Actual source code: stsolve.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: ST interface routines, callable by users
12: */
14: #include <slepc/private/stimpl.h>
16: PetscErrorCode STApply_Generic(ST st,Vec x,Vec y)
17: {
18: PetscFunctionBegin;
19: if (st->M && st->P) {
20: PetscCall(MatMult(st->M,x,st->work[0]));
21: PetscCall(STMatSolve(st,st->work[0],y));
22: } else if (st->M) PetscCall(MatMult(st->M,x,y));
23: else PetscCall(STMatSolve(st,x,y));
24: PetscFunctionReturn(PETSC_SUCCESS);
25: }
27: /*@
28: STApply - Applies the spectral transformation operator to a vector, for
29: instance (A - sB)^-1 B in the case of the shift-and-invert transformation
30: and generalized eigenproblem.
32: Collective
34: Input Parameters:
35: + st - the spectral transformation context
36: - x - input vector
38: Output Parameter:
39: . y - output vector
41: Level: developer
43: .seealso: STApplyTranspose(), STApplyHermitianTranspose()
44: @*/
45: PetscErrorCode STApply(ST st,Vec x,Vec y)
46: {
47: Mat Op;
49: PetscFunctionBegin;
54: STCheckMatrices(st,1);
55: PetscCheck(x!=y,PetscObjectComm((PetscObject)st),PETSC_ERR_ARG_IDN,"x and y must be different vectors");
56: PetscCall(VecSetErrorIfLocked(y,3));
57: PetscCall(STGetOperator_Private(st,&Op));
58: PetscCall(MatMult(Op,x,y));
59: PetscFunctionReturn(PETSC_SUCCESS);
60: }
62: PetscErrorCode STApplyMat_Generic(ST st,Mat B,Mat C)
63: {
64: Mat work;
66: PetscFunctionBegin;
67: if (st->M && st->P) {
68: PetscCall(MatMatMult(st->M,B,MAT_INITIAL_MATRIX,PETSC_DEFAULT,&work));
69: PetscCall(STMatMatSolve(st,work,C));
70: PetscCall(MatDestroy(&work));
71: } else if (st->M) PetscCall(MatMatMult(st->M,B,MAT_REUSE_MATRIX,PETSC_DEFAULT,&C));
72: else PetscCall(STMatMatSolve(st,B,C));
73: PetscFunctionReturn(PETSC_SUCCESS);
74: }
76: /*@
77: STApplyMat - Applies the spectral transformation operator to a matrix, for
78: instance (A - sB)^-1 B in the case of the shift-and-invert transformation
79: and generalized eigenproblem.
81: Collective
83: Input Parameters:
84: + st - the spectral transformation context
85: - X - input matrix
87: Output Parameter:
88: . Y - output matrix
90: Level: developer
92: .seealso: STApply()
93: @*/
94: PetscErrorCode STApplyMat(ST st,Mat X,Mat Y)
95: {
96: PetscFunctionBegin;
101: STCheckMatrices(st,1);
102: PetscCheck(X!=Y,PetscObjectComm((PetscObject)st),PETSC_ERR_ARG_IDN,"X and Y must be different matrices");
103: PetscUseTypeMethod(st,applymat,X,Y);
104: PetscFunctionReturn(PETSC_SUCCESS);
105: }
107: PetscErrorCode STApplyTranspose_Generic(ST st,Vec x,Vec y)
108: {
109: PetscFunctionBegin;
110: if (st->M && st->P) {
111: PetscCall(STMatSolveTranspose(st,x,st->work[0]));
112: PetscCall(MatMultTranspose(st->M,st->work[0],y));
113: } else if (st->M) PetscCall(MatMultTranspose(st->M,x,y));
114: else PetscCall(STMatSolveTranspose(st,x,y));
115: PetscFunctionReturn(PETSC_SUCCESS);
116: }
118: /*@
119: STApplyTranspose - Applies the transpose of the operator to a vector, for
120: instance B^T(A - sB)^-T in the case of the shift-and-invert transformation
121: and generalized eigenproblem.
