Actual source code: epssetup.c
slepc-main 2024-12-17
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: EPS routines related to problem setup
12: */
14: #include <slepc/private/epsimpl.h>
16: /*
17: Let the solver choose the ST type that should be used by default,
18: otherwise set it to SHIFT.
19: This is called at EPSSetFromOptions (before STSetFromOptions)
20: and also at EPSSetUp (in case EPSSetFromOptions was not called).
21: */
22: PetscErrorCode EPSSetDefaultST(EPS eps)
23: {
24: PetscFunctionBegin;
25: PetscTryTypeMethod(eps,setdefaultst);
26: if (!((PetscObject)eps->st)->type_name) PetscCall(STSetType(eps->st,STSHIFT));
27: PetscFunctionReturn(PETSC_SUCCESS);
28: }
30: /*
31: This is done by preconditioned eigensolvers that use the PC only.
32: It sets STPRECOND with KSPPREONLY.
33: */
34: PetscErrorCode EPSSetDefaultST_Precond(EPS eps)
35: {
36: KSP ksp;
38: PetscFunctionBegin;
39: if (!((PetscObject)eps->st)->type_name) PetscCall(STSetType(eps->st,STPRECOND));
40: PetscCall(STGetKSP(eps->st,&ksp));
41: if (!((PetscObject)ksp)->type_name) PetscCall(KSPSetType(ksp,KSPPREONLY));
42: PetscFunctionReturn(PETSC_SUCCESS);
43: }
45: /*
46: This is done by preconditioned eigensolvers that can also use the KSP.
47: It sets STPRECOND with the default KSP (GMRES) and maxit=5.
48: */
49: PetscErrorCode EPSSetDefaultST_GMRES(EPS eps)
50: {
51: KSP ksp;
53: PetscFunctionBegin;
54: if (!((PetscObject)eps->st)->type_name) PetscCall(STSetType(eps->st,STPRECOND));
55: PetscCall(STPrecondSetKSPHasMat(eps->st,PETSC_TRUE));
56: PetscCall(STGetKSP(eps->st,&ksp));
57: if (!((PetscObject)ksp)->type_name) {
58: PetscCall(KSPSetType(ksp,KSPGMRES));
59: PetscCall(KSPSetTolerances(ksp,PETSC_CURRENT,PETSC_CURRENT,PETSC_CURRENT,5));
60: }
61: PetscFunctionReturn(PETSC_SUCCESS);
62: }
64: #if defined(SLEPC_HAVE_SCALAPACK) || defined(SLEPC_HAVE_ELPA) || defined(SLEPC_HAVE_ELEMENTAL) || defined(SLEPC_HAVE_EVSL)
65: /*
66: This is for direct eigensolvers that work with A and B directly, so
67: no need to factorize B.
68: */
69: PetscErrorCode EPSSetDefaultST_NoFactor(EPS eps)
70: {
71: KSP ksp;
72: PC pc;
74: PetscFunctionBegin;
75: if (!((PetscObject)eps->st)->type_name) PetscCall(STSetType(eps->st,STSHIFT));
76: PetscCall(STGetKSP(eps->st,&ksp));
77: if (!((PetscObject)ksp)->type_name) PetscCall(KSPSetType(ksp,KSPPREONLY));
78: PetscCall(KSPGetPC(ksp,&pc));
79: if (!((PetscObject)pc)->type_name) PetscCall(PCSetType(pc,PCNONE));
80: PetscFunctionReturn(PETSC_SUCCESS);
81: }
82: #endif
84: /*
85: Check that the ST selected by the user is compatible with the EPS solver and options
86: */
87: static PetscErrorCode EPSCheckCompatibleST(EPS eps)
88: {
89: PetscBool precond,shift,sinvert,cayley,lyapii;
90: #if defined(PETSC_USE_COMPLEX)
91: PetscScalar sigma;
92: #endif
94: PetscFunctionBegin;
95: PetscCall(PetscObjectTypeCompare((PetscObject)eps->st,STPRECOND,&precond));
96: PetscCall(PetscObjectTypeCompare((PetscObject)eps->st,STSHIFT,&shift));
97: PetscCall(PetscObjectTypeCompare((PetscObject)eps->st,STSINVERT,&sinvert));
98: PetscCall(PetscObjectTypeCompare((PetscObject)eps->st,STCAYLEY,&cayley));
100: /* preconditioned eigensolvers */
101: PetscCheck(eps->categ!=EPS_CATEGORY_PRECOND || precond,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"This solver requires ST=PRECOND");
