Date: 2021-02-01T14:41:44+00:00

Actual source code: dspep.c
slepc-3.14.2 2021-02-01
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      1: /*
      2:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      3:    SLEPc - Scalable Library for Eigenvalue Problem Computations
      4:    Copyright (c) 2002-2020, 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: PetscErrorCode DSAllocate_PEP(DS ds,PetscInt ld)
     20: {
     22:   DS_PEP         *ctx = (DS_PEP*)ds->data;
     23:   PetscInt       i;

     26:   if (!ctx->d) SETERRQ(PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_WRONGSTATE,"DSPEP requires specifying the polynomial degree via DSPEPSetDegree()");
     27:   DSAllocateMat_Private(ds,DS_MAT_X);
     28:   DSAllocateMat_Private(ds,DS_MAT_Y);
     29:   for (i=0;i<=ctx->d;i++) {
     30:     DSAllocateMat_Private(ds,DSMatExtra[i]);
     31:   }
     32:   PetscFree(ds->perm);
     33:   PetscMalloc1(ld*ctx->d,&ds->perm);
     34:   PetscLogObjectMemory((PetscObject)ds,ld*ctx->d*sizeof(PetscInt));
     35:   return(0);
     36: }

     38: PetscErrorCode DSView_PEP(DS ds,PetscViewer viewer)
     39: {
     40:   PetscErrorCode    ierr;
     41:   DS_PEP            *ctx = (DS_PEP*)ds->data;
     42:   PetscViewerFormat format;
     43:   PetscInt          i;

     46:   PetscViewerGetFormat(viewer,&format);
     47:   PetscViewerASCIIPrintf(viewer,"polynomial degree: %D\n",ctx->d);
     48:   if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) return(0);
     49:   for (i=0;i<=ctx->d;i++) {
     50:     DSViewMat(ds,viewer,DSMatExtra[i]);
     51:   }
     52:   if (ds->state>DS_STATE_INTERMEDIATE) { DSViewMat(ds,viewer,DS_MAT_X); }
     53:   return(0);
     54: }

     56: PetscErrorCode DSVectors_PEP(DS ds,DSMatType mat,PetscInt *j,PetscReal *rnorm)
     57: {
     59:   if (rnorm) SETERRQ(PetscObjectComm((PetscObject)ds),PETSC_ERR_SUP,"Not implemented yet");
     60:   switch (mat) {
     61:     case DS_MAT_X:
     62:       break;
     63:     case DS_MAT_Y:
     64:       break;
     65:     default:
     66:       SETERRQ(PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_OUTOFRANGE,"Invalid mat parameter");
     67:   }
     68:   return(0);
     69: }

     71: PetscErrorCode DSSort_PEP(DS ds,PetscScalar *wr,PetscScalar *wi,PetscScalar *rr,PetscScalar *ri,PetscInt *kout)
     72: {
     74:   DS_PEP         *ctx = (DS_PEP*)ds->data;
     75:   PetscInt       n,i,j,k,p,*perm,told,ld;
     76:   PetscScalar    *A,*X,*Y,rtmp,rtmp2;

     79:   if (!ds->sc) return(0);
     80:   n = ds->n*ctx->d;
     81:   A  = ds->mat[DS_MAT_A];
     82:   perm = ds->perm;
     83:   for (i=0;i<n;i++) perm[i] = i;
     84:   told = ds->t;
     85:   ds->t = n;  /* force the sorting routines to consider d*n eigenvalues */
     86:   if (rr) {
     87:     DSSortEigenvalues_Private(ds,rr,ri,perm,PETSC_FALSE);
     88:   } else {
     89:     DSSortEigenvalues_Private(ds,wr,wi,perm,PETSC_FALSE);
     90:   }
     91:   ds->t = told;  /* restore value of t */
     92:   for (i=0;i<n;i++) A[i]  = wr[perm[i]];
     93:   for (i=0;i<n;i++) wr[i] = A[i];
     94:   for (i=0;i<n;i++) A[i]  = wi[perm[i]];
     95:   for (i=0;i<n;i++) wi[i] = A[i];
     96:   /* cannot use DSPermuteColumns_Private() since matrix is not square */
     97:   ld = ds->ld;
     98:   X  = ds->mat[DS_MAT_X];
     99:   Y  = ds->mat[DS_MAT_Y];
    100:   for (i=0;i<n;i++) {
    101:     p = perm[i];
    102:     if (p != i) {
    103:       j = i + 1;
    104:       while (perm[j] != i) j++;
    105:       perm[j] = p; perm[i] = i;
    106:       /* swap columns i and j */
    107:       for (k=0;k<ds->n;k++) {
    108:         rtmp  = X[k+p*ld]; X[k+p*ld] = X[k+i*ld]; X[k+i*ld] = rtmp;
    109:         rtmp2 = Y[k+p*ld]; Y[k+p*ld] = Y[k+i*ld]; Y[k+i*ld] = rtmp2;
    110:       }
    111:     }
    112:   }
    113:   return(0);
    114: }

