative; break;
726: case NEP_CONV_NORM: nep->converged = NEPConvergedNorm; break;
727: case NEP_CONV_USER:
728: PetscCheck(nep->convergeduser,PetscObjectComm((PetscObject)nep),PETSC_ERR_ORDER,"Must call NEPSetConvergenceTestFunction() first");
729: nep->converged = nep->convergeduser;
730: break;
731: default:
732: SETERRQ(PetscObjectComm((PetscObject)nep),PETSC_ERR_ARG_OUTOFRANGE,"Invalid 'conv' value");
733: }
734: nep->conv = conv;
735: PetscFunctionReturn(PETSC_SUCCESS);
736: }
738: /*@
739: NEPGetConvergenceTest - Gets the method used to compute the error estimate
740: used in the convergence test.
742: Not Collective
744: Input Parameters:
745: . nep - nonlinear eigensolver context obtained from NEPCreate()
747: Output Parameters:
748: . conv - the type of convergence test
750: Level: intermediate
752: .seealso: `NEPSetConvergenceTest()`, `NEPConv`
753: @*/
754: PetscErrorCode NEPGetConvergenceTest(NEP nep,NEPConv *conv)
755: {
756: PetscFunctionBegin;
758: PetscAssertPointer(conv,2);
759: *conv = nep->conv;
760: PetscFunctionReturn(PETSC_SUCCESS);
761: }
763: /*@C
764: NEPSetStoppingTestFunction - Sets a function to decide when to stop the outer
765: iteration of the eigensolver.
767: Logically Collective
769: Input Parameters:
770: + nep - nonlinear eigensolver context obtained from NEPCreate()
771: . stop - the stopping test function, see NEPStoppingTestFn for the calling sequence
772: . ctx - context for private data for the stopping routine (may be NULL)
773: - destroy - a routine for destroying the context (may be NULL), see PetscCtxDestroyFn for the calling sequence
775: Note:
776: Normal usage is to first call the default routine NEPStoppingBasic() and then
777: set reason to NEP_CONVERGED_USER if some user-defined conditions have been
778: met. To let the eigensolver continue iterating, the result must be left as
779: NEP_CONVERGED_ITERATING.
781: Level: advanced
783: .seealso: `NEPSetStoppingTest()`, `NEPStoppingBasic()`
784: @*/
785: PetscErrorCode NEPSetStoppingTestFunction(NEP nep,NEPStoppingTestFn *stop,void *ctx,PetscCtxDestroyFn *destroy)
786: {
787: PetscFunctionBegin;
789: if (nep->stoppingdestroy) PetscCall((*nep->stoppingdestroy)(&nep->stoppingctx));
790: nep->stoppinguser = stop;
791: nep->stoppingdestroy = destroy;
792: nep->stoppingctx = ctx;
793: if (stop == NEPStoppingBasic) nep->stop = NEP_STOP_BASIC;
794: else {
795: nep->stop = NEP_STOP_USER;
796: nep->stopping = nep->stoppinguser;
797: }
798: PetscFunctionReturn(PETSC_SUCCESS);
799: }
801: /*@
802: NEPSetStoppingTest - Specifies how to decide the termination of the outer
803: loop of the eigensolver.
805: Logically Collective
807: Input Parameters:
808: + nep - nonlinear eigensolver context obtained from NEPCreate()
809: - stop - the type of stopping test
811: Options Database Keys:
812: + -nep_stop_basic - Sets the default stopping test
813: - -nep_stop_user - Selects the user-defined stopping test
815: Note:
816: The parameter 'stop' can have one of these values
817: + NEP_STOP_BASIC - default stopping test
818: - NEP_STOP_USER - function set by NEPSetStoppingTestFunction()
820: Level: advanced
822: .seealso: `NEPGetStoppingTest()`, `NEPSetStoppingTestFunction()`, `NEPSetConvergenceTest()`, `NEPStop`
823: @*/
824: PetscErrorCode NEPSetStoppingTest(NEP nep,NEPStop stop)
825: {
826: PetscFunctionBegin;
829: switch (stop) {
830: case NEP_STOP_BASIC: nep->stopping = NEPStoppingBasic; break;
831: case NEP_STOP_USER:
832: PetscCheck(nep->stoppinguser,PetscObjectComm((PetscObject)nep),PETSC_ERR_ORDER,"Must call NEPSetStoppingTestFunction() first");
833: nep->stopping = nep->stoppinguser;
834: break;
835: default:
836: SETERRQ(PetscObjectComm((PetscObject)nep),PETSC_ERR_ARG_OUTOFRANGE,"Invalid 'stop' value");
837: }
838: nep->stop = stop;
839: PetscFunctionReturn(PETSC_SUCCESS);
840: }
842: /*@
843: NEPGetStoppingTest - Gets the method used to decide the termination of the outer
844: loop of the eigensolver.