123: Collective
125: Input Parameters:
126: + st - the spectral transformation context
127: - x - input vector
129: Output Parameter:
130: . y - output vector
132: Level: developer
134: .seealso: STApply(), STApplyHermitianTranspose()
135: @*/
136: PetscErrorCode STApplyTranspose(ST st,Vec x,Vec y)
137: {
138: Mat Op;
140: PetscFunctionBegin;
145: STCheckMatrices(st,1);
146: PetscCheck(x!=y,PetscObjectComm((PetscObject)st),PETSC_ERR_ARG_IDN,"x and y must be different vectors");
147: PetscCall(VecSetErrorIfLocked(y,3));
148: PetscCall(STGetOperator_Private(st,&Op));
149: PetscCall(MatMultTranspose(Op,x,y));
150: PetscFunctionReturn(PETSC_SUCCESS);
151: }
153: PetscErrorCode STApplyHermitianTranspose_Generic(ST st,Vec x,Vec y)
154: {
155: PetscFunctionBegin;
156: if (st->M && st->P) {
157: PetscCall(STMatSolveHermitianTranspose(st,x,st->work[0]));
158: PetscCall(MatMultHermitianTranspose(st->M,st->work[0],y));
159: } else if (st->M) PetscCall(MatMultHermitianTranspose(st->M,x,y));
160: else PetscCall(STMatSolveHermitianTranspose(st,x,y));
161: PetscFunctionReturn(PETSC_SUCCESS);
162: }
164: /*@
165: STApplyHermitianTranspose - Applies the hermitian-transpose of the operator
166: to a vector, for instance B^H(A - sB)^-H in the case of the shift-and-invert
167: transformation and generalized eigenproblem.
169: Collective
171: Input Parameters:
172: + st - the spectral transformation context
173: - x - input vector
175: Output Parameter:
176: . y - output vector
178: Note:
179: Currently implemented via STApplyTranspose() with appropriate conjugation.
181: Level: developer
183: .seealso: STApply(), STApplyTranspose()
184: @*/
185: PetscErrorCode STApplyHermitianTranspose(ST st,Vec x,Vec y)
186: {
187: Mat Op;
189: PetscFunctionBegin;
194: STCheckMatrices(st,1);
195: PetscCheck(x!=y,PetscObjectComm((PetscObject)st),PETSC_ERR_ARG_IDN,"x and y must be different vectors");
196: PetscCall(VecSetErrorIfLocked(y,3));
197: PetscCall(STGetOperator_Private(st,&Op));
198: PetscCall(MatMultHermitianTranspose(Op,x,y));
199: PetscFunctionReturn(PETSC_SUCCESS);
200: }
202: /*@
203: STGetBilinearForm - Returns the matrix used in the bilinear form with a
204: generalized problem with semi-definite B.
206: Logically Collective
208: Input Parameters:
209: . st - the spectral transformation context
211: Output Parameter:
212: . B - output matrix
214: Notes:
215: The output matrix B must be destroyed after use. It will be NULL in
216: case of standard eigenproblems.