102: PetscCheck(eps->categ==EPS_CATEGORY_PRECOND || !precond,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"STPRECOND is intended for preconditioned eigensolvers only");
104: /* harmonic extraction */
105: PetscCheck(precond || shift || !eps->extraction || eps->extraction==EPS_RITZ,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"Cannot use a spectral transformation combined with harmonic extraction");
107: /* real shifts in Hermitian problems */
108: #if defined(PETSC_USE_COMPLEX)
109: PetscCall(STGetShift(eps->st,&sigma));
110: PetscCheck(!eps->ishermitian || PetscImaginaryPart(sigma)==0.0,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"Hermitian problems are not compatible with complex shifts");
111: #endif
113: /* Cayley with PGNHEP */
114: PetscCheck(!cayley || eps->problem_type!=EPS_PGNHEP,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"Cayley spectral transformation is not compatible with PGNHEP");
116: /* make sure that the user does not specify smallest magnitude with shift-and-invert */
117: if ((cayley || sinvert) && (eps->categ==EPS_CATEGORY_KRYLOV || eps->categ==EPS_CATEGORY_OTHER)) {
118: PetscCall(PetscObjectTypeCompare((PetscObject)eps,EPSLYAPII,&lyapii));
119: PetscCheck(lyapii || eps->which==EPS_TARGET_MAGNITUDE || eps->which==EPS_TARGET_REAL || eps->which==EPS_TARGET_IMAGINARY || eps->which==EPS_ALL || eps->which==EPS_WHICH_USER,PetscObjectComm((PetscObject)eps),PETSC_ERR_USER_INPUT,"Shift-and-invert requires a target 'which' (see EPSSetWhichEigenpairs), for instance -st_type sinvert -eps_target 0 -eps_target_magnitude");
120: }
121: PetscFunctionReturn(PETSC_SUCCESS);
122: }
124: /*
125: MatEstimateSpectralRange_EPS: estimate the spectral range [left,right] of a
126: symmetric/Hermitian matrix A using an auxiliary EPS object
127: */
128: PetscErrorCode MatEstimateSpectralRange_EPS(Mat A,PetscReal *left,PetscReal *right)
129: {
130: PetscInt nconv;
131: PetscScalar eig0;
132: PetscReal tol=1e-3,errest=tol;
133: EPS eps;
135: PetscFunctionBegin;
136: *left = 0.0; *right = 0.0;
137: PetscCall(EPSCreate(PetscObjectComm((PetscObject)A),&eps));
138: PetscCall(EPSSetOptionsPrefix(eps,"eps_filter_"));
139: PetscCall(EPSSetOperators(eps,A,NULL));
140: PetscCall(EPSSetProblemType(eps,EPS_HEP));
141: PetscCall(EPSSetTolerances(eps,tol,50));
142: PetscCall(EPSSetConvergenceTest(eps,EPS_CONV_ABS));
143: PetscCall(EPSSetWhichEigenpairs(eps,EPS_SMALLEST_REAL));
144: PetscCall(EPSSolve(eps));
145: PetscCall(EPSGetConverged(eps,&nconv));
146: if (nconv>0) {
147: PetscCall(EPSGetEigenvalue(eps,0,&eig0,NULL));
148: PetscCall(EPSGetErrorEstimate(eps,0,&errest));
149: } else eig0 = eps->eigr[0];
150: *left = PetscRealPart(eig0)-errest;
151: PetscCall(EPSSetWhichEigenpairs(eps,EPS_LARGEST_REAL));
152: PetscCall(EPSSolve(eps));
153: PetscCall(EPSGetConverged(eps,&nconv));
154: if (nconv>0) {
155: PetscCall(EPSGetEigenvalue(eps,0,&eig0,NULL));
156: PetscCall(EPSGetErrorEstimate(eps,0,&errest));
157: } else eig0 = eps->eigr[0];
158: *right = PetscRealPart(eig0)+errest;
159: PetscCall(EPSDestroy(&eps));
160: PetscFunctionReturn(PETSC_SUCCESS);
161: }
163: /*
164: EPSSetUpSort_Basic: configure the EPS sorting criterion according to 'which'
165: */
166: PetscErrorCode EPSSetUpSort_Basic(EPS eps)
167: {
168: PetscFunctionBegin;
