Actual source code: dsnhepts.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: */
11: #include <slepc/private/dsimpl.h>
12: #include <slepcblaslapack.h>
14: typedef struct {
15: PetscScalar *wr,*wi; /* eigenvalues of B */
16: } DS_NHEPTS;
18: static PetscErrorCode DSAllocate_NHEPTS(DS ds,PetscInt ld)
19: {
20: DS_NHEPTS *ctx = (DS_NHEPTS*)ds->data;
22: PetscFunctionBegin;
23: PetscCall(DSAllocateMat_Private(ds,DS_MAT_A));
24: PetscCall(DSAllocateMat_Private(ds,DS_MAT_B));
25: PetscCall(DSAllocateMat_Private(ds,DS_MAT_Q));
26: PetscCall(DSAllocateMat_Private(ds,DS_MAT_Z));
27: PetscCall(PetscFree(ds->perm));
28: PetscCall(PetscMalloc1(ld,&ds->perm));
29: PetscCall(PetscMalloc1(ld,&ctx->wr));
30: #if !PetscDefined(USE_COMPLEX)
31: PetscCall(PetscMalloc1(ld,&ctx->wi));
32: #endif
33: PetscFunctionReturn(PETSC_SUCCESS);
34: }
36: static PetscErrorCode DSView_NHEPTS(DS ds,PetscViewer viewer)
37: {
38: PetscViewerFormat format;
40: PetscFunctionBegin;
41: PetscCall(PetscViewerGetFormat(viewer,&format));
42: if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) PetscFunctionReturn(PETSC_SUCCESS);
43: PetscCall(DSViewMat(ds,viewer,DS_MAT_A));
44: PetscCall(DSViewMat(ds,viewer,DS_MAT_B));
45: if (ds->state>DS_STATE_INTERMEDIATE) {
46: PetscCall(DSViewMat(ds,viewer,DS_MAT_Q));
47: PetscCall(DSViewMat(ds,viewer,DS_MAT_Z));
48: }
49: if (ds->omat[DS_MAT_X]) PetscCall(DSViewMat(ds,viewer,DS_MAT_X));
50: if (ds->omat[DS_MAT_Y]) PetscCall(DSViewMat(ds,viewer,DS_MAT_Y));
51: PetscFunctionReturn(PETSC_SUCCESS);
52: }
54: static PetscErrorCode DSVectors_NHEPTS_Eigen_Some(DS ds,PetscInt *k,PetscReal *rnorm,PetscBool left)
55: {
56: PetscInt i;
57: PetscBLASInt mm=1,mout,ld,n,*select,inc=1,cols=1,zero=0;
58: PetscScalar sone=1.0,szero=0.0;
59: PetscReal norm,done=1.0;
60: PetscBool iscomplex = PETSC_FALSE;
61: PetscScalar *X,*Y;
62: const PetscScalar *A,*Q;
64: PetscFunctionBegin;
65: PetscCall(PetscBLASIntCast(ds->n,&n));
66: PetscCall(PetscBLASIntCast(ds->ld,&ld));
67: PetscCall(DSAllocateWork_Private(ds,0,0,ld));
68: select = ds->iwork;
69: for (i=0;i<n;i++) select[i] = (PetscBLASInt)PETSC_FALSE;
71: /* compute k-th eigenvector Y of A */
72: PetscCall(MatDenseGetArrayRead(ds->omat[left?DS_MAT_B:DS_MAT_A],&A));
73: PetscCall(MatDenseGetArray(ds->omat[left?DS_MAT_Y:DS_MAT_X],&X));
74: Y = X+(*k)*ld;
75: select[*k] = (PetscBLASInt)PETSC_TRUE;
76: #if !PetscDefined(USE_COMPLEX)
77: if ((*k)<n-1 && A[(*k)+1+(*k)*ld]!=0.0) iscomplex = PETSC_TRUE;
78: mm = iscomplex? 2: 1;
79: if (iscomplex) select[(*k)+1] = (PetscBLASInt)PETSC_TRUE;
80: PetscCall(DSAllocateWork_Private(ds,3*ld,0,0));
81: PetscCallLAPACKInfo("LAPACKtrevc",LAPACKtrevc_("R","S",select,&n,(PetscScalar*)A,&ld,Y,&ld,Y,&ld,&mm,&mout,ds->work,&info));
82: #else
83: PetscCall(DSAllocateWork_Private(ds,2*ld,ld,0));