    116: PetscErrorCode DSSolve_PEP_QZ(DS ds,PetscScalar *wr,PetscScalar *wi)
    117: {
    119:   DS_PEP         *ctx = (DS_PEP*)ds->data;
    120:   PetscInt       i,j,k,off;
    121:   PetscScalar    *A,*B,*W,*X,*U,*Y,*E,*work,*beta,norm;
    122:   PetscReal      *ca,*cb,*cg;
    123:   PetscBLASInt   info,n,ldd,nd,lrwork=0,lwork,one=1;
    124: #if defined(PETSC_USE_COMPLEX)
    125:   PetscReal      *rwork;
    126: #else
    127:   PetscScalar    norm0;
    128: #endif

    131:   if (!ds->mat[DS_MAT_A]) {
    132:     DSAllocateMat_Private(ds,DS_MAT_A);
    133:   }
    134:   if (!ds->mat[DS_MAT_B]) {
    135:     DSAllocateMat_Private(ds,DS_MAT_B);
    136:   }
    137:   if (!ds->mat[DS_MAT_W]) {
    138:     DSAllocateMat_Private(ds,DS_MAT_W);
    139:   }
    140:   if (!ds->mat[DS_MAT_U]) {
    141:     DSAllocateMat_Private(ds,DS_MAT_U);
    142:   }
    143:   PetscBLASIntCast(ds->n*ctx->d,&nd);
    144:   PetscBLASIntCast(ds->n,&n);
    145:   PetscBLASIntCast(ds->ld*ctx->d,&ldd);
    146: #if defined(PETSC_USE_COMPLEX)
    147:   PetscBLASIntCast(nd+2*nd,&lwork);
    148:   PetscBLASIntCast(8*nd,&lrwork);
    149: #else
    150:   PetscBLASIntCast(nd+8*nd,&lwork);
    151: #endif
    152:   DSAllocateWork_Private(ds,lwork,lrwork,0);
    153:   beta = ds->work;
    154:   work = ds->work + nd;
    155:   lwork -= nd;
    156:   A = ds->mat[DS_MAT_A];
    157:   B = ds->mat[DS_MAT_B];
    158:   W = ds->mat[DS_MAT_W];
    159:   U = ds->mat[DS_MAT_U];
    160:   X = ds->mat[DS_MAT_X];
    161:   Y = ds->mat[DS_MAT_Y];
    162:   E = ds->mat[DSMatExtra[ctx->d]];