218: Level: developer
220: .seealso: BVSetMatrix()
221: @*/
222: PetscErrorCode STGetBilinearForm(ST st,Mat *B)
223: {
224: PetscFunctionBegin;
227: PetscAssertPointer(B,2);
228: STCheckMatrices(st,1);
229: PetscUseTypeMethod(st,getbilinearform,B);
230: PetscFunctionReturn(PETSC_SUCCESS);
231: }
233: PetscErrorCode STGetBilinearForm_Default(ST st,Mat *B)
234: {
235: PetscFunctionBegin;
236: if (st->nmat==1) *B = NULL;
237: else {
238: *B = st->A[1];
239: PetscCall(PetscObjectReference((PetscObject)*B));
240: }
241: PetscFunctionReturn(PETSC_SUCCESS);
242: }
244: static PetscErrorCode MatMult_STOperator(Mat Op,Vec x,Vec y)
245: {
246: ST st;
248: PetscFunctionBegin;
249: PetscCall(MatShellGetContext(Op,&st));
250: PetscCall(STSetUp(st));
251: PetscCall(PetscLogEventBegin(ST_Apply,st,x,y,0));
252: if (st->D) { /* with balancing */
253: PetscCall(VecPointwiseDivide(st->wb,x,st->D));
254: PetscUseTypeMethod(st,apply,st->wb,y);
255: PetscCall(VecPointwiseMult(y,y,st->D));
256: } else PetscUseTypeMethod(st,apply,x,y);
257: PetscCall(PetscLogEventEnd(ST_Apply,st,x,y,0));
258: PetscFunctionReturn(PETSC_SUCCESS);
259: }
261: static PetscErrorCode MatMultTranspose_STOperator(Mat Op,Vec x,Vec y)
262: {
263: ST st;
265: PetscFunctionBegin;
266: PetscCall(MatShellGetContext(Op,&st));
267: PetscCall(STSetUp(st));
268: PetscCall(PetscLogEventBegin(ST_ApplyTranspose,st,x,y,0));
269: if (st->D) { /* with balancing */
270: PetscCall(VecPointwiseMult(st->wb,x,st->D));
271: PetscUseTypeMethod(st,applytrans,st->wb,y);
272: PetscCall(VecPointwiseDivide(y,y,st->D));
273: } else PetscUseTypeMethod(st,applytrans,x,y);
274: PetscCall(PetscLogEventEnd(ST_ApplyTranspose,st,x,y,0));
275: PetscFunctionReturn(PETSC_SUCCESS);
276: }
278: #if defined(PETSC_USE_COMPLEX)
279: static PetscErrorCode MatMultHermitianTranspose_STOperator(Mat Op,Vec x,Vec y)
280: {
281: ST st;
283: PetscFunctionBegin;
284: PetscCall(MatShellGetContext(Op,&st));
285: PetscCall(STSetUp(st));
286: PetscCall(PetscLogEventBegin(ST_ApplyHermitianTranspose,st,x,y,0));
287: if (st->ops->applyhermtrans) {
288: if (st->D) { /* with balancing */
289: PetscCall(VecConjugate(st->D));
290: PetscCall(VecPointwiseMult(st->wb,x,st->D));
291: PetscUseTypeMethod(st,applyhermtrans,st->wb,y);
292: PetscCall(VecPointwiseDivide(y,y,st->D));
293: PetscCall(VecConjugate(st->D));
294: } else PetscUseTypeMethod(st,applyhermtrans,x,y);
295: } else {
296: if (!st->wht) PetscCall(MatCreateVecs(st->A[0],&st->wht,NULL));
297: PetscCall(VecCopy(x,st->wht));
298: PetscCall(VecConjugate(st->wht));
299: if (st->D) { /* with balancing */
300: PetscCall(VecPointwiseMult(st->wb,st->wht,st->D));
301: PetscUseTypeMethod(st,applytrans,st->wb,y);
302: PetscCall(VecPointwiseDivide(y,y,st->D));
303: } else PetscUseTypeMethod(st,applytrans,st->wht,y);
304: PetscCall(VecConjugate(y));
305: }
306: PetscCall(PetscLogEventEnd(ST_ApplyHermitianTranspose,st,x,y,0));
307: PetscFunctionReturn(PETSC_SUCCESS);
308: }
309: #endif
311: static PetscErrorCode MatMatMult_STOperator(Mat Op,Mat B,Mat C,void *ctx)
312: {
313: ST st;
315: PetscFunctionBegin;
316: PetscCall(MatShellGetContext(Op,&st));
317: PetscCall(STSetUp(st));
318: PetscCall(PetscLogEventBegin(ST_Apply,st,B,C,0));
319: PetscCall(STApplyMat_Generic(st,B,C));
320: PetscCall(PetscLogEventEnd(ST_Apply,st,B,C,0));
321: PetscFunctionReturn(PETSC_SUCCESS);
322: }
324: PetscErrorCode STGetOperator_Private(ST st,Mat *Op)
325: {
