Actual source code: dspep.c
slepc-3.21.1 2024-04-26
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: */
11: #include <slepc/private/dsimpl.h>
12: #include <slepcblaslapack.h>
14: typedef struct {
15: PetscInt d; /* polynomial degree */
16: PetscReal *pbc; /* polynomial basis coefficients */
17: } DS_PEP;
19: static PetscErrorCode DSAllocate_PEP(DS ds,PetscInt ld)
20: {
21: DS_PEP *ctx = (DS_PEP*)ds->data;
22: PetscInt i;
24: PetscFunctionBegin;
25: PetscCheck(ctx->d,PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_WRONGSTATE,"DSPEP requires specifying the polynomial degree via DSPEPSetDegree()");
26: PetscCall(DSAllocateMat_Private(ds,DS_MAT_X));
27: PetscCall(DSAllocateMat_Private(ds,DS_MAT_Y));
28: for (i=0;i<=ctx->d;i++) PetscCall(DSAllocateMat_Private(ds,DSMatExtra[i]));
29: PetscCall(PetscFree(ds->perm));
30: PetscCall(PetscMalloc1(ld*ctx->d,&ds->perm));
31: PetscFunctionReturn(PETSC_SUCCESS);
32: }
34: static PetscErrorCode DSView_PEP(DS ds,PetscViewer viewer)
35: {
36: DS_PEP *ctx = (DS_PEP*)ds->data;
37: PetscViewerFormat format;
38: PetscInt i;
40: PetscFunctionBegin;
41: PetscCall(PetscViewerGetFormat(viewer,&format));
42: if (format == PETSC_VIEWER_ASCII_INFO) PetscFunctionReturn(PETSC_SUCCESS);
43: if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
44: PetscCall(PetscViewerASCIIPrintf(viewer,"polynomial degree: %" PetscInt_FMT "\n",ctx->d));
45: PetscFunctionReturn(PETSC_SUCCESS);
46: }
47: for (i=0;i<=ctx->d;i++) PetscCall(DSViewMat(ds,viewer,DSMatExtra[i]));
48: if (ds->state>DS_STATE_INTERMEDIATE) PetscCall(DSViewMat(ds,viewer,DS_MAT_X));
49: PetscFunctionReturn(PETSC_SUCCESS);
50: }
52: static PetscErrorCode DSVectors_PEP(DS ds,DSMatType mat,PetscInt *j,PetscReal *rnorm)
53: {
54: PetscFunctionBegin;
55: PetscCheck(!rnorm,PetscObjectComm((PetscObject)ds),PETSC_ERR_SUP,"Not implemented yet");
56: switch (mat) {
57: case DS_MAT_X:
58: break;
59: case DS_MAT_Y:
60: break;
61: default:
62: SETERRQ(PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_OUTOFRANGE,"Invalid mat parameter");
63: }
64: PetscFunctionReturn(PETSC_SUCCESS);
65: }
67: static PetscErrorCode DSSort_PEP(DS ds,PetscScalar *wr,PetscScalar *wi,PetscScalar *rr,PetscScalar *ri,PetscInt *kout)
68: {
69: DS_PEP *ctx = (DS_PEP*)ds->data;
70: PetscInt n,i,*perm,told;
71: PetscScalar *A;
73: PetscFunctionBegin;
74: if (!ds->sc) PetscFunctionReturn(PETSC_SUCCESS);
75: n = ds->n*ctx->d;
76: perm = ds->perm;
77: for (i=0;i<n;i++) perm[i] = i;
78: told = ds->t;
79: ds->t = n; /* force the sorting routines to consider d*n eigenvalues */
80: if (rr) PetscCall(DSSortEigenvalues_Private(ds,rr,ri,perm,PETSC_FALSE));
81: else PetscCall(DSSortEigenvalues_Private(ds,wr,wi,perm,PETSC_FALSE));
82: ds->t = told; /* restore value of t */
83: PetscCall(MatDenseGetArray(ds->omat[DS_MAT_A],&A));
84: for (i=0;i<n;i++) A[i] = wr[perm[i]];
85: for (i=0;i<n;i++) wr[i] = A[i];