    164:   /* build matrices A and B of the linearization */
    165:   PetscArrayzero(A,ldd*ldd);
    166:   if (!ctx->pbc) { /* monomial basis */
    167:     for (i=0;i<nd-ds->n;i++) A[i+(i+ds->n)*ldd] = 1.0;
    168:     for (i=0;i<ctx->d;i++) {
    169:       off = i*ds->n*ldd+(ctx->d-1)*ds->n;
    170:       for (j=0;j<ds->n;j++) {
    171:         PetscArraycpy(A+off+j*ldd,ds->mat[DSMatExtra[i]]+j*ds->ld,ds->n);
    172:       }
    173:     }
    174:   } else {
    175:     ca = ctx->pbc;
    176:     cb = ca+ctx->d+1;
    177:     cg = cb+ctx->d+1;
    178:     for (i=0;i<ds->n;i++) {
    179:       A[i+(i+ds->n)*ldd] = ca[0];
    180:       A[i+i*ldd] = cb[0];
    181:     }
    182:     for (;i<nd-ds->n;i++) {
    183:       j = i/ds->n;
    184:       A[i+(i+ds->n)*ldd] = ca[j];
    185:       A[i+i*ldd] = cb[j];
    186:       A[i+(i-ds->n)*ldd] = cg[j];
    187:     }
    188:     for (i=0;i<ctx->d-2;i++) {
    189:       off = i*ds->n*ldd+(ctx->d-1)*ds->n;
    190:       for (j=0;j<ds->n;j++)
    191:         for (k=0;k<ds->n;k++)
    192:           *(A+off+j*ldd+k) = *(ds->mat[DSMatExtra[i]]+j*ds->ld+k)*ca[ctx->d-1];
    193:     }
    194:     off = i*ds->n*ldd+(ctx->d-1)*ds->n;
    195:     for (j=0;j<ds->n;j++)
    196:       for (k=0;k<ds->n;k++)
    197:         *(A+off+j*ldd+k) = *(ds->mat[DSMatExtra[i]]+j*ds->ld+k)*ca[ctx->d-1]-E[j*ds->ld+k]*cg[ctx->d-1];
    198:     off = (++i)*ds->n*ldd+(ctx->d-1)*ds->n;
    199:     for (j=0;j<ds->n;j++)
    200:       for (k=0;k<ds->n;k++)
    201:         *(A+off+j*ldd+k) = *(ds->mat[DSMatExtra[i]]+j*ds->ld+k)*ca[ctx->d-1]-E[j*ds->ld+k]*cb[ctx->d-1];
    202:   }
    203:   PetscArrayzero(B,ldd*ldd);
    204:   for (i=0;i<nd-ds->n;i++) B[i+i*ldd] = 1.0;
    205:   off = (ctx->d-1)*ds->n*(ldd+1);
    206:   for (j=0;j<ds->n;j++) {
    207:     for (i=0;i<ds->n;i++) B[off+i+j*ldd] = -E[i+j*ds->ld];
    208:   }

    210:   /* solve generalized eigenproblem */
    211: #if defined(PETSC_USE_COMPLEX)
    212:   rwork = ds->rwork;
    213:   PetscStackCallBLAS("LAPACKggev",LAPACKggev_("V","V",&nd,A,&ldd,B,&ldd,wr,beta,U,&ldd,W,&ldd,work,&lwork,rwork,&info));
    214: #else
    215:   PetscStackCallBLAS("LAPACKggev",LAPACKggev_("V","V",&nd,A,&ldd,B,&ldd,wr,wi,beta,U,&ldd,W,&ldd,work,&lwork,&info));
    216: #endif
    217:   SlepcCheckLapackInfo("ggev",info);

    219:   /* copy eigenvalues */
    220:   for (i=0;i<nd;i++) {
    221:     if (beta[i]==0.0) wr[i] = (PetscRealPart(wr[i])>0.0)? PETSC_MAX_REAL: PETSC_MIN_REAL;
    222:     else wr[i] /= beta[i];
    223: #if !defined(PETSC_USE_COMPLEX)
    224:     if (beta[i]==0.0) wi[i] = 0.0;
    225:     else wi[i] /= beta[i];
    226: #else
    227:     if (wi) wi[i] = 0.0;
    228: #endif
    229:   }