169: switch (eps->which) {
170: case EPS_LARGEST_MAGNITUDE:
171: eps->sc->comparison = SlepcCompareLargestMagnitude;
172: eps->sc->comparisonctx = NULL;
173: break;
174: case EPS_SMALLEST_MAGNITUDE:
175: eps->sc->comparison = SlepcCompareSmallestMagnitude;
176: eps->sc->comparisonctx = NULL;
177: break;
178: case EPS_LARGEST_REAL:
179: eps->sc->comparison = SlepcCompareLargestReal;
180: eps->sc->comparisonctx = NULL;
181: break;
182: case EPS_SMALLEST_REAL:
183: eps->sc->comparison = SlepcCompareSmallestReal;
184: eps->sc->comparisonctx = NULL;
185: break;
186: case EPS_LARGEST_IMAGINARY:
187: eps->sc->comparison = SlepcCompareLargestImaginary;
188: eps->sc->comparisonctx = NULL;
189: break;
190: case EPS_SMALLEST_IMAGINARY:
191: eps->sc->comparison = SlepcCompareSmallestImaginary;
192: eps->sc->comparisonctx = NULL;
193: break;
194: case EPS_TARGET_MAGNITUDE:
195: eps->sc->comparison = SlepcCompareTargetMagnitude;
196: eps->sc->comparisonctx = &eps->target;
197: break;
198: case EPS_TARGET_REAL:
199: eps->sc->comparison = SlepcCompareTargetReal;
200: eps->sc->comparisonctx = &eps->target;
201: break;
202: case EPS_TARGET_IMAGINARY:
203: #if defined(PETSC_USE_COMPLEX)
204: eps->sc->comparison = SlepcCompareTargetImaginary;
205: eps->sc->comparisonctx = &eps->target;
206: #endif
207: break;
208: case EPS_ALL:
209: eps->sc->comparison = SlepcCompareSmallestReal;
210: eps->sc->comparisonctx = NULL;
211: break;
212: case EPS_WHICH_USER:
213: break;
214: }
215: eps->sc->map = NULL;
216: eps->sc->mapobj = NULL;
217: PetscFunctionReturn(PETSC_SUCCESS);
218: }
220: /*
221: EPSSetUpSort_Default: configure both EPS and DS sorting criterion
222: */
223: PetscErrorCode EPSSetUpSort_Default(EPS eps)
224: {
225: SlepcSC sc;
226: PetscBool istrivial;
228: PetscFunctionBegin;
229: /* fill sorting criterion context */
230: PetscCall(EPSSetUpSort_Basic(eps));
231: /* fill sorting criterion for DS */
232: PetscCall(DSGetSlepcSC(eps->ds,&sc));
233: PetscCall(RGIsTrivial(eps->rg,&istrivial));
234: sc->rg = istrivial? NULL: eps->rg;
235: sc->comparison = eps->sc->comparison;
236: sc->comparisonctx = eps->sc->comparisonctx;
237: sc->map = SlepcMap_ST;
238: sc->mapobj = (PetscObject)eps->st;
239: PetscFunctionReturn(PETSC_SUCCESS);
240: }
242: /*@
243: EPSSetDSType - Sets the type of the internal DS object based on the current
244: settings of the eigenvalue solver.
246: Collective
248: Input Parameter:
249: . eps - eigenproblem solver context
251: Note:
252: This function need not be called explicitly, since it will be called at
253: both EPSSetFromOptions() and EPSSetUp().
255: Level: developer
257: .seealso: EPSSetFromOptions(), EPSSetUp()
258: @*/
259: PetscErrorCode EPSSetDSType(EPS eps)
260: {
261: PetscFunctionBegin;
263: PetscTryTypeMethod(eps,setdstype);
264: PetscFunctionReturn(PETSC_SUCCESS);
265: }
267: /*@
268: EPSSetUp - Sets up all the internal data structures necessary for the
269: execution of the eigensolver. Then calls STSetUp() for any set-up
270: operations associated to the ST object.
272: Collective
274: Input Parameter:
275: . eps - eigenproblem solver context
277: Notes:
278: This function need not be called explicitly in most cases, since EPSSolve()
279: calls it. It can be useful when one wants to measure the set-up time
280: separately from the solve time.