86: for (i=0;i<n;i++) A[i] = wi[perm[i]];
87: for (i=0;i<n;i++) wi[i] = A[i];
88: PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_A],&A));
89: PetscCall(DSPermuteColumnsTwo_Private(ds,0,n,ds->n,DS_MAT_X,DS_MAT_Y,perm));
90: PetscFunctionReturn(PETSC_SUCCESS);
91: }
93: static PetscErrorCode DSSolve_PEP_QZ(DS ds,PetscScalar *wr,PetscScalar *wi)
94: {
95: DS_PEP *ctx = (DS_PEP*)ds->data;
96: PetscInt i,j,k,off;
97: PetscScalar *A,*B,*W,*X,*U,*Y,*work,*beta,a;
98: const PetscScalar *Ed,*Ei;
99: PetscReal *ca,*cb,*cg,norm,done=1.0;
100: PetscBLASInt info,n,ld,ldd,nd,lwork,one=1,zero=0,cols;
101: PetscBool useggev3=(ds->method==1)?PETSC_TRUE:PETSC_FALSE;
103: PetscFunctionBegin;
104: PetscCall(PetscBLASIntCast(ds->n*ctx->d,&nd));
105: PetscCall(PetscBLASIntCast(ds->n,&n));
106: PetscCall(PetscBLASIntCast(ds->ld,&ld));
107: PetscCall(PetscBLASIntCast(ds->ld*ctx->d,&ldd));
108: PetscCall(DSAllocateMat_Private(ds,DS_MAT_A));
109: PetscCall(DSAllocateMat_Private(ds,DS_MAT_B));
110: PetscCall(DSAllocateMat_Private(ds,DS_MAT_W));
111: PetscCall(DSAllocateMat_Private(ds,DS_MAT_U));
112: PetscCall(MatDenseGetArray(ds->omat[DS_MAT_A],&A));
113: PetscCall(MatDenseGetArray(ds->omat[DS_MAT_B],&B));
115: /* build matrices A and B of the linearization */
116: PetscCall(MatDenseGetArrayRead(ds->omat[DSMatExtra[ctx->d]],&Ed));
117: PetscCall(PetscArrayzero(A,ldd*ldd));
118: if (!ctx->pbc) { /* monomial basis */
119: for (i=0;i<nd-ds->n;i++) A[i+(i+ds->n)*ldd] = 1.0;
120: for (i=0;i<ctx->d;i++) {
121: PetscCall(MatDenseGetArrayRead(ds->omat[DSMatExtra[i]],&Ei));
122: off = i*ds->n*ldd+(ctx->d-1)*ds->n;
123: for (j=0;j<ds->n;j++) PetscCall(PetscArraycpy(A+off+j*ldd,Ei+j*ds->ld,ds->n));
124: PetscCall(MatDenseRestoreArrayRead(ds->omat[DSMatExtra[i]],&Ei));
125: }
126: } else {
127: ca = ctx->pbc;
128: cb = ca+ctx->d+1;
129: cg = cb+ctx->d+1;
130: for (i=0;i<ds->n;i++) {
131: A[i+(i+ds->n)*ldd] = ca[0];
132: A[i+i*ldd] = cb[0];
133: }
134: for (;i<nd-ds->n;i++) {
135: j = i/ds->n;
136: A[i+(i+ds->n)*ldd] = ca[j];
137: A[i+i*ldd] = cb[j];
138: A[i+(i-ds->n)*ldd] = cg[j];
139: }
140: for (i=0;i<ctx->d-2;i++) {
141: PetscCall(MatDenseGetArrayRead(ds->omat[DSMatExtra[i]],&Ei));
142: off = i*ds->n*ldd+(ctx->d-1)*ds->n;
143: for (j=0;j<ds->n;j++)
144: for (k=0;k<ds->n;k++)
145: A[off+j*ldd+k] = Ei[j*ds->ld+k]*ca[ctx->d-1];
146: PetscCall(MatDenseRestoreArrayRead(ds->omat[DSMatExtra[i]],&Ei));
147: }
148: PetscCall(MatDenseGetArrayRead(ds->omat[DSMatExtra[i]],&Ei));
149: off = i*ds->n*ldd+(ctx->d-1)*ds->n;
150: for (j=0;j<ds->n;j++)
151: for (k=0;k<ds->n;k++)
152: A[off+j*ldd+k] = Ei[j*ds->ld+k]*ca[ctx->d-1]-Ed[j*ds->ld+k]*cg[ctx->d-1];
153: PetscCall(MatDenseRestoreArrayRead(ds->omat[DSMatExtra[i]],&Ei));
154: i++;
155: PetscCall(MatDenseGetArrayRead(ds->omat[DSMatExtra[i]],&Ei));
156: off = i*ds->n*ldd+(ctx->d-1)*ds->n;
157: for (j=0;j<ds->n;j++)