    231:   /* copy and normalize eigenvectors */
    232:   for (j=0;j<nd;j++) {
    233:     PetscArraycpy(X+j*ds->ld,W+j*ldd,ds->n);
    234:     PetscArraycpy(Y+j*ds->ld,U+ds->n*(ctx->d-1)+j*ldd,ds->n);
    235:   }
    236:   for (j=0;j<nd;j++) {
    237: #if !defined(PETSC_USE_COMPLEX)
    238:     if (wi[j] != 0.0) {
    239:       norm = BLASnrm2_(&n,X+j*ds->ld,&one);
    240:       norm0 = BLASnrm2_(&n,X+(j+1)*ds->ld,&one);
    241:       norm = 1.0/SlepcAbsEigenvalue(norm,norm0);
    242:       PetscStackCallBLAS("BLASscal",BLASscal_(&n,&norm,X+j*ds->ld,&one));
    243:       PetscStackCallBLAS("BLASscal",BLASscal_(&n,&norm,X+(j+1)*ds->ld,&one));
    244:       norm = BLASnrm2_(&n,Y+j*ds->ld,&one);
    245:       norm0 = BLASnrm2_(&n,Y+(j+1)*ds->ld,&one);
    246:       norm = 1.0/SlepcAbsEigenvalue(norm,norm0);
    247:       PetscStackCallBLAS("BLASscal",BLASscal_(&n,&norm,Y+j*ds->ld,&one));
    248:       PetscStackCallBLAS("BLASscal",BLASscal_(&n,&norm,Y+(j+1)*ds->ld,&one));
    249:       j++;
    250:     } else
    251: #endif
    252:     {
    253:       norm = 1.0/BLASnrm2_(&n,X+j*ds->ld,&one);
    254:       PetscStackCallBLAS("BLASscal",BLASscal_(&n,&norm,X+j*ds->ld,&one));
    255:       norm = 1.0/BLASnrm2_(&n,Y+j*ds->ld,&one);
    256:       PetscStackCallBLAS("BLASscal",BLASscal_(&n,&norm,Y+j*ds->ld,&one));
    257:     }
    258:   }
    259:   return(0);
    260: }

    262: PetscErrorCode DSSynchronize_PEP(DS ds,PetscScalar eigr[],PetscScalar eigi[])
    263: {
    265:   DS_PEP         *ctx = (DS_PEP*)ds->data;
    266:   PetscInt       ld=ds->ld,k=0;
    267:   PetscMPIInt    ldnd,rank,off=0,size,dn;

    270:   if (ds->state>=DS_STATE_CONDENSED) k += 2*ctx->d*ds->n*ld;
    271:   if (eigr) k += ctx->d*ds->n;
    272:   if (eigi) k += ctx->d*ds->n;
    273:   DSAllocateWork_Private(ds,k,0,0);
    274:   PetscMPIIntCast(k*sizeof(PetscScalar),&size);
    275:   PetscMPIIntCast(ds->n*ctx->d*ld,&ldnd);
    276:   PetscMPIIntCast(ctx->d*ds->n,&dn);
    277:   MPI_Comm_rank(PetscObjectComm((PetscObject)ds),&rank);
    278:   if (!rank) {
    279:     if (ds->state>=DS_STATE_CONDENSED) {
    280:       MPI_Pack(ds->mat[DS_MAT_X],ldnd,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds));
    281:       MPI_Pack(ds->mat[DS_MAT_Y],ldnd,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds));
    282:     }
    283:     if (eigr) {
    284:       MPI_Pack(eigr,dn,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds));
    285:     }
    286:     if (eigi) {
    287:       MPI_Pack(eigi,dn,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds));
    288:     }
    289:   }
    290:   MPI_Bcast(ds->work,size,MPI_BYTE,0,PetscObjectComm((PetscObject)ds));
    291:   if (rank) {
    292:     if (ds->state>=DS_STATE_CONDENSED) {
    293:       MPI_Unpack(ds->work,size,&off,ds->mat[DS_MAT_X],ldnd,MPIU_SCALAR,PetscObjectComm((PetscObject)ds));
    294:       MPI_Unpack(ds->work,size,&off,ds->mat[DS_MAT_Y],ldnd,MPIU_SCALAR,PetscObjectComm((PetscObject)ds));
    295:     }
    296:     if (eigr) {
    297:       MPI_Unpack(ds->work,size,&off,eigr,dn,MPIU_SCALAR,PetscObjectComm((PetscObject)ds));
    298:     }
    299:     if (eigi) {
    300:       MPI_Unpack(ds->work,size,&off,eigi,dn,MPIU_SCALAR,PetscObjectComm((PetscObject)ds));
    301:     }
    302:   }
    303:   return(0);
    304: }

    306: static PetscErrorCode DSPEPSetDegree_PEP(DS ds,PetscInt d)
    307: {
    308:   DS_PEP *ctx = (DS_PEP*)ds->data;

    311:   if (d<0) SETERRQ(PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_OUTOFRANGE,"The degree must be a non-negative integer");
    312:   if (d>=DS_NUM_EXTRA) SETERRQ1(PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_OUTOFRANGE,"Only implemented for polynomials of degree at most %D",DS_NUM_EXTRA-1);
    313:   ctx->d = d;
    314:   return(0);
    315: }

    317: /*@
    318:    DSPEPSetDegree - Sets the polynomial degree for a DSPEP.