282: Level: developer
284: .seealso: EPSCreate(), EPSSolve(), EPSDestroy(), STSetUp(), EPSSetInitialSpace()
285: @*/
286: PetscErrorCode EPSSetUp(EPS eps)
287: {
288: Mat A,B;
289: PetscInt k,nmat;
290: PetscBool flg;
291: EPSStoppingCtx ctx;
293: PetscFunctionBegin;
295: if (eps->state) PetscFunctionReturn(PETSC_SUCCESS);
296: PetscCall(PetscLogEventBegin(EPS_SetUp,eps,0,0,0));
298: /* reset the convergence flag from the previous solves */
299: eps->reason = EPS_CONVERGED_ITERATING;
301: /* Set default solver type (EPSSetFromOptions was not called) */
302: if (!((PetscObject)eps)->type_name) PetscCall(EPSSetType(eps,EPSKRYLOVSCHUR));
303: if (!eps->st) PetscCall(EPSGetST(eps,&eps->st));
304: PetscCall(EPSSetDefaultST(eps));
306: PetscCall(STSetTransform(eps->st,PETSC_TRUE));
307: PetscCall(STSetStructured(eps->st,PETSC_FALSE));
308: if (eps->useds && !eps->ds) PetscCall(EPSGetDS(eps,&eps->ds));
309: if (eps->useds) PetscCall(EPSSetDSType(eps));
310: if (eps->twosided) {
311: PetscCheck(!eps->ishermitian || (eps->isgeneralized && !eps->ispositive),PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"Two-sided methods are not intended for %s problems",SLEPC_STRING_HERMITIAN);
312: }
313: if (!eps->rg) PetscCall(EPSGetRG(eps,&eps->rg));
314: if (!((PetscObject)eps->rg)->type_name) PetscCall(RGSetType(eps->rg,RGINTERVAL));
316: /* Set problem dimensions */
317: PetscCall(STGetNumMatrices(eps->st,&nmat));
318: PetscCheck(nmat,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_WRONGSTATE,"EPSSetOperators must be called first");
319: PetscCall(STMatGetSize(eps->st,&eps->n,NULL));
320: PetscCall(STMatGetLocalSize(eps->st,&eps->nloc,NULL));
322: /* Set default problem type */
323: if (!eps->problem_type) {
324: if (nmat==1) PetscCall(EPSSetProblemType(eps,EPS_NHEP));
325: else PetscCall(EPSSetProblemType(eps,EPS_GNHEP));
326: } else if (nmat==1 && eps->isgeneralized) {
327: PetscCall(PetscInfo(eps,"Eigenproblem set as generalized but no matrix B was provided; reverting to a standard eigenproblem\n"));
328: eps->isgeneralized = PETSC_FALSE;
329: eps->problem_type = eps->ishermitian? EPS_HEP: EPS_NHEP;
330: } else PetscCheck(nmat==1 || eps->isgeneralized,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_INCOMP,"Inconsistent EPS state: the problem type does not match the number of matrices");
332: if (eps->isstructured) {
333: /* make sure the user has set the appropriate matrix */
334: PetscCall(STGetMatrix(eps->st,0,&A));
335: if (eps->problem_type==EPS_BSE) PetscCall(SlepcCheckMatStruct(A,SLEPC_MAT_STRUCT_BSE,NULL));
336: }
338: /* safeguard for small problems */
339: if (eps->isstructured) {
340: if (2*eps->nev > eps->n) eps->nev = eps->n/2;
341: if (2*eps->ncv > eps->n) eps->ncv = eps->n/2;
342: } else {
343: if (eps->nev > eps->n) eps->nev = eps->n;
344: if (eps->ncv > eps->n) eps->ncv = eps->n;
345: }
347: /* check some combinations of eps->which */
348: PetscCheck(!eps->ishermitian || (eps->isgeneralized && !eps->ispositive) || (eps->which!=EPS_LARGEST_IMAGINARY && eps->which!=EPS_SMALLEST_IMAGINARY && eps->which!=EPS_TARGET_IMAGINARY),PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"Sorting the eigenvalues along the imaginary axis is not allowed when all eigenvalues are real");
350: /* initialization of matrix norms */
351: if (eps->conv==EPS_CONV_NORM) {
352: if (!eps->nrma) {
353: PetscCall(STGetMatrix(eps->st,0,&A));
354: PetscCall(MatNorm(A,NORM_INFINITY,&eps->nrma));
355: }
356: if (nmat>1 && !eps->nrmb) {
357: PetscCall(STGetMatrix(eps->st,1,&B));
358: PetscCall(MatNorm(B,NORM_INFINITY,&eps->nrmb));
359: }
360: }
362: /* call specific solver setup */
363: PetscUseTypeMethod(eps,setup);
365: /* threshold stopping test */
366: if (eps->stop==EPS_STOP_THRESHOLD) {
367: PetscCheck(eps->thres!=PETSC_MIN_REAL,PetscObjectComm((PetscObject)eps),PETSC_ERR_USER_INPUT,"Must give a threshold value with EPSSetThreshold()");
368: PetscCheck(eps->which==EPS_LARGEST_MAGNITUDE || eps->which==EPS_SMALLEST_MAGNITUDE || eps->which==EPS_LARGEST_REAL || eps->which==EPS_SMALLEST_REAL || eps->which==EPS_TARGET_MAGNITUDE,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"Threshold stopping test can only be used with largest/smallest/target magnitude or largest/smallest real selection of eigenvalues");