84: PetscCallLAPACKInfo("LAPACKtrevc",LAPACKtrevc_("R","S",select,&n,(PetscScalar*)A,&ld,Y,&ld,Y,&ld,&mm,&mout,ds->work,ds->rwork,&info));
85: #endif
86: PetscCheck(mout==mm,PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Inconsistent arguments");
87: PetscCall(MatDenseRestoreArrayRead(ds->omat[left?DS_MAT_B:DS_MAT_A],&A));
89: /* accumulate and normalize eigenvectors */
90: if (ds->state>=DS_STATE_CONDENSED) {
91: PetscCall(MatDenseGetArrayRead(ds->omat[left?DS_MAT_Z:DS_MAT_Q],&Q));
92: PetscCall(PetscArraycpy(ds->work,Y,mout*ld));
93: PetscCallBLAS("BLASgemv",BLASgemv_("N",&n,&n,&sone,Q,&ld,ds->work,&inc,&szero,Y,&inc));
94: #if !PetscDefined(USE_COMPLEX)
95: if (iscomplex) PetscCallBLAS("BLASgemv",BLASgemv_("N",&n,&n,&sone,Q,&ld,ds->work+ld,&inc,&szero,Y+ld,&inc));
96: #endif
97: PetscCall(MatDenseRestoreArrayRead(ds->omat[left?DS_MAT_Z:DS_MAT_Q],&Q));
98: cols = 1;
99: norm = BLASnrm2_(&n,Y,&inc);
100: #if !PetscDefined(USE_COMPLEX)
101: if (iscomplex) {
102: norm = SlepcAbsEigenvalue(norm,BLASnrm2_(&n,Y+ld,&inc));
103: cols = 2;
104: }
105: #endif
106: PetscCallLAPACKInfo("LAPACKlascl",LAPACKlascl_("G",&zero,&zero,&norm,&done,&n,&cols,Y,&ld,&info));
107: }
109: /* set output arguments */
110: if (iscomplex) (*k)++;
111: if (rnorm) {
112: if (iscomplex) *rnorm = SlepcAbsEigenvalue(Y[n-1],Y[n-1+ld]);
113: else *rnorm = PetscAbsScalar(Y[n-1]);
114: }
115: PetscCall(MatDenseRestoreArray(ds->omat[left?DS_MAT_Y:DS_MAT_X],&X));
116: PetscFunctionReturn(PETSC_SUCCESS);
117: }
119: static PetscErrorCode DSVectors_NHEPTS_Eigen_All(DS ds,PetscBool left)
120: {
121: PetscInt i;
122: PetscBLASInt n,ld,mout,inc=1,cols,zero=0;
123: PetscBool iscomplex;
124: PetscScalar *X;
125: const PetscScalar *A;
126: PetscReal norm,done=1.0;
127: const char *back;
129: PetscFunctionBegin;
130: PetscCall(PetscBLASIntCast(ds->n,&n));
131: PetscCall(PetscBLASIntCast(ds->ld,&ld));
132: PetscCall(MatDenseGetArrayRead(ds->omat[left?DS_MAT_B:DS_MAT_A],&A));
133: PetscCall(MatDenseGetArrayWrite(ds->omat[left?DS_MAT_Y:DS_MAT_X],&X));
134: if (ds->state>=DS_STATE_CONDENSED) {
135: /* DSSolve() has been called, backtransform with matrix Q */
136: back = "B";
137: PetscCall(MatCopy(ds->omat[left?DS_MAT_Z:DS_MAT_Q],ds->omat[left?DS_MAT_Y:DS_MAT_X],SAME_NONZERO_PATTERN));
138: } else back = "A";
139: #if !PetscDefined(USE_COMPLEX)
140: PetscCall(DSAllocateWork_Private(ds,3*ld,0,0));
141: PetscCallLAPACKInfo("LAPACKtrevc",LAPACKtrevc_("R",back,NULL,&n,(PetscScalar*)A,&ld,X,&ld,X,&ld,&n,&mout,ds->work,&info));
142: #else
143: PetscCall(DSAllocateWork_Private(ds,2*ld,ld,0));
144: PetscCallLAPACKInfo("LAPACKtrevc",LAPACKtrevc_("R",back,NULL,&n,(PetscScalar*)A,&ld,X,&ld,X,&ld,&n,&mout,ds->work,ds->rwork,&info));
145: #endif
147: /* normalize eigenvectors */
148: for (i=0;i<n;i++) {