158: for (k=0;k<ds->n;k++)
159: A[off+j*ldd+k] = Ei[j*ds->ld+k]*ca[ctx->d-1]-Ed[j*ds->ld+k]*cb[ctx->d-1];
160: PetscCall(MatDenseRestoreArrayRead(ds->omat[DSMatExtra[i]],&Ei));
161: }
162: PetscCall(PetscArrayzero(B,ldd*ldd));
163: for (i=0;i<nd-ds->n;i++) B[i+i*ldd] = 1.0;
164: off = (ctx->d-1)*ds->n*(ldd+1);
165: for (j=0;j<ds->n;j++) {
166: for (i=0;i<ds->n;i++) B[off+i+j*ldd] = -Ed[i+j*ds->ld];
167: }
168: PetscCall(MatDenseRestoreArrayRead(ds->omat[DSMatExtra[ctx->d]],&Ed));
170: /* solve generalized eigenproblem */
171: PetscCall(MatDenseGetArray(ds->omat[DS_MAT_W],&W));
172: PetscCall(MatDenseGetArray(ds->omat[DS_MAT_U],&U));
173: lwork = -1;
174: #if defined(PETSC_USE_COMPLEX)
175: if (useggev3) PetscCallBLAS("LAPACKggev3",LAPACKggev3_("V","V",&nd,A,&ldd,B,&ldd,wr,NULL,U,&ldd,W,&ldd,&a,&lwork,NULL,&info));
176: else PetscCallBLAS("LAPACKggev",LAPACKggev_("V","V",&nd,A,&ldd,B,&ldd,wr,NULL,U,&ldd,W,&ldd,&a,&lwork,NULL,&info));
177: PetscCall(PetscBLASIntCast((PetscInt)PetscRealPart(a),&lwork));
178: PetscCall(DSAllocateWork_Private(ds,lwork+nd,8*nd,0));
179: beta = ds->work;
180: work = ds->work + nd;
181: if (useggev3) PetscCallBLAS("LAPACKggev3",LAPACKggev3_("V","V",&nd,A,&ldd,B,&ldd,wr,beta,U,&ldd,W,&ldd,work,&lwork,ds->rwork,&info));
182: else PetscCallBLAS("LAPACKggev",LAPACKggev_("V","V",&nd,A,&ldd,B,&ldd,wr,beta,U,&ldd,W,&ldd,work,&lwork,ds->rwork,&info));
183: #else
184: if (useggev3) PetscCallBLAS("LAPACKggev3",LAPACKggev3_("V","V",&nd,A,&ldd,B,&ldd,wr,wi,NULL,U,&ldd,W,&ldd,&a,&lwork,&info));
185: else PetscCallBLAS("LAPACKggev",LAPACKggev_("V","V",&nd,A,&ldd,B,&ldd,wr,wi,NULL,U,&ldd,W,&ldd,&a,&lwork,&info));
186: PetscCall(PetscBLASIntCast((PetscInt)a,&lwork));
187: PetscCall(DSAllocateWork_Private(ds,lwork+nd,0,0));
188: beta = ds->work;
189: work = ds->work + nd;
190: if (useggev3) PetscCallBLAS("LAPACKggev3",LAPACKggev3_("V","V",&nd,A,&ldd,B,&ldd,wr,wi,beta,U,&ldd,W,&ldd,work,&lwork,&info));
191: else PetscCallBLAS("LAPACKggev",LAPACKggev_("V","V",&nd,A,&ldd,B,&ldd,wr,wi,beta,U,&ldd,W,&ldd,work,&lwork,&info));
192: #endif
193: SlepcCheckLapackInfo(useggev3?"ggev3":"ggev",info);
194: PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_A],&A));
195: PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_B],&B));
197: /* copy eigenvalues */
198: for (i=0;i<nd;i++) {
199: if (beta[i]==0.0) wr[i] = (PetscRealPart(wr[i])>0.0)? PETSC_MAX_REAL: PETSC_MIN_REAL;
200: else wr[i] /= beta[i];
201: #if !defined(PETSC_USE_COMPLEX)
202: if (beta[i]==0.0) wi[i] = 0.0;
203: else wi[i] /= beta[i];
204: #else
205: if (wi) wi[i] = 0.0;
206: #endif
207: }
209: /* copy and normalize eigenvectors */
210: PetscCall(MatDenseGetArray(ds->omat[DS_MAT_X],&X));
211: PetscCall(MatDenseGetArray(ds->omat[DS_MAT_Y],&Y));
212: for (j=0;j<nd;j++) {
213: PetscCall(PetscArraycpy(X+j*ds->ld,W+j*ldd,ds->n));