846: Not Collective
848: Input Parameters:
849: . nep - nonlinear eigensolver context obtained from NEPCreate()
851: Output Parameters:
852: . stop - the type of stopping test
854: Level: advanced
856: .seealso: `NEPSetStoppingTest()`, `NEPStop`
857: @*/
858: PetscErrorCode NEPGetStoppingTest(NEP nep,NEPStop *stop)
859: {
860: PetscFunctionBegin;
862: PetscAssertPointer(stop,2);
863: *stop = nep->stop;
864: PetscFunctionReturn(PETSC_SUCCESS);
865: }
867: /*@
868: NEPSetTrackAll - Specifies if the solver must compute the residual of all
869: approximate eigenpairs or not.
871: Logically Collective
873: Input Parameters:
874: + nep - the eigensolver context
875: - trackall - whether compute all residuals or not
877: Notes:
878: If the user sets trackall=PETSC_TRUE then the solver explicitly computes
879: the residual for each eigenpair approximation. Computing the residual is
880: usually an expensive operation and solvers commonly compute the associated
881: residual to the first unconverged eigenpair.
883: The option '-nep_monitor_all' automatically activates this option.
885: Level: developer
887: .seealso: `NEPGetTrackAll()`
888: @*/
889: PetscErrorCode NEPSetTrackAll(NEP nep,PetscBool trackall)
890: {
891: PetscFunctionBegin;
894: nep->trackall = trackall;
895: PetscFunctionReturn(PETSC_SUCCESS);
896: }
898: /*@
899: NEPGetTrackAll - Returns the flag indicating whether all residual norms must
900: be computed or not.
902: Not Collective
904: Input Parameter:
905: . nep - the eigensolver context
907: Output Parameter:
908: . trackall - the returned flag
910: Level: developer
912: .seealso: `NEPSetTrackAll()`
913: @*/
914: PetscErrorCode NEPGetTrackAll(NEP nep,PetscBool *trackall)
915: {
916: PetscFunctionBegin;
918: PetscAssertPointer(trackall,2);
919: *trackall = nep->trackall;
920: PetscFunctionReturn(PETSC_SUCCESS);
921: }
923: /*@
924: NEPSetRefine - Specifies the refinement type (and options) to be used
925: after the solve.
927: Logically Collective
929: Input Parameters:
930: + nep - the nonlinear eigensolver context
931: . refine - refinement type
932: . npart - number of partitions of the communicator
933: . tol - the convergence tolerance
934: . its - maximum number of refinement iterations
935: - scheme - which scheme to be used for solving the involved linear systems
937: Options Database Keys:
938: + -nep_refine <type> - refinement type, one of <none,simple,multiple>
939: . -nep_refine_partitions <n> - the number of partitions
940: . -nep_refine_tol <tol> - the tolerance
941: . -nep_refine_its <its> - number of iterations
942: - -nep_refine_scheme - to set the scheme for the linear solves
944: Notes:
945: By default, iterative refinement is disabled, since it may be very
946: costly. There are two possible refinement strategies, simple and multiple.
947: The simple approach performs iterative refinement on each of the
948: converged eigenpairs individually, whereas the multiple strategy works
949: with the invariant pair as a whole, refining all eigenpairs simultaneously.
950: The latter may be required for the case of multiple eigenvalues.