149: iscomplex = (i<n-1 && A[i+1+i*ld]!=0.0)? PETSC_TRUE: PETSC_FALSE;
150: cols = 1;
151: norm = BLASnrm2_(&n,X+i*ld,&inc);
152: #if !PetscDefined(USE_COMPLEX)
153: if (iscomplex) {
154: norm = SlepcAbsEigenvalue(norm,BLASnrm2_(&n,X+(i+1)*ld,&inc));
155: cols = 2;
156: }
157: #endif
158: PetscCallLAPACKInfo("LAPACKlascl",LAPACKlascl_("G",&zero,&zero,&norm,&done,&n,&cols,X+i*ld,&ld,&info));
159: if (iscomplex) i++;
160: }
161: PetscCall(MatDenseRestoreArrayRead(ds->omat[left?DS_MAT_B:DS_MAT_A],&A));
162: PetscCall(MatDenseRestoreArrayWrite(ds->omat[left?DS_MAT_Y:DS_MAT_X],&X));
163: PetscFunctionReturn(PETSC_SUCCESS);
164: }
166: static PetscErrorCode DSVectors_NHEPTS(DS ds,DSMatType mat,PetscInt *j,PetscReal *rnorm)
167: {
168: PetscFunctionBegin;
169: switch (mat) {
170: case DS_MAT_X:
171: PetscCheck(!ds->refined,PetscObjectComm((PetscObject)ds),PETSC_ERR_SUP,"Not implemented yet");
172: if (j) PetscCall(DSVectors_NHEPTS_Eigen_Some(ds,j,rnorm,PETSC_FALSE));
173: else PetscCall(DSVectors_NHEPTS_Eigen_All(ds,PETSC_FALSE));
174: break;
175: case DS_MAT_Y:
176: PetscCheck(!ds->refined,PetscObjectComm((PetscObject)ds),PETSC_ERR_SUP,"Not implemented yet");
177: if (j) PetscCall(DSVectors_NHEPTS_Eigen_Some(ds,j,rnorm,PETSC_TRUE));
178: else PetscCall(DSVectors_NHEPTS_Eigen_All(ds,PETSC_TRUE));
179: break;
180: case DS_MAT_U:
181: case DS_MAT_V:
182: SETERRQ(PetscObjectComm((PetscObject)ds),PETSC_ERR_SUP,"Not implemented yet");
183: default:
184: SETERRQ(PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_OUTOFRANGE,"Invalid mat parameter");
185: }
186: PetscFunctionReturn(PETSC_SUCCESS);
187: }
189: static PetscErrorCode DSSort_NHEPTS(DS ds,PetscScalar *wr,PetscScalar *wi,PetscScalar *rr,PetscScalar *ri,PetscInt *k)
190: {
191: DS_NHEPTS *ctx = (DS_NHEPTS*)ds->data;
192: PetscInt i,j,cont,id=0,*p,*idx,*idx2;
193: PetscReal s,t;
194: #if PetscDefined(USE_COMPLEX)
195: Mat A,U;
196: #endif
198: PetscFunctionBegin;
199: PetscCheck(!rr || wr==rr,PetscObjectComm((PetscObject)ds),PETSC_ERR_SUP,"Not implemented yet");
200: PetscCall(PetscMalloc3(ds->ld,&idx,ds->ld,&idx2,ds->ld,&p));
201: PetscCall(DSSort_NHEP_Total(ds,DS_MAT_A,DS_MAT_Q,wr,wi));
202: #if PetscDefined(USE_COMPLEX)
203: PetscCall(DSGetMat(ds,DS_MAT_B,&A));
204: PetscCall(MatConjugate(A));
205: PetscCall(DSRestoreMat(ds,DS_MAT_B,&A));
206: PetscCall(DSGetMat(ds,DS_MAT_Z,&U));
207: PetscCall(MatConjugate(U));
208: PetscCall(DSRestoreMat(ds,DS_MAT_Z,&U));
209: for (i=0;i<ds->n;i++) ctx->wr[i] = PetscConj(ctx->wr[i]);
210: #endif
211: PetscCall(DSSort_NHEP_Total(ds,DS_MAT_B,DS_MAT_Z,ctx->wr,ctx->wi));
212: /* check correct eigenvalue correspondence */
213: cont = 0;
214: for (i=0;i<ds->n;i++) {
215: if (SlepcAbsEigenvalue(ctx->wr[i]-wr[i],ctx->wi[i]-wi[i])>PETSC_SQRT_MACHINE_EPSILON) {idx2[cont] = i; idx[cont++] = i;}