214: PetscCall(PetscArraycpy(Y+j*ds->ld,U+ds->n*(ctx->d-1)+j*ldd,ds->n));
215: }
216: PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_W],&W));
217: PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_U],&U));
218: for (j=0;j<nd;j++) {
219: cols = 1;
220: norm = BLASnrm2_(&n,X+j*ds->ld,&one);
221: #if !defined(PETSC_USE_COMPLEX)
222: if (wi[j] != 0.0) {
223: norm = SlepcAbsEigenvalue(norm,BLASnrm2_(&n,X+(j+1)*ds->ld,&one));
224: cols = 2;
225: }
226: #endif
227: PetscCallBLAS("LAPACKlascl",LAPACKlascl_("G",&zero,&zero,&norm,&done,&n,&cols,X+j*ds->ld,&ld,&info));
228: SlepcCheckLapackInfo("lascl",info);
229: norm = BLASnrm2_(&n,Y+j*ds->ld,&one);
230: #if !defined(PETSC_USE_COMPLEX)
231: if (wi[j] != 0.0) norm = SlepcAbsEigenvalue(norm,BLASnrm2_(&n,Y+(j+1)*ds->ld,&one));
232: #endif
233: PetscCallBLAS("LAPACKlascl",LAPACKlascl_("G",&zero,&zero,&norm,&done,&n,&cols,Y+j*ds->ld,&ld,&info));
234: SlepcCheckLapackInfo("lascl",info);
235: #if !defined(PETSC_USE_COMPLEX)
236: if (wi[j] != 0.0) j++;
237: #endif
238: }
239: PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_X],&X));
240: PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_Y],&Y));
241: PetscFunctionReturn(PETSC_SUCCESS);
242: }
244: #if !defined(PETSC_HAVE_MPIUNI)
245: static PetscErrorCode DSSynchronize_PEP(DS ds,PetscScalar eigr[],PetscScalar eigi[])
246: {
247: DS_PEP *ctx = (DS_PEP*)ds->data;
248: PetscInt ld=ds->ld,k=0;
249: PetscMPIInt ldnd,rank,off=0,size,dn;
250: PetscScalar *X,*Y;
252: PetscFunctionBegin;
253: if (ds->state>=DS_STATE_CONDENSED) k += 2*ctx->d*ds->n*ld;
254: if (eigr) k += ctx->d*ds->n;
255: if (eigi) k += ctx->d*ds->n;
256: PetscCall(DSAllocateWork_Private(ds,k,0,0));
257: PetscCall(PetscMPIIntCast(k*sizeof(PetscScalar),&size));
258: PetscCall(PetscMPIIntCast(ds->n*ctx->d*ld,&ldnd));
259: PetscCall(PetscMPIIntCast(ctx->d*ds->n,&dn));
260: if (ds->state>=DS_STATE_CONDENSED) {
261: PetscCall(MatDenseGetArray(ds->omat[DS_MAT_X],&X));
262: PetscCall(MatDenseGetArray(ds->omat[DS_MAT_Y],&Y));
263: }
264: PetscCallMPI(MPI_Comm_rank(PetscObjectComm((PetscObject)ds),&rank));
265: if (!rank) {
266: if (ds->state>=DS_STATE_CONDENSED) {
267: PetscCallMPI(MPI_Pack(X,ldnd,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds)));
268: PetscCallMPI(MPI_Pack(Y,ldnd,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds)));
269: }
270: if (eigr) PetscCallMPI(MPI_Pack(eigr,dn,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds)));
271: #if !defined(PETSC_USE_COMPLEX)
272: if (eigi) PetscCallMPI(MPI_Pack(eigi,dn,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds)));
273: #endif
274: }
275: PetscCallMPI(MPI_Bcast(ds->work,size,MPI_BYTE,0,PetscObjectComm((PetscObject)ds)));
276: if (rank) {
277: if (ds->state>=DS_STATE_CONDENSED) {
278: PetscCallMPI(MPI_Unpack(ds->work,size,&off,X,ldnd,MPIU_SCALAR,PetscObjectComm((PetscObject)ds)));
