Actual source code: ciss.c
slepc-3.21.1 2024-04-26
Report Typos and Errors

      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:    SLEPc eigensolver: "ciss"

     13:    Method: Contour Integral Spectral Slicing

     15:    Algorithm:

     17:        Contour integral based on Sakurai-Sugiura method to construct a
     18:        subspace, with various eigenpair extractions (Rayleigh-Ritz,
     19:        explicit moment).

     21:    Based on code contributed by Y. Maeda, T. Sakurai.

     23:    References:

     25:        [1] T. Sakurai and H. Sugiura, "A projection method for generalized
     26:            eigenvalue problems", J. Comput. Appl. Math. 159:119-128, 2003.

     28:        [2] T. Sakurai and H. Tadano, "CIRR: a Rayleigh-Ritz type method with
     29:            contour integral for generalized eigenvalue problems", Hokkaido
     30:            Math. J. 36:745-757, 2007.
     31: */

     33: #include <slepc/private/epsimpl.h>
     34: #include <slepc/private/slepccontour.h>
     35: #include <slepcblaslapack.h>

     37: typedef struct {
     38:   /* user parameters */
     39:   PetscInt          N;          /* number of integration points (32) */
     40:   PetscInt          L;          /* block size (16) */
     41:   PetscInt          M;          /* moment degree (N/4 = 4) */
     42:   PetscReal         delta;      /* threshold of singular value (1e-12) */
     43:   PetscInt          L_max;      /* maximum number of columns of the source matrix V */
     44:   PetscReal         spurious_threshold; /* discard spurious eigenpairs */
     45:   PetscBool         isreal;     /* A and B are real */
     46:   PetscInt          npart;      /* number of partitions */
     47:   PetscInt          refine_inner;
     48:   PetscInt          refine_blocksize;
     49:   EPSCISSQuadRule   quad;
     50:   EPSCISSExtraction extraction;
     51:   PetscBool         usest;
     52:   /* private data */
     53:   SlepcContourData  contour;
     54:   PetscReal         *sigma;     /* threshold for numerical rank */
     55:   PetscScalar       *weight;
     56:   PetscScalar       *omega;
     57:   PetscScalar       *pp;
     58:   BV                V;
     59:   BV                S;
     60:   BV                pV;
     61:   BV                Y;
     62:   PetscBool         useconj;
     63:   PetscBool         usest_set;  /* whether the user set the usest flag or not */
     64:   PetscObjectId     rgid;
     65:   PetscObjectState  rgstate;
     66: } EPS_CISS;

     68: /*
     69:   Set up KSP solvers for every integration point, only called if !ctx->usest
     70: */
     71: static PetscErrorCode EPSCISSSetUp(EPS eps,Mat A,Mat B,Mat Pa,Mat Pb)
     72: {
     73:   EPS_CISS         *ctx = (EPS_CISS*)eps->data;
     74:   SlepcContourData contour;
     75:   PetscInt         i,p_id,nsplit;
     76:   Mat              Amat,Pmat;
     77:   MatStructure     str,strp;

     79:   PetscFunctionBegin;
     80:   if (!ctx->contour || !ctx->contour->ksp) PetscCall(EPSCISSGetKSPs(eps,NULL,NULL));
     81:   PetscAssert(ctx->contour && ctx->contour->ksp,PetscObjectComm((PetscObject)eps),PETSC_ERR_PLIB,"Something went wrong with EPSCISSGetKSPs()");
     82:   contour = ctx->contour;
     83:   PetscCall(STGetMatStructure(eps->st,&str));
     84:   PetscCall(STGetSplitPreconditionerInfo(eps->st,&nsplit,&strp));
     85:   for (i=0;i<contour->npoints;i++) {
     86:     p_id = i*contour->subcomm->n + contour->subcomm->color;
     87:     PetscCall(MatDuplicate(A,MAT_COPY_VALUES,&Amat));
     88:     if (B) PetscCall(MatAXPY(Amat,-ctx->omega[p_id],B,str));
     89:     else PetscCall(MatShift(Amat,-ctx->omega[p_id]));
     90:     if (nsplit) {
     91:       PetscCall(MatDuplicate(Pa,MAT_COPY_VALUES,&Pmat));
     92:       if (Pb) PetscCall(MatAXPY(Pmat,-ctx->omega[p_id],Pb,strp));
     93:       else PetscCall(MatShift(Pmat,-ctx->omega[p_id]));
     94:     } else Pmat = Amat;
     95:     PetscCall(EPS_KSPSetOperators(contour->ksp[i],Amat,Amat));
     96:     PetscCall(MatDestroy(&Amat));
     97:     if (nsplit) PetscCall(MatDestroy(&Pmat));
     98:   }
     99:   PetscFunctionReturn(PETSC_SUCCESS);
    100: }