326: PetscInt m,n,M,N;
327: Vec v;
328: VecType vtype;
330: PetscFunctionBegin;
331: if (!st->Op) {
332: if (Op) *Op = NULL;
333: /* create the shell matrix */
334: PetscCall(MatGetLocalSize(st->A[0],&m,&n));
335: PetscCall(MatGetSize(st->A[0],&M,&N));
336: PetscCall(MatCreateShell(PetscObjectComm((PetscObject)st),m,n,M,N,st,&st->Op));
337: PetscCall(MatShellSetOperation(st->Op,MATOP_MULT,(void(*)(void))MatMult_STOperator));
338: PetscCall(MatShellSetOperation(st->Op,MATOP_MULT_TRANSPOSE,(void(*)(void))MatMultTranspose_STOperator));
339: #if defined(PETSC_USE_COMPLEX)
340: PetscCall(MatShellSetOperation(st->Op,MATOP_MULT_HERMITIAN_TRANSPOSE,(void(*)(void))MatMultHermitianTranspose_STOperator));
341: #else
342: PetscCall(MatShellSetOperation(st->Op,MATOP_MULT_HERMITIAN_TRANSPOSE,(void(*)(void))MatMultTranspose_STOperator));
343: #endif
344: if (!st->D && st->ops->apply==STApply_Generic) {
345: PetscCall(MatShellSetMatProductOperation(st->Op,MATPRODUCT_AB,NULL,MatMatMult_STOperator,NULL,MATDENSE,MATDENSE));
346: PetscCall(MatShellSetMatProductOperation(st->Op,MATPRODUCT_AB,NULL,MatMatMult_STOperator,NULL,MATDENSECUDA,MATDENSECUDA));
347: PetscCall(MatShellSetMatProductOperation(st->Op,MATPRODUCT_AB,NULL,MatMatMult_STOperator,NULL,MATDENSEHIP,MATDENSEHIP));
348: }
349: /* make sure the shell matrix generates a vector of the same type as the problem matrices */
350: PetscCall(MatCreateVecs(st->A[0],&v,NULL));
351: PetscCall(VecGetType(v,&vtype));
352: PetscCall(MatShellSetVecType(st->Op,vtype));
353: PetscCall(VecDestroy(&v));
354: /* build the operator matrices */
355: PetscCall(STComputeOperator(st));
356: }
357: if (Op) *Op = st->Op;
358: PetscFunctionReturn(PETSC_SUCCESS);
359: }
361: /*@
362: STGetOperator - Returns a shell matrix that represents the operator of the
363: spectral transformation.
365: Collective
367: Input Parameter:
368: . st - the spectral transformation context
370: Output Parameter:
371: . Op - operator matrix
373: Notes:
374: The operator is defined in linear eigenproblems only, not in polynomial ones,
375: so the call will fail if more than 2 matrices were passed in STSetMatrices().
377: The returned shell matrix is essentially a wrapper to the STApply() and
378: STApplyTranspose() operations. The operator can often be expressed as
380: $ Op = D*inv(K)*M*inv(D)
382: where D is the balancing matrix, and M and K are two matrices corresponding
383: to the numerator and denominator for spectral transformations that represent
384: a rational matrix function. In the case of STSHELL, the inner part inv(K)*M
385: is replaced by the user-provided operation from STShellSetApply().
387: The preconditioner matrix K typically depends on the value of the shift, and
388: its inverse is handled via an internal KSP object. Normal usage does not
389: require explicitly calling STGetOperator(), but it can be used to force the
390: creation of K and M, and then K is passed to the KSP. This is useful for
391: setting options associated with the PCFactor (to set MUMPS options, for instance).
393: The returned matrix must NOT be destroyed by the user. Instead, when no
394: longer needed it must be returned with STRestoreOperator(). In particular,
395: this is required before modifying the ST matrices or the shift.
397: A NULL pointer can be passed in Op in case the matrix is not required but we
398: want to force its creation. In this case, STRestoreOperator() should not be
399: called.