279: PetscCallMPI(MPI_Unpack(ds->work,size,&off,Y,ldnd,MPIU_SCALAR,PetscObjectComm((PetscObject)ds)));
280: }
281: if (eigr) PetscCallMPI(MPI_Unpack(ds->work,size,&off,eigr,dn,MPIU_SCALAR,PetscObjectComm((PetscObject)ds)));
282: #if !defined(PETSC_USE_COMPLEX)
283: if (eigi) PetscCallMPI(MPI_Unpack(ds->work,size,&off,eigi,dn,MPIU_SCALAR,PetscObjectComm((PetscObject)ds)));
284: #endif
285: }
286: if (ds->state>=DS_STATE_CONDENSED) {
287: PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_X],&X));
288: PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_Y],&Y));
289: }
290: PetscFunctionReturn(PETSC_SUCCESS);
291: }
292: #endif
294: static PetscErrorCode DSPEPSetDegree_PEP(DS ds,PetscInt d)
295: {
296: DS_PEP *ctx = (DS_PEP*)ds->data;
298: PetscFunctionBegin;
299: PetscCheck(d>=0,PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_OUTOFRANGE,"The degree must be a non-negative integer");
300: PetscCheck(d<DS_NUM_EXTRA,PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_OUTOFRANGE,"Only implemented for polynomials of degree at most %d",DS_NUM_EXTRA-1);
301: ctx->d = d;
302: PetscFunctionReturn(PETSC_SUCCESS);
303: }
305: /*@
306: DSPEPSetDegree - Sets the polynomial degree for a DSPEP.
308: Logically Collective
310: Input Parameters:
311: + ds - the direct solver context
312: - d - the degree
314: Level: intermediate
316: .seealso: DSPEPGetDegree()
317: @*/
318: PetscErrorCode DSPEPSetDegree(DS ds,PetscInt d)
319: {
320: PetscFunctionBegin;
323: PetscTryMethod(ds,"DSPEPSetDegree_C",(DS,PetscInt),(ds,d));
324: PetscFunctionReturn(PETSC_SUCCESS);
325: }
327: static PetscErrorCode DSPEPGetDegree_PEP(DS ds,PetscInt *d)
328: {
329: DS_PEP *ctx = (DS_PEP*)ds->data;
331: PetscFunctionBegin;
332: *d = ctx->d;
333: PetscFunctionReturn(PETSC_SUCCESS);
334: }
336: /*@
337: DSPEPGetDegree - Returns the polynomial degree for a DSPEP.
339: Not Collective
341: Input Parameter:
342: . ds - the direct solver context
344: Output Parameters:
345: . d - the degree
347: Level: intermediate
349: .seealso: DSPEPSetDegree()
350: @*/
351: PetscErrorCode DSPEPGetDegree(DS ds,PetscInt *d)
352: {
353: PetscFunctionBegin;
355: PetscAssertPointer(d,2);
356: PetscUseMethod(ds,"DSPEPGetDegree_C",(DS,PetscInt*),(ds,d));
357: PetscFunctionReturn(PETSC_SUCCESS);
358: }
360: static PetscErrorCode DSPEPSetCoefficients_PEP(DS ds,PetscReal *pbc)
361: {
362: DS_PEP *ctx = (DS_PEP*)ds->data;
363: PetscInt i;
365: PetscFunctionBegin;
366: PetscCheck(ctx->d,PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_WRONGSTATE,"Must first specify the polynomial degree via DSPEPSetDegree()");
367: if (ctx->pbc) PetscCall(PetscFree(ctx->pbc));
368: PetscCall(PetscMalloc1(3*(ctx->d+1),&ctx->pbc));
369: for (i=0;i<3*(ctx->d+1);i++) ctx->pbc[i] = pbc[i];
370: ds->state = DS_STATE_RAW;
371: PetscFunctionReturn(PETSC_SUCCESS);
372: }
374: /*@C
375: DSPEPSetCoefficients - Sets the polynomial basis coefficients for a DSPEP.
