Date: 2021-09-20T09:43:41+00:00

Actual source code: dspep.c
slepc-3.15.2 2021-09-20
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      1: /*
      2:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      3:    SLEPc - Scalable Library for Eigenvalue Problem Computations
      4:    Copyright (c) 2002-2021, 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;
    122:   PetscReal      *ca,*cb,*cg,norm,done=1.0;
    123:   PetscBLASInt   info,n,ld,ldd,nd,lrwork=0,lwork,one=1,zero=0,cols;
    124: #if defined(PETSC_USE_COMPLEX)
    125:   PetscReal      *rwork;
    126: #endif

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

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

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

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

    230:   /* copy and normalize eigenvectors */
    231:   for (j=0;j<nd;j++) {
    232:     PetscArraycpy(X+j*ds->ld,W+j*ldd,ds->n);
    233:     PetscArraycpy(Y+j*ds->ld,U+ds->n*(ctx->d-1)+j*ldd,ds->n);
    234:   }
    235:   for (j=0;j<nd;j++) {
    236:     cols = 1;
    237:     norm = BLASnrm2_(&n,X+j*ds->ld,&one);
    238: #if !defined(PETSC_USE_COMPLEX)
    239:     if (wi[j] != 0.0) {
    240:       norm = SlepcAbsEigenvalue(norm,BLASnrm2_(&n,X+(j+1)*ds->ld,&one));
    241:       cols = 2;
    242:     }
    243: #endif
    244:     PetscStackCallBLAS("LAPACKlascl",LAPACKlascl_("G",&zero,&zero,&norm,&done,&n,&cols,X+j*ds->ld,&ld,&info));
    245:     SlepcCheckLapackInfo("lascl",info);
    246:     norm = BLASnrm2_(&n,Y+j*ds->ld,&one);
    247: #if !defined(PETSC_USE_COMPLEX)
    248:     if (wi[j] != 0.0) norm = SlepcAbsEigenvalue(norm,BLASnrm2_(&n,Y+(j+1)*ds->ld,&one));
    249: #endif
    250:     PetscStackCallBLAS("LAPACKlascl",LAPACKlascl_("G",&zero,&zero,&norm,&done,&n,&cols,Y+j*ds->ld,&ld,&info));
    251:     SlepcCheckLapackInfo("lascl",info);
    252: #if !defined(PETSC_USE_COMPLEX)
    253:     if (wi[j] != 0.0) j++;
    254: #endif
    255:   }
    256:   return(0);
    257: }

    259: PetscErrorCode DSSynchronize_PEP(DS ds,PetscScalar eigr[],PetscScalar eigi[])
    260: {
    262:   DS_PEP         *ctx = (DS_PEP*)ds->data;
    263:   PetscInt       ld=ds->ld,k=0;
    264:   PetscMPIInt    ldnd,rank,off=0,size,dn;

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

    303: static PetscErrorCode DSPEPSetDegree_PEP(DS ds,PetscInt d)
    304: {
    305:   DS_PEP *ctx = (DS_PEP*)ds->data;

    308:   if (d<0) SETERRQ(PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_OUTOFRANGE,"The degree must be a non-negative integer");
    309:   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);
    310:   ctx->d = d;
    311:   return(0);
    312: }

    314: /*@
    315:    DSPEPSetDegree - Sets the polynomial degree for a DSPEP.

    317:    Logically Collective on ds

    319:    Input Parameters:
    320: +  ds - the direct solver context
    321: -  d  - the degree

    323:    Level: intermediate

    325: .seealso: DSPEPGetDegree()
    326: @*/
    327: PetscErrorCode DSPEPSetDegree(DS ds,PetscInt d)
    328: {

    334:   PetscTryMethod(ds,"DSPEPSetDegree_C",(DS,PetscInt),(ds,d));
    335:   return(0);
    336: }

    338: static PetscErrorCode DSPEPGetDegree_PEP(DS ds,PetscInt *d)
    339: {
    340:   DS_PEP *ctx = (DS_PEP*)ds->data;

    343:   *d = ctx->d;
    344:   return(0);
    345: }

    347: /*@
    348:    DSPEPGetDegree - Returns the polynomial degree for a DSPEP.

    350:    Not collective

    352:    Input Parameter:
    353: .  ds - the direct solver context

    355:    Output Parameters:
    356: .  d - the degree

    358:    Level: intermediate

    360: .seealso: DSPEPSetDegree()
    361: @*/
    362: PetscErrorCode DSPEPGetDegree(DS ds,PetscInt *d)
    363: {

    369:   PetscUseMethod(ds,"DSPEPGetDegree_C",(DS,PetscInt*),(ds,d));
    370:   return(0);
    371: }

    373: static PetscErrorCode DSPEPSetCoefficients_PEP(DS ds,PetscReal *pbc)
    374: {
    376:   DS_PEP         *ctx = (DS_PEP*)ds->data;
    377:   PetscInt       i;

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

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

    391:    Logically Collective on ds

    393:    Input Parameters:
    394: +  ds  - the direct solver context
    395: -  pbc - the polynomial basis coefficients

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

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

    410:    Level: advanced

    412: .seealso: DSPEPGetCoefficients(), DSPEPSetDegree()
    413: @*/
    414: PetscErrorCode DSPEPSetCoefficients(DS ds,PetscReal *pbc)
    415: {

    420:   PetscTryMethod(ds,"DSPEPSetCoefficients_C",(DS,PetscReal*),(ds,pbc));
    421:   return(0);
    422: }

    424: static PetscErrorCode DSPEPGetCoefficients_PEP(DS ds,PetscReal **pbc)
    425: {
    427:   DS_PEP         *ctx = (DS_PEP*)ds->data;
    428:   PetscInt       i;

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

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

    441:    Not collective

    443:    Input Parameter:
    444: .  ds - the direct solver context

    446:    Output Parameters:
    447: .  pbc - the polynomial basis coefficients

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

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

    459:    Level: advanced

    461: .seealso: DSPEPSetCoefficients()
    462: @*/
    463: PetscErrorCode DSPEPGetCoefficients(DS ds,PetscReal **pbc)
    464: {

    470:   PetscUseMethod(ds,"DSPEPGetCoefficients_C",(DS,PetscReal**),(ds,pbc));
    471:   return(0);
    472: }

    474: PetscErrorCode DSDestroy_PEP(DS ds)
    475: {
    477:   DS_PEP         *ctx = (DS_PEP*)ds->data;

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

    489: PetscErrorCode DSMatGetSize_PEP(DS ds,DSMatType t,PetscInt *rows,PetscInt *cols)
    490: {
    491:   DS_PEP *ctx = (DS_PEP*)ds->data;

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

    502: SLEPC_EXTERN PetscErrorCode DSCreate_PEP(DS ds)
    503: {
    504:   DS_PEP         *ctx;

    508:   PetscNewLog(ds,&ctx);
    509:   ds->data = (void*)ctx;

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