401: Level: advanced
403: .seealso: STApply(), STApplyTranspose(), STSetBalanceMatrix(), STShellSetApply(),
404: STGetKSP(), STSetShift(), STRestoreOperator(), STSetMatrices()
405: @*/
406: PetscErrorCode STGetOperator(ST st,Mat *Op)
407: {
408: PetscFunctionBegin;
411: STCheckMatrices(st,1);
412: STCheckNotSeized(st,1);
413: PetscCheck(st->nmat<=2,PetscObjectComm((PetscObject)st),PETSC_ERR_ARG_WRONGSTATE,"The operator is not defined in polynomial eigenproblems");
414: PetscCall(STGetOperator_Private(st,Op));
415: if (Op) st->opseized = PETSC_TRUE;
416: PetscFunctionReturn(PETSC_SUCCESS);
417: }
419: /*@
420: STRestoreOperator - Restore the previously seized operator matrix.
422: Logically Collective
424: Input Parameters:
425: + st - the spectral transformation context
426: - Op - operator matrix
428: Notes:
429: The arguments must match the corresponding call to STGetOperator().
431: Level: advanced
433: .seealso: STGetOperator()
434: @*/
435: PetscErrorCode STRestoreOperator(ST st,Mat *Op)
436: {
437: PetscFunctionBegin;
439: PetscAssertPointer(Op,2);
441: PetscCheck(st->opseized,PetscObjectComm((PetscObject)st),PETSC_ERR_ARG_WRONGSTATE,"Must be called after STGetOperator()");
442: *Op = NULL;
443: st->opseized = PETSC_FALSE;
444: PetscFunctionReturn(PETSC_SUCCESS);
445: }
447: /*
448: STComputeOperator - Computes the matrices that constitute the operator
450: Op = D*inv(K)*M*inv(D).
452: K and M are computed here (D is user-provided) from the system matrices
453: and the shift sigma (whenever these are changed, this function recomputes
454: K and M). This is used only in linear eigenproblems (nmat<3).
456: K is the "preconditioner matrix": it is the denominator in rational operators,
457: e.g. (A-sigma*B) in shift-and-invert. In non-rational transformations such
458: as STFILTER, K=NULL which means identity. After computing K, it is passed to
459: the internal KSP object via KSPSetOperators.
461: M is the numerator in rational operators. If unused it is set to NULL (e.g.
462: in STPRECOND).
464: STSHELL does not compute anything here, but sets the flag as if it was ready.
465: */
466: PetscErrorCode STComputeOperator(ST st)
467: {
468: PC pc;
470: PetscFunctionBegin;
473: if (!st->opready && st->ops->computeoperator) {
474: PetscCall(PetscInfo(st,"Building the operator matrices\n"));
475: STCheckMatrices(st,1);
476: if (!st->T) PetscCall(PetscCalloc1(PetscMax(2,st->nmat),&st->T));
477: PetscCall(PetscLogEventBegin(ST_ComputeOperator,st,0,0,0));
478: PetscUseTypeMethod(st,computeoperator);
479: PetscCall(PetscLogEventEnd(ST_ComputeOperator,st,0,0,0));
480: if (st->usesksp) {
481: if (!st->ksp) PetscCall(STGetKSP(st,&st->ksp));
482: if (st->P) {
483: PetscCall(STSetDefaultKSP(st));
484: PetscCall(ST_KSPSetOperators(st,st->P,st->Pmat?st->Pmat:st->P));
485: } else {
486: /* STPRECOND defaults to PCNONE if st->P is empty */
487: PetscCall(KSPGetPC(st->ksp,&pc));
488: PetscCall(PCSetType(pc,PCNONE));
489: }
490: }
491: }
492: st->opready = PETSC_TRUE;
493: PetscFunctionReturn(PETSC_SUCCESS);
494: }
496: /*@
497: STSetUp - Prepares for the use of a spectral transformation.