377: Logically Collective
379: Input Parameters:
380: + ds - the direct solver context
381: - pbc - the polynomial basis coefficients
383: Notes:
384: This function is required only in the case of a polynomial specified in a
385: non-monomial basis, to provide the coefficients that will be used
386: during the linearization, multiplying the identity blocks on the three main
387: diagonal blocks. Depending on the polynomial basis (Chebyshev, Legendre, ...)
388: the coefficients must be different.
390: There must be a total of 3*(d+1) coefficients, where d is the degree of the
391: polynomial. The coefficients are arranged in three groups, alpha, beta, and
392: gamma, according to the definition of the three-term recurrence. In the case
393: of the monomial basis, alpha=1 and beta=gamma=0, in which case it is not
394: necessary to invoke this function.
396: Level: advanced
398: .seealso: DSPEPGetCoefficients(), DSPEPSetDegree()
399: @*/
400: PetscErrorCode DSPEPSetCoefficients(DS ds,PetscReal *pbc)
401: {
402: PetscFunctionBegin;
404: PetscTryMethod(ds,"DSPEPSetCoefficients_C",(DS,PetscReal*),(ds,pbc));
405: PetscFunctionReturn(PETSC_SUCCESS);
406: }
408: static PetscErrorCode DSPEPGetCoefficients_PEP(DS ds,PetscReal **pbc)
409: {
410: DS_PEP *ctx = (DS_PEP*)ds->data;
411: PetscInt i;
413: PetscFunctionBegin;
414: PetscCheck(ctx->d,PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_WRONGSTATE,"Must first specify the polynomial degree via DSPEPSetDegree()");
415: PetscCall(PetscCalloc1(3*(ctx->d+1),pbc));
416: if (ctx->pbc) for (i=0;i<3*(ctx->d+1);i++) (*pbc)[i] = ctx->pbc[i];
417: else for (i=0;i<ctx->d+1;i++) (*pbc)[i] = 1.0;
418: PetscFunctionReturn(PETSC_SUCCESS);
419: }
421: /*@C
422: DSPEPGetCoefficients - Returns the polynomial basis coefficients for a DSPEP.
424: Not Collective
426: Input Parameter:
427: . ds - the direct solver context
429: Output Parameters:
430: . pbc - the polynomial basis coefficients
432: Note:
433: The returned array has length 3*(d+1) and should be freed by the user.
435: Fortran Notes:
436: The calling sequence from Fortran is
437: .vb
438: DSPEPGetCoefficients(eps,pbc,ierr)
439: double precision pbc(d+1) output
440: .ve
442: Level: advanced
444: .seealso: DSPEPSetCoefficients()
445: @*/
446: PetscErrorCode DSPEPGetCoefficients(DS ds,PetscReal **pbc)
447: {
448: PetscFunctionBegin;
450: PetscAssertPointer(pbc,2);
451: PetscUseMethod(ds,"DSPEPGetCoefficients_C",(DS,PetscReal**),(ds,pbc));
452: PetscFunctionReturn(PETSC_SUCCESS);
453: }
455: static PetscErrorCode DSDestroy_PEP(DS ds)
456: {
457: DS_PEP *ctx = (DS_PEP*)ds->data;
459: PetscFunctionBegin;
460: if (ctx->pbc) PetscCall(PetscFree(ctx->pbc));
461: PetscCall(PetscFree(ds->data));
462: PetscCall(PetscObjectComposeFunction((PetscObject)ds,"DSPEPSetDegree_C",NULL));
463: PetscCall(PetscObjectComposeFunction((PetscObject)ds,"DSPEPGetDegree_C",NULL));
464: PetscCall(PetscObjectComposeFunction((PetscObject)ds,"DSPEPSetCoefficients_C",NULL));
465: PetscCall(PetscObjectComposeFunction((PetscObject)ds,"DSPEPGetCoefficients_C",NULL));
466: PetscFunctionReturn(PETSC_SUCCESS);
467: }
469: static PetscErrorCode DSMatGetSize_PEP(DS ds,DSMatType t,PetscInt *rows,PetscInt *cols)
470: {
471: DS_PEP *ctx = (DS_PEP*)ds->data;
473: PetscFunctionBegin;
474: PetscCheck(ctx->d,PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_WRONGSTATE,"DSPEP requires specifying the polynomial degree via DSPEPSetDegree()");
475: *rows = ds->n;
476: if (t==DS_MAT_A || t==DS_MAT_B || t==DS_MAT_W || t==DS_MAT_U) *rows *= ctx->d;
477: *cols = ds->n;
478: if (t==DS_MAT_A || t==DS_MAT_B || t==DS_MAT_W || t==DS_MAT_U || t==DS_MAT_X || t==DS_MAT_Y) *cols *= ctx->d;
479: PetscFunctionReturn(PETSC_SUCCESS);
480: }
482: /*MC
483: DSPEP - Dense Polynomial Eigenvalue Problem.