952: In some cases, especially when using direct solvers within the
953: iterative refinement method, it may be helpful for improved scalability
954: to split the communicator in several partitions. The npart parameter
955: indicates how many partitions to use (defaults to 1).
957: The tol and its parameters specify the stopping criterion. In the simple
958: method, refinement continues until the residual of each eigenpair is
959: below the tolerance (tol defaults to the NEP tol, but may be set to a
960: different value). In contrast, the multiple method simply performs its
961: refinement iterations (just one by default).
963: The scheme argument is used to change the way in which linear systems are
964: solved. Possible choices are explicit, mixed block elimination (MBE),
965: and Schur complement.
967: Use PETSC_CURRENT to retain the current value of npart, tol or its. Use
968: PETSC_DETERMINE to assign a default value.
970: Level: intermediate
972: .seealso: `NEPGetRefine()`
973: @*/
974: PetscErrorCode NEPSetRefine(NEP nep,NEPRefine refine,PetscInt npart,PetscReal tol,PetscInt its,NEPRefineScheme scheme)
975: {
976: PetscMPIInt size;
978: PetscFunctionBegin;
985: nep->refine = refine;
986: if (refine) { /* process parameters only if not REFINE_NONE */
987: if (npart!=nep->npart) {
988: PetscCall(PetscSubcommDestroy(&nep->refinesubc));
989: PetscCall(KSPDestroy(&nep->refineksp));
990: }
991: if (npart == PETSC_DETERMINE) {
992: nep->npart = 1;
993: } else if (npart != PETSC_CURRENT) {
994: PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)nep),&size));
995: PetscCheck(npart>0 && npart<=size,PetscObjectComm((PetscObject)nep),PETSC_ERR_ARG_OUTOFRANGE,"Illegal value of npart");
996: nep->npart = npart;
997: }
998: if (tol == (PetscReal)PETSC_DETERMINE) {
999: nep->rtol = PETSC_DETERMINE;
1000: } else if (tol != (PetscReal)PETSC_CURRENT) {
1001: PetscCheck(tol>0.0,PetscObjectComm((PetscObject)nep),PETSC_ERR_ARG_OUTOFRANGE,"Illegal value of tol. Must be > 0");
1002: nep->rtol = tol;
1003: }
1004: if (its==PETSC_DETERMINE) {
1005: nep->rits = PETSC_DETERMINE;
1006: } else if (its != PETSC_CURRENT) {
1007: PetscCheck(its>=0,PetscObjectComm((PetscObject)nep),PETSC_ERR_ARG_OUTOFRANGE,"Illegal value of its. Must be >= 0");
1008: nep->rits = its;
1009: }
1010: nep->scheme = scheme;
1011: }
1012: nep->state = NEP_STATE_INITIAL;
1013: PetscFunctionReturn(PETSC_SUCCESS);
1014: }
1016: /*@
1017: NEPGetRefine - Gets the refinement strategy used by the NEP object, and the
1018: associated parameters.
1020: Not Collective
1022: Input Parameter:
1023: . nep - the nonlinear eigensolver context
1025: Output Parameters:
1026: + refine - refinement type
1027: . npart - number of partitions of the communicator
1028: . tol - the convergence tolerance
1029: . its - maximum number of refinement iterations
1030: - scheme - the scheme used for solving linear systems
1032: Level: intermediate
1034: Note:
1035: The user can specify NULL for any parameter that is not needed.
1037: .seealso: `NEPSetRefine()`
1038: @*/
1039: PetscErrorCode NEPGetRefine(NEP nep,NEPRefine *refine,PetscInt *npart,PetscReal *tol,PetscInt *its,NEPRefineScheme *scheme)
1040: {
1041: PetscFunctionBegin;
1043: if (refine) *refine = nep->refine;
1044: if (npart) *npart = nep->npart;
1045: if (tol) *tol = nep->rtol;
1046: if (its) *its = nep->rits;
1047: if (scheme) *scheme = nep->scheme;
1048: PetscFunctionReturn(PETSC_SUCCESS);
1049: }
1051: /*@
1052: NEPSetOptionsPrefix - Sets the prefix used for searching for all
1053: NEP options in the database.