    320:    Logically Collective on ds

    322:    Input Parameters:
    323: +  ds - the direct solver context
    324: -  d  - the degree

    326:    Level: intermediate

    328: .seealso: DSPEPGetDegree()
    329: @*/
    330: PetscErrorCode DSPEPSetDegree(DS ds,PetscInt d)
    331: {

    337:   PetscTryMethod(ds,"DSPEPSetDegree_C",(DS,PetscInt),(ds,d));
    338:   return(0);
    339: }

    341: static PetscErrorCode DSPEPGetDegree_PEP(DS ds,PetscInt *d)
    342: {
    343:   DS_PEP *ctx = (DS_PEP*)ds->data;

    346:   *d = ctx->d;
    347:   return(0);
    348: }

    350: /*@
    351:    DSPEPGetDegree - Returns the polynomial degree for a DSPEP.

    353:    Not collective

    355:    Input Parameter:
    356: .  ds - the direct solver context

    358:    Output Parameters:
    359: .  d - the degree

    361:    Level: intermediate

    363: .seealso: DSPEPSetDegree()
    364: @*/
    365: PetscErrorCode DSPEPGetDegree(DS ds,PetscInt *d)
    366: {

    372:   PetscUseMethod(ds,"DSPEPGetDegree_C",(DS,PetscInt*),(ds,d));
    373:   return(0);
    374: }

    376: static PetscErrorCode DSPEPSetCoefficients_PEP(DS ds,PetscReal *pbc)
    377: {
    379:   DS_PEP         *ctx = (DS_PEP*)ds->data;
    380:   PetscInt       i;

    383:   if (!ctx->d) SETERRQ(PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_WRONGSTATE,"Must first specify the polynomial degree via DSPEPSetDegree()");
    384:   if (ctx->pbc) { PetscFree(ctx->pbc); }
    385:   PetscMalloc1(3*(ctx->d+1),&ctx->pbc);
    386:   for (i=0;i<3*(ctx->d+1);i++) ctx->pbc[i] = pbc[i];
    387:   ds->state = DS_STATE_RAW;
    388:   return(0);
    389: }

    391: /*@C
    392:    DSPEPSetCoefficients - Sets the polynomial basis coefficients for a DSPEP.

    394:    Logically Collective on ds

    396:    Input Parameters:
    397: +  ds  - the direct solver context
    398: -  pbc - the polynomial basis coefficients

    400:    Notes:
    401:    This function is required only in the case of a polynomial specified in a
    402:    non-monomial basis, to provide the coefficients that will be used
    403:    during the linearization, multiplying the identity blocks on the three main
    404:    diagonal blocks. Depending on the polynomial basis (Chebyshev, Legendre, ...)
    405:    the coefficients must be different.

    407:    There must be a total of 3*(d+1) coefficients, where d is the degree of the
    408:    polynomial. The coefficients are arranged in three groups: alpha, beta, and
    409:    gamma, according to the definition of the three-term recurrence. In the case
    410:    of the monomial basis, alpha=1 and beta=gamma=0, in which case it is not
    411:    necessary to invoke this function.

    413:    Level: advanced

    415: .seealso: DSPEPGetCoefficients(), DSPEPSetDegree()
    416: @*/
    417: PetscErrorCode DSPEPSetCoefficients(DS ds,PetscReal *pbc)
    418: {

    423:   PetscTryMethod(ds,"DSPEPSetCoefficients_C",(DS,PetscReal*),(ds,pbc));
    424:   return(0);
    425: }

    427: static PetscErrorCode DSPEPGetCoefficients_PEP(DS ds,PetscReal **pbc)
    428: {
    430:   DS_PEP         *ctx = (DS_PEP*)ds->data;
    431:   PetscInt       i;

    434:   if (!ctx->d) SETERRQ(PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_WRONGSTATE,"Must first specify the polynomial degree via DSPEPSetDegree()");
    435:   PetscCalloc1(3*(ctx->d+1),pbc);
    436:   if (ctx->pbc) for (i=0;i<3*(ctx->d+1);i++) (*pbc)[i] = ctx->pbc[i];
    437:   else for (i=0;i<ctx->d+1;i++) (*pbc)[i] = 1.0;
    438:   return(0);
    439: }

    441: /*@C
    442:    DSPEPGetCoefficients - Returns the polynomial basis coefficients for a DSPEP.