    102: /*
    103:   Y_i = (A-z_i B)^{-1}BV for every integration point, Y=[Y_i] is in the context
    104: */
    105: static PetscErrorCode EPSCISSSolve(EPS eps,Mat B,BV V,PetscInt L_start,PetscInt L_end)
    106: {
    107:   EPS_CISS         *ctx = (EPS_CISS*)eps->data;
    108:   SlepcContourData contour;
    109:   PetscInt         i,p_id;
    110:   Mat              MV,BMV=NULL,MC;
    111:   KSP              ksp;

    113:   PetscFunctionBegin;
    114:   if (!ctx->contour || !ctx->contour->ksp) PetscCall(EPSCISSGetKSPs(eps,NULL,NULL));
    115:   contour = ctx->contour;
    116:   PetscAssert(ctx->contour && ctx->contour->ksp,PetscObjectComm((PetscObject)eps),PETSC_ERR_PLIB,"Something went wrong with EPSCISSGetKSPs()");
    117:   PetscCall(BVSetActiveColumns(V,L_start,L_end));
    118:   PetscCall(BVGetMat(V,&MV));
    119:   for (i=0;i<contour->npoints;i++) {
    120:     p_id = i*contour->subcomm->n + contour->subcomm->color;
    121:     if (ctx->usest)  {
    122:       PetscCall(STSetShift(eps->st,ctx->omega[p_id]));
    123:       PetscCall(STGetKSP(eps->st,&ksp));
    124:     } else ksp = contour->ksp[i];
    125:     PetscCall(BVSetActiveColumns(ctx->Y,i*ctx->L+L_start,i*ctx->L+L_end));
    126:     PetscCall(BVGetMat(ctx->Y,&MC));
    127:     if (B) {
    128:       if (!i) {
    129:         PetscCall(MatProductCreate(B,MV,NULL,&BMV));
    130:         PetscCall(MatProductSetType(BMV,MATPRODUCT_AB));
    131:         PetscCall(MatProductSetFromOptions(BMV));
    132:         PetscCall(MatProductSymbolic(BMV));
    133:       }
    134:       PetscCall(MatProductNumeric(BMV));
    135:       PetscCall(KSPMatSolve(ksp,BMV,MC));
    136:     } else PetscCall(KSPMatSolve(ksp,MV,MC));
    137:     PetscCall(BVRestoreMat(ctx->Y,&MC));
    138:     if (ctx->usest && i<contour->npoints-1) PetscCall(KSPReset(ksp));
    139:   }
    140:   PetscCall(MatDestroy(&BMV));
    141:   PetscCall(BVRestoreMat(V,&MV));
    142:   PetscFunctionReturn(PETSC_SUCCESS);
    143: }

    145: static PetscErrorCode rescale_eig(EPS eps,PetscInt nv)
    146: {
    147:   EPS_CISS       *ctx = (EPS_CISS*)eps->data;
    148:   PetscInt       i;
    149:   PetscScalar    center;
    150:   PetscReal      radius,a,b,c,d,rgscale;
    151: #if defined(PETSC_USE_COMPLEX)
    152:   PetscReal      start_ang,end_ang,vscale,theta;
    153: #endif
    154:   PetscBool      isring,isellipse,isinterval;