1055: Logically Collective
1057: Input Parameters:
1058: + nep - the nonlinear eigensolver context
1059: - prefix - the prefix string to prepend to all NEP option requests
1061: Notes:
1062: A hyphen (-) must NOT be given at the beginning of the prefix name.
1063: The first character of all runtime options is AUTOMATICALLY the
1064: hyphen.
1066: For example, to distinguish between the runtime options for two
1067: different NEP contexts, one could call
1068: .vb
1069: NEPSetOptionsPrefix(nep1,"neig1_")
1070: NEPSetOptionsPrefix(nep2,"neig2_")
1071: .ve
1073: Level: advanced
1075: .seealso: `NEPAppendOptionsPrefix()`, `NEPGetOptionsPrefix()`
1076: @*/
1077: PetscErrorCode NEPSetOptionsPrefix(NEP nep,const char *prefix)
1078: {
1079: PetscFunctionBegin;
1081: if (!nep->V) PetscCall(NEPGetBV(nep,&nep->V));
1082: PetscCall(BVSetOptionsPrefix(nep->V,prefix));
1083: if (!nep->ds) PetscCall(NEPGetDS(nep,&nep->ds));
1084: PetscCall(DSSetOptionsPrefix(nep->ds,prefix));
1085: if (!nep->rg) PetscCall(NEPGetRG(nep,&nep->rg));
1086: PetscCall(RGSetOptionsPrefix(nep->rg,prefix));
1087: PetscCall(PetscObjectSetOptionsPrefix((PetscObject)nep,prefix));
1088: PetscFunctionReturn(PETSC_SUCCESS);
1089: }
1091: /*@
1092: NEPAppendOptionsPrefix - Appends to the prefix used for searching for all
1093: NEP options in the database.
1095: Logically Collective
1097: Input Parameters:
1098: + nep - the nonlinear eigensolver context
1099: - prefix - the prefix string to prepend to all NEP option requests
1101: Notes:
1102: A hyphen (-) must NOT be given at the beginning of the prefix name.
1103: The first character of all runtime options is AUTOMATICALLY the hyphen.
1105: Level: advanced
1107: .seealso: `NEPSetOptionsPrefix()`, `NEPGetOptionsPrefix()`
1108: @*/
1109: PetscErrorCode NEPAppendOptionsPrefix(NEP nep,const char *prefix)
1110: {
1111: PetscFunctionBegin;
1113: if (!nep->V) PetscCall(NEPGetBV(nep,&nep->V));
1114: PetscCall(BVAppendOptionsPrefix(nep->V,prefix));
1115: if (!nep->ds) PetscCall(NEPGetDS(nep,&nep->ds));
1116: PetscCall(DSAppendOptionsPrefix(nep->ds,prefix));
1117: if (!nep->rg) PetscCall(NEPGetRG(nep,&nep->rg));
1118: PetscCall(RGAppendOptionsPrefix(nep->rg,prefix));
1119: PetscCall(PetscObjectAppendOptionsPrefix((PetscObject)nep,prefix));
1120: PetscFunctionReturn(PETSC_SUCCESS);
1121: }
1123: /*@
1124: NEPGetOptionsPrefix - Gets the prefix used for searching for all
1125: NEP options in the database.
1127: Not Collective
1129: Input Parameters:
1130: . nep - the nonlinear eigensolver context
1132: Output Parameters:
1133: . prefix - pointer to the prefix string used is returned
1135: Note:
1136: On the Fortran side, the user should pass in a string 'prefix' of
1137: sufficient length to hold the prefix.
1139: Level: advanced
1141: .seealso: `NEPSetOptionsPrefix()`, `NEPAppendOptionsPrefix()`
1142: @*/
1143: PetscErrorCode NEPGetOptionsPrefix(NEP nep,const char *prefix[])
1144: {
1145: PetscFunctionBegin;
1147: PetscAssertPointer(prefix,2);
1148: PetscCall(PetscObjectGetOptionsPrefix((PetscObject)nep,prefix));
1149: PetscFunctionReturn(PETSC_SUCCESS);
1150: }