216: p[i] = -1;
217: }
218: if (cont) {
219: for (i=0;i<cont;i++) {
220: t = PETSC_MAX_REAL;
221: for (j=0;j<cont;j++) if (idx2[j]!=-1 && (s=SlepcAbsEigenvalue(ctx->wr[idx[j]]-wr[idx[i]],ctx->wi[idx[j]]-wi[idx[i]]))<t) { id = j; t = s; }
222: p[idx[i]] = idx[id];
223: idx2[id] = -1;
224: }
225: for (i=0;i<ds->n;i++) if (p[i]==-1) p[i] = i;
226: PetscCall(DSSortWithPermutation_NHEP_Private(ds,p,DS_MAT_B,DS_MAT_Z,ctx->wr,ctx->wi));
227: }
228: #if PetscDefined(USE_COMPLEX)
229: PetscCall(DSGetMat(ds,DS_MAT_B,&A));
230: PetscCall(MatConjugate(A));
231: PetscCall(DSRestoreMat(ds,DS_MAT_B,&A));
232: PetscCall(DSGetMat(ds,DS_MAT_Z,&U));
233: PetscCall(MatConjugate(U));
234: PetscCall(DSRestoreMat(ds,DS_MAT_Z,&U));
235: #endif
236: PetscCall(PetscFree3(idx,idx2,p));
237: PetscFunctionReturn(PETSC_SUCCESS);
238: }
240: static PetscErrorCode DSUpdateExtraRow_NHEPTS(DS ds)
241: {
242: PetscInt i;
243: PetscBLASInt n,ld,incx=1;
244: PetscScalar *A,*x,*y,one=1.0,zero=0.0;
245: const PetscScalar *Q;
247: PetscFunctionBegin;
248: PetscCall(PetscBLASIntCast(ds->n,&n));
249: PetscCall(PetscBLASIntCast(ds->ld,&ld));
250: PetscCall(DSAllocateWork_Private(ds,2*ld,0,0));
251: x = ds->work;
252: y = ds->work+ld;
253: PetscCall(MatDenseGetArray(ds->omat[DS_MAT_A],&A));
254: PetscCall(MatDenseGetArrayRead(ds->omat[DS_MAT_Q],&Q));
255: for (i=0;i<n;i++) x[i] = PetscConj(A[n+i*ld]);
256: PetscCallBLAS("BLASgemv",BLASgemv_("C",&n,&n,&one,Q,&ld,x,&incx,&zero,y,&incx));
257: for (i=0;i<n;i++) A[n+i*ld] = PetscConj(y[i]);
258: PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_A],&A));
259: PetscCall(MatDenseRestoreArrayRead(ds->omat[DS_MAT_Q],&Q));
260: PetscCall(MatDenseGetArray(ds->omat[DS_MAT_B],&A));
261: PetscCall(MatDenseGetArrayRead(ds->omat[DS_MAT_Z],&Q));
262: for (i=0;i<n;i++) x[i] = PetscConj(A[n+i*ld]);
263: PetscCallBLAS("BLASgemv",BLASgemv_("C",&n,&n,&one,Q,&ld,x,&incx,&zero,y,&incx));
264: for (i=0;i<n;i++) A[n+i*ld] = PetscConj(y[i]);
265: PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_B],&A));
266: PetscCall(MatDenseRestoreArrayRead(ds->omat[DS_MAT_Z],&Q));
267: ds->k = n;
268: PetscFunctionReturn(PETSC_SUCCESS);
269: }
271: static PetscErrorCode DSSolve_NHEPTS(DS ds,PetscScalar *wr,PetscScalar *wi)
272: {
273: DS_NHEPTS *ctx = (DS_NHEPTS*)ds->data;
275: PetscFunctionBegin;
276: #if !PetscDefined(USE_COMPLEX)
277: PetscAssertPointer(wi,3);
278: #endif
279: PetscCall(DSSolve_NHEP_Private(ds,DS_MAT_A,DS_MAT_Q,wr,wi));
280: PetscCall(DSSolve_NHEP_Private(ds,DS_MAT_B,DS_MAT_Z,ctx->wr,ctx->wi));
281: PetscFunctionReturn(PETSC_SUCCESS);
282: }
284: #if !PetscDefined(HAVE_MPIUNI)
285: static PetscErrorCode DSSynchronize_NHEPTS(DS ds,PetscScalar eigr[],PetscScalar eigi[])
286: {
287: PetscInt ld=ds->ld,l=ds->l,k;
288: PetscMPIInt n,rank,off=0,size,ldn;