499: Collective
501: Input Parameter:
502: . st - the spectral transformation context
504: Level: advanced
506: .seealso: STCreate(), STApply(), STDestroy()
507: @*/
508: PetscErrorCode STSetUp(ST st)
509: {
510: PetscInt i,n,k;
512: PetscFunctionBegin;
515: STCheckMatrices(st,1);
516: switch (st->state) {
517: case ST_STATE_INITIAL:
518: PetscCall(PetscInfo(st,"Setting up new ST\n"));
519: if (!((PetscObject)st)->type_name) PetscCall(STSetType(st,STSHIFT));
520: break;
521: case ST_STATE_SETUP:
522: PetscFunctionReturn(PETSC_SUCCESS);
523: case ST_STATE_UPDATED:
524: PetscCall(PetscInfo(st,"Setting up updated ST\n"));
525: break;
526: }
527: PetscCall(PetscLogEventBegin(ST_SetUp,st,0,0,0));
528: if (st->state!=ST_STATE_UPDATED) {
529: if (!(st->nmat<3 && st->opready)) {
530: if (st->T) {
531: for (i=0;i<PetscMax(2,st->nmat);i++) PetscCall(MatDestroy(&st->T[i]));
532: }
533: PetscCall(MatDestroy(&st->P));
534: }
535: }
536: if (st->D) {
537: PetscCall(MatGetLocalSize(st->A[0],NULL,&n));
538: PetscCall(VecGetLocalSize(st->D,&k));
539: PetscCheck(n==k,PetscObjectComm((PetscObject)st),PETSC_ERR_ARG_SIZ,"Balance matrix has wrong dimension %" PetscInt_FMT " (should be %" PetscInt_FMT ")",k,n);
540: if (!st->wb) PetscCall(VecDuplicate(st->D,&st->wb));
541: }
542: if (st->nmat<3 && st->transform) PetscCall(STComputeOperator(st));
543: else {
544: if (!st->T) PetscCall(PetscCalloc1(PetscMax(2,st->nmat),&st->T));
545: }
546: PetscTryTypeMethod(st,setup);
547: st->state = ST_STATE_SETUP;
548: PetscCall(PetscLogEventEnd(ST_SetUp,st,0,0,0));
549: PetscFunctionReturn(PETSC_SUCCESS);
550: }
552: /*
553: Computes coefficients for the transformed polynomial,
554: and stores the result in argument S.
556: alpha - value of the parameter of the transformed polynomial
557: beta - value of the previous shift (only used in inplace mode)
558: k - index of first matrix included in the computation
559: coeffs - coefficients of the expansion
560: initial - true if this is the first time
561: precond - whether the preconditioner matrix must be computed
562: */
563: PetscErrorCode STMatMAXPY_Private(ST st,PetscScalar alpha,PetscScalar beta,PetscInt k,PetscScalar *coeffs,PetscBool initial,PetscBool precond,Mat *S)
564: {
565: PetscInt *matIdx=NULL,nmat,i,ini=-1;
566: PetscScalar t=1.0,ta,gamma;
567: PetscBool nz=PETSC_FALSE;
568: Mat *A=precond?st->Psplit:st->A;
569: MatStructure str=precond?st->strp:st->str;
571: PetscFunctionBegin;
572: nmat = st->nmat-k;
573: switch (st->matmode) {
574: case ST_MATMODE_INPLACE:
575: PetscCheck(st->nmat<=2,PetscObjectComm((PetscObject)st),PETSC_ERR_SUP,"ST_MATMODE_INPLACE not supported for polynomial eigenproblems");
576: PetscCheck(!precond,PetscObjectComm((PetscObject)st),PETSC_ERR_SUP,"ST_MATMODE_INPLACE not supported for split preconditioner");
577: if (initial) {
578: PetscCall(PetscObjectReference((PetscObject)A[0]));
579: *S = A[0];
580: gamma = alpha;
581: } else gamma = alpha-beta;
582: if (gamma != 0.0) {
583: if (st->nmat>1) PetscCall(MatAXPY(*S,gamma,A[1],str));
584: else PetscCall(MatShift(*S,gamma));
585: }
586: break;
587: case ST_MATMODE_SHELL:
588: PetscCheck(!precond,PetscObjectComm((PetscObject)st),PETSC_ERR_SUP,"ST_MATMODE_SHELL not supported for split preconditioner");
589: if (initial) {
590: if (st->nmat>2) {
591: PetscCall(PetscMalloc1(nmat,&matIdx));
592: for (i=0;i<nmat;i++) matIdx[i] = k+i;
593: }
594: PetscCall(STMatShellCreate(st,alpha,nmat,matIdx,coeffs,S));
595: if (st->nmat>2) PetscCall(PetscFree(matIdx));
596: } else PetscCall(STMatShellShift(*S,alpha));
597: break;
598: case ST_MATMODE_COPY:
599: if (coeffs) {
600: for (i=0;i<nmat && ini==-1;i++) {
601: if (coeffs[i]!=0.0) ini = i;
602: else t *= alpha;
603: }
604: if (coeffs[ini] != 1.0) nz = PETSC_TRUE;
605: for (i=ini+1;i<nmat&&!nz;i++) if (coeffs[i]!=0.0) nz = PETSC_TRUE;
606: } else { nz = PETSC_TRUE; ini = 0; }
607: if ((alpha == 0.0 || !nz) && t==1.0) {
608: PetscCall(PetscObjectReference((PetscObject)A[k+ini]));
609: PetscCall(MatDestroy(S));
610: *S = A[k+ini];
611: } else {
612: if (*S && *S!=A[k+ini]) {
613: PetscCall(MatSetOption(*S,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE));
614: PetscCall(MatCopy(A[k+ini],*S,DIFFERENT_NONZERO_PATTERN));
615: } else {
616: PetscCall(MatDestroy(S));
617: PetscCall(MatDuplicate(A[k+ini],MAT_COPY_VALUES,S));
618: PetscCall(MatSetOption(*S,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE));
619: }
620: if (coeffs && coeffs[ini]!=1.0) PetscCall(MatScale(*S,coeffs[ini]));
621: for (i=ini+k+1;i<PetscMax(2,st->nmat);i++) {
622: t *= alpha;
623: ta = t;
624: if (coeffs) ta *= coeffs[i-k];
625: if (ta!=0.0) {
626: if (st->nmat>1) PetscCall(MatAXPY(*S,ta,A[i],str));
627: else PetscCall(MatShift(*S,ta));
628: }
629: }
630: }
631: }
632: PetscCall(MatSetOption(*S,MAT_SYMMETRIC,st->asymm));
633: PetscCall(MatSetOption(*S,MAT_HERMITIAN,(PetscImaginaryPart(st->sigma)==0.0)?st->aherm:PETSC_FALSE));
634: PetscFunctionReturn(PETSC_SUCCESS);
635: }
637: /*
638: Computes the values of the coefficients required by STMatMAXPY_Private
639: for the case of monomial basis.
640: */
641: PetscErrorCode STCoeffs_Monomial(ST st, PetscScalar *coeffs)
642: {
643: PetscInt k,i,ini,inip;
645: PetscFunctionBegin;
646: /* Compute binomial coefficients */
647: ini = (st->nmat*(st->nmat-1))/2;
648: for (i=0;i<st->nmat;i++) coeffs[ini+i]=1.0;
649: for (k=st->nmat-1;k>=1;k--) {
650: inip = ini+1;
651: ini = (k*(k-1))/2;
652: coeffs[ini] = 1.0;
653: for (i=1;i<k;i++) coeffs[ini+i] = coeffs[ini+i-1]+coeffs[inip+i-1];
654: }
655: PetscFunctionReturn(PETSC_SUCCESS);
656: }
658: /*@
659: STPostSolve - Optional post-solve phase, intended for any actions that must
660: be performed on the ST object after the eigensolver has finished.
662: Collective
664: Input Parameters:
665: . st - the spectral transformation context
667: Level: developer
669: .seealso: EPSSolve()
670: @*/
671: PetscErrorCode STPostSolve(ST st)
672: {
673: PetscFunctionBegin;
676: PetscTryTypeMethod(st,postsolve);
677: PetscFunctionReturn(PETSC_SUCCESS);
678: }
680: /*@
681: STBackTransform - Back-transformation phase, intended for
682: spectral transformations which require to transform the computed
683: eigenvalues back to the original eigenvalue problem.