369: if (eps->which==EPS_LARGEST_REAL || eps->which==EPS_SMALLEST_REAL) PetscCheck(eps->problem_type==EPS_HEP || eps->problem_type==EPS_GHEP || eps->problem_type==EPS_BSE,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"Threshold stopping test with largest/smallest real can only be used in problems that have all eigenvaues real");
370: else PetscCheck(eps->thres>0.0,PetscObjectComm((PetscObject)eps),PETSC_ERR_USER_INPUT,"In case of largest/smallest/target magnitude the threshold value must be positive");
371: PetscCheck(eps->which==EPS_LARGEST_MAGNITUDE || eps->which==EPS_TARGET_MAGNITUDE || !eps->threlative,PetscObjectComm((PetscObject)eps),PETSC_ERR_USER_INPUT,"Can only use a relative threshold with largest/target magnitude selection of eigenvalues");
372: PetscCall(PetscNew(&ctx));
373: ctx->thres = eps->thres;
374: ctx->threlative = eps->threlative;
375: ctx->which = eps->which;
376: PetscCall(EPSSetStoppingTestFunction(eps,EPSStoppingThreshold,ctx,PetscCtxDestroyDefault));
377: }
379: /* if purification is set, check that it really makes sense */
380: if (eps->purify) {
381: if (eps->categ==EPS_CATEGORY_PRECOND || eps->categ==EPS_CATEGORY_CONTOUR) eps->purify = PETSC_FALSE;
382: else {
383: if (!eps->isgeneralized) eps->purify = PETSC_FALSE;
384: else if (!eps->ishermitian && !eps->ispositive) eps->purify = PETSC_FALSE;
385: else {
386: PetscCall(PetscObjectTypeCompare((PetscObject)eps->st,STCAYLEY,&flg));
387: if (flg) eps->purify = PETSC_FALSE;
388: }
389: }
390: }
392: /* set tolerance if not yet set */
393: if (eps->tol==(PetscReal)PETSC_DETERMINE) eps->tol = SLEPC_DEFAULT_TOL;
395: /* set up sorting criterion */
396: PetscTryTypeMethod(eps,setupsort);
398: /* Build balancing matrix if required */
399: if (eps->balance!=EPS_BALANCE_USER) {
400: PetscCall(STSetBalanceMatrix(eps->st,NULL));
401: if (!eps->ishermitian && (eps->balance==EPS_BALANCE_ONESIDE || eps->balance==EPS_BALANCE_TWOSIDE)) {
402: if (!eps->D) PetscCall(BVCreateVec(eps->V,&eps->D));
403: PetscCall(EPSBuildBalance_Krylov(eps));
404: PetscCall(STSetBalanceMatrix(eps->st,eps->D));
405: }
406: }
408: /* Setup ST */
409: PetscCall(STSetUp(eps->st));
410: PetscCall(EPSCheckCompatibleST(eps));
412: /* process deflation and initial vectors */
413: if (eps->nds<0) {
414: PetscCheck(!eps->isstructured,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"Deflation space is not supported in structured eigenproblems");
415: k = -eps->nds;
416: PetscCall(BVInsertConstraints(eps->V,&k,eps->defl));
417: PetscCall(SlepcBasisDestroy_Private(&eps->nds,&eps->defl));
418: eps->nds = k;
419: PetscCall(STCheckNullSpace(eps->st,eps->V));
420: }
421: if (eps->nini<0) {
422: k = -eps->nini;
423: PetscCheck(k<=eps->ncv,PetscObjectComm((PetscObject)eps),PETSC_ERR_USER_INPUT,"The number of initial vectors is larger than ncv");
424: PetscCall(BVInsertVecs(eps->V,0,&k,eps->IS,PETSC_TRUE));
425: PetscCall(SlepcBasisDestroy_Private(&eps->nini,&eps->IS));
426: eps->nini = k;
427: }
428: if (eps->twosided && eps->ninil<0) {
429: k = -eps->ninil;
430: PetscCheck(k<=eps->ncv,PetscObjectComm((PetscObject)eps),PETSC_ERR_USER_INPUT,"The number of left initial vectors is larger than ncv");
431: PetscCall(BVInsertVecs(eps->W,0,&k,eps->ISL,PETSC_TRUE));
432: PetscCall(SlepcBasisDestroy_Private(&eps->ninil,&eps->ISL));
433: eps->ninil = k;
434: }
436: PetscCall(PetscLogEventEnd(EPS_SetUp,eps,0,0,0));
437: eps->state = EPS_STATE_SETUP;
438: PetscFunctionReturn(PETSC_SUCCESS);
439: }
441: /*@
442: EPSSetOperators - Sets the matrices associated with the eigenvalue problem.
444: Collective
446: Input Parameters:
447: + eps - the eigenproblem solver context
448: . A - the matrix associated with the eigensystem
449: - B - the second matrix in the case of generalized eigenproblems
451: Notes:
452: To specify a standard eigenproblem, use NULL for parameter B.
454: It must be called before EPSSetUp(). If it is called again after EPSSetUp() and
455: the matrix sizes have changed then the EPS object is reset.
457: For structured eigenproblem types such as EPS_BSE (see EPSSetProblemType()), the
458: provided matrices must have been created with the corresponding helper function,
459: i.e., MatCreateBSE().