289: DS_NHEPTS *ctx = (DS_NHEPTS*)ds->data;
290: PetscScalar *A,*B,*Q,*Z;
292: PetscFunctionBegin;
293: k = 2*(ds->n-l)*ld;
294: if (ds->state>DS_STATE_RAW) k += 2*(ds->n-l)*ld;
295: if (eigr) k += ds->n-l;
296: if (eigi) k += ds->n-l;
297: if (ctx->wr) k += ds->n-l;
298: if (ctx->wi) k += ds->n-l;
299: PetscCall(DSAllocateWork_Private(ds,k,0,0));
300: PetscCall(PetscMPIIntCast(k*sizeof(PetscScalar),&size));
301: PetscCall(PetscMPIIntCast(ds->n-l,&n));
302: PetscCall(PetscMPIIntCast(ld*(ds->n-l),&ldn));
303: PetscCall(MatDenseGetArray(ds->omat[DS_MAT_A],&A));
304: PetscCall(MatDenseGetArray(ds->omat[DS_MAT_B],&B));
305: if (ds->state>DS_STATE_RAW) {
306: PetscCall(MatDenseGetArray(ds->omat[DS_MAT_Q],&Q));
307: PetscCall(MatDenseGetArray(ds->omat[DS_MAT_Z],&Z));
308: }
309: PetscCallMPI(MPI_Comm_rank(PetscObjectComm((PetscObject)ds),&rank));
310: if (!rank) {
311: PetscCallMPI(MPI_Pack(A+l*ld,ldn,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds)));
312: PetscCallMPI(MPI_Pack(B+l*ld,ldn,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds)));
313: if (ds->state>DS_STATE_RAW) {
314: PetscCallMPI(MPI_Pack(Q+l*ld,ldn,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds)));
315: PetscCallMPI(MPI_Pack(Z+l*ld,ldn,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds)));
316: }
317: if (eigr) PetscCallMPI(MPI_Pack(eigr+l,n,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds)));
318: #if !PetscDefined(USE_COMPLEX)
319: if (eigi) PetscCallMPI(MPI_Pack(eigi+l,n,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds)));
320: #endif
321: if (ctx->wr) PetscCallMPI(MPI_Pack(ctx->wr+l,n,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds)));
322: if (ctx->wi) PetscCallMPI(MPI_Pack(ctx->wi+l,n,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds)));
323: }
324: PetscCallMPI(MPI_Bcast(ds->work,size,MPI_BYTE,0,PetscObjectComm((PetscObject)ds)));
325: if (rank) {
326: PetscCallMPI(MPI_Unpack(ds->work,size,&off,A+l*ld,ldn,MPIU_SCALAR,PetscObjectComm((PetscObject)ds)));
327: PetscCallMPI(MPI_Unpack(ds->work,size,&off,B+l*ld,ldn,MPIU_SCALAR,PetscObjectComm((PetscObject)ds)));
328: if (ds->state>DS_STATE_RAW) {
329: PetscCallMPI(MPI_Unpack(ds->work,size,&off,Q+l*ld,ldn,MPIU_SCALAR,PetscObjectComm((PetscObject)ds)));
330: PetscCallMPI(MPI_Unpack(ds->work,size,&off,Z+l*ld,ldn,MPIU_SCALAR,PetscObjectComm((PetscObject)ds)));
331: }
332: if (eigr) PetscCallMPI(MPI_Unpack(ds->work,size,&off,eigr+l,n,MPIU_SCALAR,PetscObjectComm((PetscObject)ds)));
333: #if !PetscDefined(USE_COMPLEX)
334: if (eigi) PetscCallMPI(MPI_Unpack(ds->work,size,&off,eigi+l,n,MPIU_SCALAR,PetscObjectComm((PetscObject)ds)));
335: #endif
336: if (ctx->wr) PetscCallMPI(MPI_Unpack(ds->work,size,&off,ctx->wr+l,n,MPIU_SCALAR,PetscObjectComm((PetscObject)ds)));