685: Not Collective
687: Input Parameters:
688: + st - the spectral transformation context
689: . n - number of eigenvalues
690: . eigr - real part of a computed eigenvalues
691: - eigi - imaginary part of a computed eigenvalues
693: Level: developer
695: .seealso: STIsInjective()
696: @*/
697: PetscErrorCode STBackTransform(ST st,PetscInt n,PetscScalar* eigr,PetscScalar* eigi)
698: {
699: PetscFunctionBegin;
702: PetscTryTypeMethod(st,backtransform,n,eigr,eigi);
703: PetscFunctionReturn(PETSC_SUCCESS);
704: }
706: /*@
707: STIsInjective - Ask if this spectral transformation is injective or not
708: (that is, if it corresponds to a one-to-one mapping). If not, then it
709: does not make sense to call STBackTransform().
711: Not Collective
713: Input Parameter:
714: . st - the spectral transformation context
716: Output Parameter:
717: . is - the answer
719: Level: developer
721: .seealso: STBackTransform()
722: @*/
723: PetscErrorCode STIsInjective(ST st,PetscBool* is)
724: {
725: PetscBool shell;
727: PetscFunctionBegin;
730: PetscAssertPointer(is,2);
732: PetscCall(PetscObjectTypeCompare((PetscObject)st,STSHELL,&shell));
733: if (shell) PetscCall(STIsInjective_Shell(st,is));
734: else *is = st->ops->backtransform? PETSC_TRUE: PETSC_FALSE;
735: PetscFunctionReturn(PETSC_SUCCESS);
736: }
738: /*@
739: STMatSetUp - Build the preconditioner matrix used in STMatSolve().
741: Collective
743: Input Parameters:
744: + st - the spectral transformation context
745: . sigma - the shift
746: - coeffs - the coefficients (may be NULL)
748: Note:
749: This function is not intended to be called by end users, but by SLEPc
750: solvers that use ST. It builds matrix st->P as follows, then calls KSPSetUp().
751: .vb
752: If (coeffs) st->P = Sum_{i=0..nmat-1} coeffs[i]*sigma^i*A_i
753: else st->P = Sum_{i=0..nmat-1} sigma^i*A_i
754: .ve
756: Level: developer
758: .seealso: STMatSolve()
759: @*/
760: PetscErrorCode STMatSetUp(ST st,PetscScalar sigma,PetscScalar *coeffs)
761: {
762: PetscFunctionBegin;
765: STCheckMatrices(st,1);
767: PetscCall(PetscLogEventBegin(ST_MatSetUp,st,0,0,0));
768: PetscCall(STMatMAXPY_Private(st,sigma,0.0,0,coeffs,PETSC_TRUE,PETSC_FALSE,&st->P));
769: if (st->Psplit) PetscCall(STMatMAXPY_Private(st,sigma,0.0,0,coeffs,PETSC_TRUE,PETSC_TRUE,&st->Pmat));
770: PetscCall(ST_KSPSetOperators(st,st->P,st->Pmat?st->Pmat:st->P));
771: PetscCall(KSPSetUp(st->ksp));
772: PetscCall(PetscLogEventEnd(ST_MatSetUp,st,0,0,0));
773: PetscFunctionReturn(PETSC_SUCCESS);
774: }
776: /*@
777: STSetWorkVecs - Sets a number of work vectors into the ST object.
779: Collective
781: Input Parameters:
782: + st - the spectral transformation context
783: - nw - number of work vectors to allocate
785: Developer Notes:
786: This is SLEPC_EXTERN because it may be required by shell STs.
788: Level: developer
790: .seealso: STMatCreateVecs()
791: @*/
792: PetscErrorCode STSetWorkVecs(ST st,PetscInt nw)
793: {
794: PetscInt i;
796: PetscFunctionBegin;
799: PetscCheck(nw>0,PetscObjectComm((PetscObject)st),PETSC_ERR_ARG_OUTOFRANGE,"nw must be > 0: nw = %" PetscInt_FMT,nw);
800: if (st->nwork < nw) {
801: PetscCall(VecDestroyVecs(st->nwork,&st->work));
802: st->nwork = nw;
803: PetscCall(PetscMalloc1(nw,&st->work));
804: for (i=0;i<nw;i++) PetscCall(STMatCreateVecs(st,&st->work[i],NULL));
805: }
806: PetscFunctionReturn(PETSC_SUCCESS);
807: }