461: Level: beginner
463: .seealso: EPSSolve(), EPSSetUp(), EPSReset(), EPSGetST(), STGetMatrix(), EPSSetProblemType()
464: @*/
465: PetscErrorCode EPSSetOperators(EPS eps,Mat A,Mat B)
466: {
467: PetscInt m,n,m0,mloc,nloc,mloc0,nmat;
468: Mat mat[2];
470: PetscFunctionBegin;
474: PetscCheckSameComm(eps,1,A,2);
475: if (B) PetscCheckSameComm(eps,1,B,3);
477: /* Check matrix sizes */
478: PetscCall(MatGetSize(A,&m,&n));
479: PetscCall(MatGetLocalSize(A,&mloc,&nloc));
480: PetscCheck(m==n,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_WRONG,"A is a non-square matrix (%" PetscInt_FMT " rows, %" PetscInt_FMT " cols)",m,n);
481: PetscCheck(mloc==nloc,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_WRONG,"A does not have equal row and column sizes (%" PetscInt_FMT ", %" PetscInt_FMT ")",mloc,nloc);
482: if (B) {
483: PetscCall(MatGetSize(B,&m0,&n));
484: PetscCall(MatGetLocalSize(B,&mloc0,&nloc));
485: PetscCheck(m0==n,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_WRONG,"B is a non-square matrix (%" PetscInt_FMT " rows, %" PetscInt_FMT " cols)",m0,n);
486: PetscCheck(mloc0==nloc,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_WRONG,"B does not have equal row and column local sizes (%" PetscInt_FMT ", %" PetscInt_FMT ")",mloc0,nloc);
487: PetscCheck(m==m0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_INCOMP,"Dimensions of A and B do not match (%" PetscInt_FMT ", %" PetscInt_FMT ")",m,m0);
488: PetscCheck(mloc==mloc0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_INCOMP,"Local dimensions of A and B do not match (%" PetscInt_FMT ", %" PetscInt_FMT ")",mloc,mloc0);
489: }
490: if (eps->state && (n!=eps->n || nloc!=eps->nloc)) PetscCall(EPSReset(eps));
491: eps->nrma = 0.0;
492: eps->nrmb = 0.0;
493: if (!eps->st) PetscCall(EPSGetST(eps,&eps->st));
494: mat[0] = A;
495: if (B) {
496: mat[1] = B;
497: nmat = 2;
498: } else nmat = 1;
499: PetscCall(STSetMatrices(eps->st,nmat,mat));
500: eps->state = EPS_STATE_INITIAL;
501: PetscFunctionReturn(PETSC_SUCCESS);
502: }
504: /*@
505: EPSGetOperators - Gets the matrices associated with the eigensystem.
507: Collective
509: Input Parameter:
510: . eps - the EPS context
512: Output Parameters:
513: + A - the matrix associated with the eigensystem
514: - B - the second matrix in the case of generalized eigenproblems
516: Note:
517: Does not increase the reference count of the matrices, so you should not destroy them.
519: Level: intermediate
521: .seealso: EPSSolve(), EPSGetST(), STGetMatrix(), STSetMatrices()
522: @*/
523: PetscErrorCode EPSGetOperators(EPS eps,Mat *A,Mat *B)
524: {
525: ST st;
526: PetscInt k;
528: PetscFunctionBegin;
530: PetscCall(EPSGetST(eps,&st));
531: PetscCall(STGetNumMatrices(st,&k));
532: if (A) {
533: if (k<1) *A = NULL;
534: else PetscCall(STGetMatrix(st,0,A));
535: }
536: if (B) {
537: if (k<2) *B = NULL;
538: else PetscCall(STGetMatrix(st,1,B));
539: }
540: PetscFunctionReturn(PETSC_SUCCESS);
541: }
543: /*@
544: EPSSetDeflationSpace - Specify a basis of vectors that constitute the deflation
545: space.
547: Collective
549: Input Parameters:
550: + eps - the eigenproblem solver context
551: . n - number of vectors
552: - v - set of basis vectors of the deflation space
554: Notes:
555: When a deflation space is given, the eigensolver seeks the eigensolution
556: in the restriction of the problem to the orthogonal complement of this
557: space. This can be used for instance in the case that an invariant
558: subspace is known beforehand (such as the nullspace of the matrix).
560: These vectors do not persist from one EPSSolve() call to the other, so the
561: deflation space should be set every time.
563: The vectors do not need to be mutually orthonormal, since they are explicitly
564: orthonormalized internally.