337: if (ctx->wi) PetscCallMPI(MPI_Unpack(ds->work,size,&off,ctx->wi+l,n,MPIU_SCALAR,PetscObjectComm((PetscObject)ds)));
338: }
339: PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_A],&A));
340: PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_B],&B));
341: if (ds->state>DS_STATE_RAW) {
342: PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_Q],&Q));
343: PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_Z],&Z));
344: }
345: PetscFunctionReturn(PETSC_SUCCESS);
346: }
347: #endif
349: static PetscErrorCode DSGetTruncateSize_NHEPTS(DS ds,PetscInt l,PetscInt n,PetscInt *k)
350: {
351: #if !PetscDefined(USE_COMPLEX)
352: const PetscScalar *A,*B;
353: #endif
355: PetscFunctionBegin;
356: #if !PetscDefined(USE_COMPLEX)
357: PetscCall(MatDenseGetArrayRead(ds->omat[DS_MAT_A],&A));
358: PetscCall(MatDenseGetArrayRead(ds->omat[DS_MAT_B],&B));
359: if (A[l+(*k)+(l+(*k)-1)*ds->ld] != 0.0 || B[l+(*k)+(l+(*k)-1)*ds->ld] != 0.0) {
360: if (l+(*k)<n-1) (*k)++;
361: else (*k)--;
362: }
363: PetscCall(MatDenseRestoreArrayRead(ds->omat[DS_MAT_A],&A));
364: PetscCall(MatDenseRestoreArrayRead(ds->omat[DS_MAT_B],&B));
365: #endif
366: PetscFunctionReturn(PETSC_SUCCESS);
367: }
369: static PetscErrorCode DSTruncate_NHEPTS(DS ds,PetscInt n,PetscBool trim)
370: {
371: PetscInt i,ld=ds->ld,l=ds->l;
372: PetscScalar *A,*B;
374: PetscFunctionBegin;
375: PetscCall(MatDenseGetArray(ds->omat[DS_MAT_A],&A));
376: PetscCall(MatDenseGetArray(ds->omat[DS_MAT_B],&B));
377: #if PetscDefined(USE_DEBUG)
378: /* make sure diagonal 2x2 block is not broken */
379: PetscCheck(ds->state<DS_STATE_CONDENSED || n==0 || n==ds->n || A[n+(n-1)*ld]==0.0 || B[n+(n-1)*ld]==0.0,PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"The given size would break a 2x2 block, call DSGetTruncateSize() first");
380: #endif
381: if (trim) {
382: if (ds->extrarow) { /* clean extra row */
383: for (i=l;i<ds->n;i++) { A[ds->n+i*ld] = 0.0; B[ds->n+i*ld] = 0.0; }
384: }
385: ds->l = 0;
386: ds->k = 0;
387: ds->n = n;
388: ds->t = ds->n; /* truncated length equal to the new dimension */
389: } else {
390: if (ds->extrarow && ds->k==ds->n) {
391: /* copy entries of extra row to the new position, then clean last row */
392: for (i=l;i<n;i++) { A[n+i*ld] = A[ds->n+i*ld]; B[n+i*ld] = B[ds->n+i*ld]; }
393: for (i=l;i<ds->n;i++) { A[ds->n+i*ld] = 0.0; B[ds->n+i*ld] = 0.0; }
394: }
395: ds->k = ds->extrarow? n: 0;
396: ds->t = ds->n; /* truncated length equal to previous dimension */
397: ds->n = n;
398: }
399: PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_A],&A));
400: PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_B],&B));
401: PetscFunctionReturn(PETSC_SUCCESS);
402: }
404: static PetscErrorCode DSDestroy_NHEPTS(DS ds)
405: {
406: DS_NHEPTS *ctx = (DS_NHEPTS*)ds->data;
408: PetscFunctionBegin;