    156:   PetscFunctionBegin;
    157:   PetscCall(PetscObjectTypeCompare((PetscObject)eps->rg,RGELLIPSE,&isellipse));
    158:   PetscCall(PetscObjectTypeCompare((PetscObject)eps->rg,RGRING,&isring));
    159:   PetscCall(PetscObjectTypeCompare((PetscObject)eps->rg,RGINTERVAL,&isinterval));
    160:   PetscCall(RGGetScale(eps->rg,&rgscale));
    161:   if (isinterval) {
    162:     PetscCall(RGIntervalGetEndpoints(eps->rg,NULL,NULL,&c,&d));
    163:     if (c==d) {
    164:       for (i=0;i<nv;i++) {
    165: #if defined(PETSC_USE_COMPLEX)
    166:         eps->eigr[i] = PetscRealPart(eps->eigr[i]);
    167: #else
    168:         eps->eigi[i] = 0;
    169: #endif
    170:       }
    171:     }
    172:   }
    173:   if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) {
    174:     if (isellipse) {
    175:       PetscCall(RGEllipseGetParameters(eps->rg,&center,&radius,NULL));
    176:       for (i=0;i<nv;i++) eps->eigr[i] = rgscale*(center + radius*eps->eigr[i]);
    177:     } else if (isinterval) {
    178:       PetscCall(RGIntervalGetEndpoints(eps->rg,&a,&b,&c,&d));
    179:       if (ctx->quad == EPS_CISS_QUADRULE_CHEBYSHEV) {
    180:         for (i=0;i<nv;i++) {
    181:           if (c==d) eps->eigr[i] = ((b-a)*(eps->eigr[i]+1.0)/2.0+a)*rgscale;
    182:           if (a==b) {
    183: #if defined(PETSC_USE_COMPLEX)
    184:             eps->eigr[i] = ((d-c)*(eps->eigr[i]+1.0)/2.0+c)*rgscale*PETSC_i;
    185: #else
    186:             SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Integration points on a vertical line require complex arithmetic");
    187: #endif
    188:           }
    189:         }
    190:       } else {
    191:         center = (b+a)/2.0+(d+c)/2.0*PETSC_PI;
    192:         radius = PetscSqrtReal(PetscPowRealInt((b-a)/2.0,2)+PetscPowRealInt((d-c)/2.0,2));
    193:         for (i=0;i<nv;i++) eps->eigr[i] = center + radius*eps->eigr[i];
    194:       }
    195:     } else if (isring) {  /* only supported in complex scalars */
    196: #if defined(PETSC_USE_COMPLEX)
    197:       PetscCall(RGRingGetParameters(eps->rg,&center,&radius,&vscale,&start_ang,&end_ang,NULL));
    198:       if (ctx->quad == EPS_CISS_QUADRULE_CHEBYSHEV) {
    199:         for (i=0;i<nv;i++) {
    200:           theta = (start_ang*2.0+(end_ang-start_ang)*(PetscRealPart(eps->eigr[i])+1.0))*PETSC_PI;
    201:           eps->eigr[i] = rgscale*center + (rgscale*radius+PetscImaginaryPart(eps->eigr[i]))*PetscCMPLX(PetscCosReal(theta),vscale*PetscSinReal(theta));
    202:         }
    203:       } else {
    204:         for (i=0;i<nv;i++) eps->eigr[i] = rgscale*(center + radius*eps->eigr[i]);
    205:       }
    206: #endif
    207:     }
    208:   }
    209:   PetscFunctionReturn(PETSC_SUCCESS);
    210: }

    212: static PetscErrorCode EPSSetUp_CISS(EPS eps)
    213: {
    214:   EPS_CISS         *ctx = (EPS_CISS*)eps->data;
    215:   SlepcContourData contour;
    216:   PetscBool        istrivial,isring,isellipse,isinterval,flg;
    217:   PetscReal        c,d;
    218:   PetscInt         nsplit;
    219:   PetscRandom      rand;
    220:   PetscObjectId    id;
    221:   PetscObjectState state;
    222:   Mat              A[2],Psplit[2];
    223:   Vec              v0;

    225:   PetscFunctionBegin;
    226:   if (eps->ncv==PETSC_DEFAULT) {
    227:     eps->ncv = ctx->L_max*ctx->M;
    228:     if (eps->ncv>eps->n) {
    229:       eps->ncv = eps->n;
    230:       ctx->L_max = eps->ncv/ctx->M;
    231:       PetscCheck(ctx->L_max,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"Cannot adjust solver parameters, try setting a smaller value of M (moment size)");
    232:     }
    233:   } else {
    234:     PetscCall(EPSSetDimensions_Default(eps,eps->nev,&eps->ncv,&eps->mpd));
    235:     ctx->L_max = eps->ncv/ctx->M;
    236:     if (!ctx->L_max) {
    237:       ctx->L_max = 1;
    238:       eps->ncv = ctx->L_max*ctx->M;
    239:     }
    240:   }
    241:   ctx->L = PetscMin(ctx->L,ctx->L_max);
    242:   if (eps->max_it==PETSC_DEFAULT) eps->max_it = 5;
    243:   if (eps->mpd==PETSC_DEFAULT) eps->mpd = eps->ncv;
    244:   if (!eps->which) eps->which = EPS_ALL;
    245:   PetscCheck(eps->which==EPS_ALL,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"This solver supports only computing all eigenvalues");
    246:   EPSCheckUnsupported(eps,EPS_FEATURE_BALANCE | EPS_FEATURE_ARBITRARY | EPS_FEATURE_EXTRACTION | EPS_FEATURE_STOPPING | EPS_FEATURE_TWOSIDED);