566: Level: intermediate
568: .seealso: EPSSetInitialSpace()
569: @*/
570: PetscErrorCode EPSSetDeflationSpace(EPS eps,PetscInt n,Vec v[])
571: {
572: PetscFunctionBegin;
575: PetscCheck(n>=0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"Argument n cannot be negative");
576: if (n>0) {
577: PetscAssertPointer(v,3);
579: }
580: PetscCall(SlepcBasisReference_Private(n,v,&eps->nds,&eps->defl));
581: if (n>0) eps->state = EPS_STATE_INITIAL;
582: PetscFunctionReturn(PETSC_SUCCESS);
583: }
585: /*@
586: EPSSetInitialSpace - Specify a basis of vectors that constitute the initial
587: space, that is, the subspace from which the solver starts to iterate.
589: Collective
591: Input Parameters:
592: + eps - the eigenproblem solver context
593: . n - number of vectors
594: - is - set of basis vectors of the initial space
596: Notes:
597: Some solvers start to iterate on a single vector (initial vector). In that case,
598: the other vectors are ignored.
600: These vectors do not persist from one EPSSolve() call to the other, so the
601: initial space should be set every time.
603: The vectors do not need to be mutually orthonormal, since they are explicitly
604: orthonormalized internally.
606: Common usage of this function is when the user can provide a rough approximation
607: of the wanted eigenspace. Then, convergence may be faster.
609: Level: intermediate
611: .seealso: EPSSetLeftInitialSpace(), EPSSetDeflationSpace()
612: @*/
613: PetscErrorCode EPSSetInitialSpace(EPS eps,PetscInt n,Vec is[])
614: {
615: PetscFunctionBegin;
618: PetscCheck(n>=0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"Argument n cannot be negative");
619: if (n>0) {
620: PetscAssertPointer(is,3);
622: }
623: PetscCall(SlepcBasisReference_Private(n,is,&eps->nini,&eps->IS));
624: if (n>0) eps->state = EPS_STATE_INITIAL;
625: PetscFunctionReturn(PETSC_SUCCESS);
626: }
628: /*@
629: EPSSetLeftInitialSpace - Specify a basis of vectors that constitute the left
630: initial space, used by two-sided solvers to start the left subspace.
632: Collective
634: Input Parameters:
635: + eps - the eigenproblem solver context
636: . n - number of vectors
637: - isl - set of basis vectors of the left initial space
639: Notes:
640: Left initial vectors are used to initiate the left search space in two-sided
641: eigensolvers. Users should pass here an approximation of the left eigenspace,
642: if available.
644: The same comments in EPSSetInitialSpace() are applicable here.
646: Level: intermediate
648: .seealso: EPSSetInitialSpace(), EPSSetTwoSided()
649: @*/
650: PetscErrorCode EPSSetLeftInitialSpace(EPS eps,PetscInt n,Vec isl[])
651: {
652: PetscFunctionBegin;
655: PetscCheck(n>=0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"Argument n cannot be negative");
656: if (n>0) {
657: PetscAssertPointer(isl,3);
659: }
660: PetscCall(SlepcBasisReference_Private(n,isl,&eps->ninil,&eps->ISL));
661: if (n>0) eps->state = EPS_STATE_INITIAL;
662: PetscFunctionReturn(PETSC_SUCCESS);
663: }
665: /*
666: EPSSetDimensions_Default - Set reasonable values for ncv, mpd if not set
667: by the user. This is called at setup.
668: */
669: PetscErrorCode EPSSetDimensions_Default(EPS eps,PetscInt *nev,PetscInt *ncv,PetscInt *mpd)
670: {
671: PetscBool krylov;
672: PetscInt n = eps->isstructured? eps->n/2: eps->n;
674: PetscFunctionBegin;
675: if (*nev==0 && eps->stop!=EPS_STOP_THRESHOLD) *nev = 1;
676: if (*ncv!=PETSC_DETERMINE) { /* ncv set */
677: PetscCall(PetscObjectTypeCompareAny((PetscObject)eps,&krylov,EPSKRYLOVSCHUR,EPSARNOLDI,EPSLANCZOS,""));
678: if (krylov) {
679: PetscCheck(*ncv>=*nev+1 || (*ncv==*nev && *ncv==n),PetscObjectComm((PetscObject)eps),PETSC_ERR_USER_INPUT,"The value of ncv must be at least nev+1");
680: } else {
681: PetscCheck(*ncv>=*nev,PetscObjectComm((PetscObject)eps),PETSC_ERR_USER_INPUT,"The value of ncv must be at least nev");
682: }
683: } else if (*mpd!=PETSC_DETERMINE) { /* mpd set */
684: *ncv = PetscMin(n,*nev+(*mpd));
685: } else { /* neither set: defaults depend on nev being small or large */
686: if (*nev<500) *ncv = PetscMin(n,PetscMax(2*(*nev),*nev+15));
687: else {
688: *mpd = 500;
689: *ncv = PetscMin(n,*nev+(*mpd));
690: }
691: }
692: if (*mpd==PETSC_DETERMINE) *mpd = *ncv;
693: PetscFunctionReturn(PETSC_SUCCESS);
694: }
696: /*@
697: EPSAllocateSolution - Allocate memory storage for common variables such
698: as eigenvalues and eigenvectors.