485: Level: beginner
487: Notes:
488: The problem is expressed as P(lambda)*x = 0, where P(.) is a matrix
489: polynomial of degree d. The eigenvalues lambda are the arguments
490: returned by DSSolve().
492: The degree of the polynomial, d, can be set with DSPEPSetDegree(), with
493: the first d+1 extra matrices of the DS defining the matrix polynomial. By
494: default, the polynomial is expressed in the monomial basis, but a
495: different basis can be used by setting the corresponding coefficients
496: via DSPEPSetCoefficients().
498: The problem is solved via linearization, by building a pencil (A,B) of
499: size p*n and solving the corresponding GNHEP.
501: Used DS matrices:
502: + DS_MAT_Ex - coefficients of the matrix polynomial
503: . DS_MAT_A - (workspace) first matrix of the linearization
504: . DS_MAT_B - (workspace) second matrix of the linearization
505: . DS_MAT_W - (workspace) right eigenvectors of the linearization
506: - DS_MAT_U - (workspace) left eigenvectors of the linearization
508: Implemented methods:
509: . 0 - QZ iteration on the linearization (_ggev)
511: .seealso: DSCreate(), DSSetType(), DSType, DSPEPSetDegree(), DSPEPSetCoefficients()
512: M*/
513: SLEPC_EXTERN PetscErrorCode DSCreate_PEP(DS ds)
514: {
515: DS_PEP *ctx;
517: PetscFunctionBegin;
518: PetscCall(PetscNew(&ctx));
519: ds->data = (void*)ctx;
521: ds->ops->allocate = DSAllocate_PEP;
522: ds->ops->view = DSView_PEP;
523: ds->ops->vectors = DSVectors_PEP;
524: ds->ops->solve[0] = DSSolve_PEP_QZ;
525: #if !defined(SLEPC_MISSING_LAPACK_GGES3)
526: ds->ops->solve[1] = DSSolve_PEP_QZ;
527: #endif
528: ds->ops->sort = DSSort_PEP;
529: #if !defined(PETSC_HAVE_MPIUNI)
530: ds->ops->synchronize = DSSynchronize_PEP;
531: #endif
532: ds->ops->destroy = DSDestroy_PEP;
533: ds->ops->matgetsize = DSMatGetSize_PEP;
534: PetscCall(PetscObjectComposeFunction((PetscObject)ds,"DSPEPSetDegree_C",DSPEPSetDegree_PEP));
535: PetscCall(PetscObjectComposeFunction((PetscObject)ds,"DSPEPGetDegree_C",DSPEPGetDegree_PEP));
536: PetscCall(PetscObjectComposeFunction((PetscObject)ds,"DSPEPSetCoefficients_C",DSPEPSetCoefficients_PEP));
537: PetscCall(PetscObjectComposeFunction((PetscObject)ds,"DSPEPGetCoefficients_C",DSPEPGetCoefficients_PEP));
538: PetscFunctionReturn(PETSC_SUCCESS);
539: }