    248:   /* check region */
    249:   PetscCall(RGIsTrivial(eps->rg,&istrivial));
    250:   PetscCheck(!istrivial,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"CISS requires a nontrivial region, e.g. -rg_type ellipse ...");
    251:   PetscCall(RGGetComplement(eps->rg,&flg));
    252:   PetscCheck(!flg,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"A region with complement flag set is not allowed");
    253:   PetscCall(PetscObjectTypeCompare((PetscObject)eps->rg,RGELLIPSE,&isellipse));
    254:   PetscCall(PetscObjectTypeCompare((PetscObject)eps->rg,RGRING,&isring));
    255:   PetscCall(PetscObjectTypeCompare((PetscObject)eps->rg,RGINTERVAL,&isinterval));
    256:   PetscCheck(isellipse || isring || isinterval,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"Currently only implemented for interval, elliptic or ring regions");

    258:   /* if the region has changed, then reset contour data */
    259:   PetscCall(PetscObjectGetId((PetscObject)eps->rg,&id));
    260:   PetscCall(PetscObjectStateGet((PetscObject)eps->rg,&state));
    261:   if (ctx->rgid && (id != ctx->rgid || state != ctx->rgstate)) {
    262:     PetscCall(SlepcContourDataDestroy(&ctx->contour));
    263:     PetscCall(PetscInfo(eps,"Resetting the contour data structure due to a change of region\n"));
    264:     ctx->rgid = id; ctx->rgstate = state;
    265:   }

    267: #if !defined(PETSC_USE_COMPLEX)
    268:   PetscCheck(!isring,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"Ring region only supported for complex scalars");
    269: #endif
    270:   if (isinterval) {
    271:     PetscCall(RGIntervalGetEndpoints(eps->rg,NULL,NULL,&c,&d));
    272: #if !defined(PETSC_USE_COMPLEX)
    273:     PetscCheck(c==d && c==0.0,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"In real scalars, endpoints of the imaginary axis must be both zero");
    274: #endif
    275:     if (!ctx->quad && c==d) ctx->quad = EPS_CISS_QUADRULE_CHEBYSHEV;
    276:   }
    277:   if (!ctx->quad) ctx->quad = EPS_CISS_QUADRULE_TRAPEZOIDAL;

    279:   /* create contour data structure */
    280:   if (!ctx->contour) {
    281:     PetscCall(RGCanUseConjugates(eps->rg,ctx->isreal,&ctx->useconj));
    282:     PetscCall(SlepcContourDataCreate(ctx->useconj?ctx->N/2:ctx->N,ctx->npart,(PetscObject)eps,&ctx->contour));
    283:   }

    285:   PetscCall(EPSAllocateSolution(eps,0));
    286:   PetscCall(BVGetRandomContext(eps->V,&rand));  /* make sure the random context is available when duplicating */
    287:   if (ctx->weight) PetscCall(PetscFree4(ctx->weight,ctx->omega,ctx->pp,ctx->sigma));
    288:   PetscCall(PetscMalloc4(ctx->N,&ctx->weight,ctx->N+1,&ctx->omega,ctx->N,&ctx->pp,ctx->L_max*ctx->M,&ctx->sigma));

    290:   /* allocate basis vectors */
    291:   PetscCall(BVDestroy(&ctx->S));
    292:   PetscCall(BVDuplicateResize(eps->V,ctx->L*ctx->M,&ctx->S));
    293:   PetscCall(BVDestroy(&ctx->V));
    294:   PetscCall(BVDuplicateResize(eps->V,ctx->L,&ctx->V));