700: Collective
702: Input Parameters:
703: + eps - eigensolver context
704: - extra - number of additional positions, used for methods that require a
705: working basis slightly larger than ncv
707: Developer Notes:
708: This is SLEPC_EXTERN because it may be required by user plugin EPS
709: implementations.
711: Level: developer
713: .seealso: EPSSetUp()
714: @*/
715: PetscErrorCode EPSAllocateSolution(EPS eps,PetscInt extra)
716: {
717: PetscInt oldsize,requested;
718: PetscRandom rand;
719: Vec t;
721: PetscFunctionBegin;
722: requested = eps->ncv + extra;
724: /* oldsize is zero if this is the first time setup is called */
725: PetscCall(BVGetSizes(eps->V,NULL,NULL,&oldsize));
727: /* allocate space for eigenvalues and friends */
728: if (requested != oldsize || !eps->eigr) {
729: PetscCall(PetscFree4(eps->eigr,eps->eigi,eps->errest,eps->perm));
730: PetscCall(PetscMalloc4(requested,&eps->eigr,requested,&eps->eigi,requested,&eps->errest,requested,&eps->perm));
731: }
733: /* workspace for the case of arbitrary selection */
734: if (eps->arbitrary) {
735: if (eps->rr) PetscCall(PetscFree2(eps->rr,eps->ri));
736: PetscCall(PetscMalloc2(requested,&eps->rr,requested,&eps->ri));
737: }
739: /* allocate V */
740: if (!eps->V) PetscCall(EPSGetBV(eps,&eps->V));
741: if (!oldsize) {
742: if (!((PetscObject)eps->V)->type_name) PetscCall(BVSetType(eps->V,BVMAT));
743: PetscCall(STMatCreateVecsEmpty(eps->st,&t,NULL));
744: PetscCall(BVSetSizesFromVec(eps->V,t,requested));
745: PetscCall(VecDestroy(&t));
746: } else PetscCall(BVResize(eps->V,requested,PETSC_FALSE));
748: /* allocate W */
749: if (eps->twosided) {
750: PetscCall(BVGetRandomContext(eps->V,&rand)); /* make sure the random context is available when duplicating */
751: PetscCall(BVDestroy(&eps->W));
752: PetscCall(BVDuplicate(eps->V,&eps->W));
753: }
754: PetscFunctionReturn(PETSC_SUCCESS);
755: }
757: /*@
758: EPSReallocateSolution - Reallocate memory storage for common variables such
759: as the eigenvalues and the basis vectors.
761: Collective
763: Input Parameters:
764: + eps - eigensolver context
765: - newsize - new size
767: Developer Notes:
768: This is SLEPC_EXTERN because it may be required by user plugin EPS
769: implementations.
771: This is called during the iteration in case the threshold stopping test has
772: been selected.
774: Level: developer
776: .seealso: EPSAllocateSolution(), EPSSetThreshold()
777: @*/
778: PetscErrorCode EPSReallocateSolution(EPS eps,PetscInt newsize)
779: {
780: PetscInt oldsize,*nperm;
781: PetscReal *nerrest;
782: PetscScalar *neigr,*neigi;
784: PetscFunctionBegin;
785: PetscCall(BVGetSizes(eps->V,NULL,NULL,&oldsize));
786: if (oldsize>=newsize) PetscFunctionReturn(PETSC_SUCCESS);
787: PetscCall(PetscInfo(eps,"Reallocating basis vectors to %" PetscInt_FMT " columns\n",newsize));
789: /* reallocate eigenvalues */
790: PetscCall(PetscMalloc4(newsize,&neigr,newsize,&neigi,newsize,&nerrest,newsize,&nperm));
791: PetscCall(PetscArraycpy(neigr,eps->eigr,oldsize));
792: PetscCall(PetscArraycpy(neigi,eps->eigi,oldsize));
793: PetscCall(PetscArraycpy(nerrest,eps->errest,oldsize));
794: PetscCall(PetscArraycpy(nperm,eps->perm,oldsize));
795: PetscCall(PetscFree4(eps->eigr,eps->eigi,eps->errest,eps->perm));
796: eps->eigr = neigr;
797: eps->eigi = neigi;
798: eps->errest = nerrest;
799: eps->perm = nperm;
800: /* reallocate V,W */
801: PetscCall(BVResize(eps->V,newsize,PETSC_TRUE));
802: if (eps->twosided) PetscCall(BVResize(eps->W,newsize,PETSC_TRUE));
803: PetscFunctionReturn(PETSC_SUCCESS);
804: }