409: PetscCall(PetscFree(ctx->wr));
410: PetscCall(PetscFree(ctx->wi));
411: PetscCall(PetscFree(ds->data));
412: PetscFunctionReturn(PETSC_SUCCESS);
413: }
415: static PetscErrorCode DSMatGetSize_NHEPTS(DS ds,DSMatType t,PetscInt *rows,PetscInt *cols)
416: {
417: PetscFunctionBegin;
418: *rows = ((t==DS_MAT_A || t==DS_MAT_B) && ds->extrarow)? ds->n+1: ds->n;
419: *cols = ds->n;
420: PetscFunctionReturn(PETSC_SUCCESS);
421: }
423: /*MC
424: DSNHEPTS - Dense Non-Hermitian Eigenvalue Problem (special variant intended
425: for two-sided Krylov solvers).
427: Notes:
428: Two related problems are solved, $AX = X\Lambda$ and $BY = Y\Lambda^*$, where $A$ and
429: $B$ are supposed to come from the Arnoldi factorizations of a certain matrix and its
430: (conjugate) transpose, respectively. Hence, in exact arithmetic the columns of $Y$
431: are equal to the left eigenvectors of $A$. $\Lambda$ is a diagonal matrix whose diagonal
432: elements are the arguments of `DSSolve()`. After solve, $A$ is overwritten with the
433: upper quasi-triangular matrix $T$ of the (real) Schur form, $AQ = QT$, and similarly
434: another (real) Schur relation is computed, $BZ = ZS$, overwriting $B$.
436: In the intermediate state $A$ and $B$ are reduced to upper Hessenberg form.
438: When left eigenvectors `DS_MAT_Y` are requested, right eigenvectors of $B$ are returned,
439: while `DS_MAT_X` contains right eigenvectors of $A$.
441: Used DS matrices:
442: + `DS_MAT_A` - first problem matrix obtained from Arnoldi
443: . `DS_MAT_B` - second problem matrix obtained from Arnoldi on the transpose
444: . `DS_MAT_Q` - orthogonal/unitary transformation that reduces $A$ to Hessenberg form
445: (intermediate step) or matrix of orthogonal Schur vectors of $A$
446: - `DS_MAT_Z` - orthogonal/unitary transformation that reduces $B$ to Hessenberg form
447: (intermediate step) or matrix of orthogonal Schur vectors of $B$
449: Implemented methods:
450: . 0 - Implicit QR (`_hseqr`)
452: Level: beginner
454: .seealso: [](sec:ds), `DSCreate()`, `DSSetType()`, `DSType`
455: M*/
456: SLEPC_EXTERN PetscErrorCode DSCreate_NHEPTS(DS ds)
457: {
458: DS_NHEPTS *ctx;
460: PetscFunctionBegin;
461: PetscCall(PetscNew(&ctx));
462: ds->data = (void*)ctx;
464: ds->ops->allocate = DSAllocate_NHEPTS;
465: ds->ops->view = DSView_NHEPTS;
466: ds->ops->vectors = DSVectors_NHEPTS;
467: ds->ops->solve[0] = DSSolve_NHEPTS;
468: ds->ops->sort = DSSort_NHEPTS;
469: #if !PetscDefined(HAVE_MPIUNI)
470: ds->ops->synchronize = DSSynchronize_NHEPTS;
471: #endif
472: ds->ops->gettruncatesize = DSGetTruncateSize_NHEPTS;
473: ds->ops->truncate = DSTruncate_NHEPTS;
474: ds->ops->update = DSUpdateExtraRow_NHEPTS;
475: ds->ops->destroy = DSDestroy_NHEPTS;
476: ds->ops->matgetsize = DSMatGetSize_NHEPTS;
477: PetscFunctionReturn(PETSC_SUCCESS);
478: }