    444:    Not collective

    446:    Input Parameter:
    447: .  ds - the direct solver context

    449:    Output Parameters:
    450: .  pbc - the polynomial basis coefficients

    452:    Note:
    453:    The returned array has length 3*(d+1) and should be freed by the user.

    455:    Fortran Note:
    456:    The calling sequence from Fortran is
    457: .vb
    458:    DSPEPGetCoefficients(eps,pbc,ierr)
    459:    double precision pbc(d+1) output
    460: .ve

    462:    Level: advanced

    464: .seealso: DSPEPSetCoefficients()
    465: @*/
    466: PetscErrorCode DSPEPGetCoefficients(DS ds,PetscReal **pbc)
    467: {

    473:   PetscUseMethod(ds,"DSPEPGetCoefficients_C",(DS,PetscReal**),(ds,pbc));
    474:   return(0);
    475: }

    477: PetscErrorCode DSDestroy_PEP(DS ds)
    478: {
    480:   DS_PEP         *ctx = (DS_PEP*)ds->data;

    483:   if (ctx->pbc) { PetscFree(ctx->pbc); }
    484:   PetscFree(ds->data);
    485:   PetscObjectComposeFunction((PetscObject)ds,"DSPEPSetDegree_C",NULL);
    486:   PetscObjectComposeFunction((PetscObject)ds,"DSPEPGetDegree_C",NULL);
    487:   PetscObjectComposeFunction((PetscObject)ds,"DSPEPSetCoefficients_C",NULL);
    488:   PetscObjectComposeFunction((PetscObject)ds,"DSPEPGetCoefficients_C",NULL);
    489:   return(0);
    490: }

    492: PetscErrorCode DSMatGetSize_PEP(DS ds,DSMatType t,PetscInt *rows,PetscInt *cols)
    493: {
    494:   DS_PEP *ctx = (DS_PEP*)ds->data;

    497:   if (!ctx->d) SETERRQ(PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_WRONGSTATE,"DSPEP requires specifying the polynomial degree via DSPEPSetDegree()");
    498:   *rows = ds->n;
    499:   if (t==DS_MAT_A || t==DS_MAT_B || t==DS_MAT_W || t==DS_MAT_U) *rows *= ctx->d;
    500:   *cols = ds->n;
    501:   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;
    502:   return(0);
    503: }

    505: SLEPC_EXTERN PetscErrorCode DSCreate_PEP(DS ds)
    506: {
    507:   DS_PEP         *ctx;

    511:   PetscNewLog(ds,&ctx);
    512:   ds->data = (void*)ctx;

    514:   ds->ops->allocate      = DSAllocate_PEP;
    515:   ds->ops->view          = DSView_PEP;
    516:   ds->ops->vectors       = DSVectors_PEP;
    517:   ds->ops->solve[0]      = DSSolve_PEP_QZ;
    518:   ds->ops->sort          = DSSort_PEP;
    519:   ds->ops->synchronize   = DSSynchronize_PEP;
    520:   ds->ops->destroy       = DSDestroy_PEP;
    521:   ds->ops->matgetsize    = DSMatGetSize_PEP;
    522:   PetscObjectComposeFunction((PetscObject)ds,"DSPEPSetDegree_C",DSPEPSetDegree_PEP);
    523:   PetscObjectComposeFunction((PetscObject)ds,"DSPEPGetDegree_C",DSPEPGetDegree_PEP);
    524:   PetscObjectComposeFunction((PetscObject)ds,"DSPEPSetCoefficients_C",DSPEPSetCoefficients_PEP);
    525:   PetscObjectComposeFunction((PetscObject)ds,"DSPEPGetCoefficients_C",DSPEPGetCoefficients_PEP);
    526:   return(0);
    527: }