    296:   PetscCall(STGetMatrix(eps->st,0,&A[0]));
    297:   PetscCall(MatIsShell(A[0],&flg));
    298:   PetscCheck(!flg,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"Matrix type shell is not supported in this solver");
    299:   if (eps->isgeneralized) PetscCall(STGetMatrix(eps->st,1,&A[1]));

    301:   if (!ctx->usest_set) ctx->usest = (ctx->npart>1)? PETSC_FALSE: PETSC_TRUE;
    302:   PetscCheck(!ctx->usest || ctx->npart==1,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"The usest flag is not supported when partitions > 1");

    304:   /* check if a user-defined split preconditioner has been set */
    305:   PetscCall(STGetSplitPreconditionerInfo(eps->st,&nsplit,NULL));
    306:   if (nsplit) {
    307:     PetscCall(STGetSplitPreconditionerTerm(eps->st,0,&Psplit[0]));
    308:     if (eps->isgeneralized) PetscCall(STGetSplitPreconditionerTerm(eps->st,1,&Psplit[1]));
    309:   }

    311:   contour = ctx->contour;
    312:   PetscCall(SlepcContourRedundantMat(contour,eps->isgeneralized?2:1,A,nsplit?Psplit:NULL));
    313:   if (contour->pA) {
    314:     PetscCall(BVGetColumn(ctx->V,0,&v0));
    315:     PetscCall(SlepcContourScatterCreate(contour,v0));
    316:     PetscCall(BVRestoreColumn(ctx->V,0,&v0));
    317:     PetscCall(BVDestroy(&ctx->pV));
    318:     PetscCall(BVCreate(PetscObjectComm((PetscObject)contour->xsub),&ctx->pV));
    319:     PetscCall(BVSetSizesFromVec(ctx->pV,contour->xsub,eps->n));
    320:     PetscCall(BVSetFromOptions(ctx->pV));
    321:     PetscCall(BVResize(ctx->pV,ctx->L,PETSC_FALSE));
    322:   }

    324:   EPSCheckDefinite(eps);
    325:   EPSCheckSinvertCondition(eps,ctx->usest," (with the usest flag set)");

    327:   PetscCall(BVDestroy(&ctx->Y));
    328:   if (contour->pA) {
    329:     PetscCall(BVCreate(PetscObjectComm((PetscObject)contour->xsub),&ctx->Y));
    330:     PetscCall(BVSetSizesFromVec(ctx->Y,contour->xsub,eps->n));
    331:     PetscCall(BVSetFromOptions(ctx->Y));
    332:     PetscCall(BVResize(ctx->Y,contour->npoints*ctx->L,PETSC_FALSE));
    333:   } else PetscCall(BVDuplicateResize(eps->V,contour->npoints*ctx->L,&ctx->Y));

    335:   if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) PetscCall(DSSetType(eps->ds,DSGNHEP));
    336:   else if (eps->isgeneralized) {
    337:     if (eps->ishermitian && eps->ispositive) PetscCall(DSSetType(eps->ds,DSGHEP));
    338:     else PetscCall(DSSetType(eps->ds,DSGNHEP));
    339:   } else {
    340:     if (eps->ishermitian) PetscCall(DSSetType(eps->ds,DSHEP));
    341:     else PetscCall(DSSetType(eps->ds,DSNHEP));
    342:   }
    343:   PetscCall(DSAllocate(eps->ds,eps->ncv));

    345: #if !defined(PETSC_USE_COMPLEX)
    346:   PetscCall(EPSSetWorkVecs(eps,3));
    347:   if (!eps->ishermitian) PetscCall(PetscInfo(eps,"Warning: complex eigenvalues are not calculated exactly without --with-scalar-type=complex in PETSc\n"));
    348: #else
    349:   PetscCall(EPSSetWorkVecs(eps,2));
    350: #endif
    351:   PetscFunctionReturn(PETSC_SUCCESS);
    352: }

    354: static PetscErrorCode EPSSetUpSort_CISS(EPS eps)
    355: {
    356:   SlepcSC        sc;

    358:   PetscFunctionBegin;
    359:   /* fill sorting criterion context */
    360:   eps->sc->comparison    = SlepcCompareSmallestReal;
    361:   eps->sc->comparisonctx = NULL;
    362:   eps->sc->map           = NULL;
    363:   eps->sc->mapobj        = NULL;

    365:   /* fill sorting criterion for DS */
    366:   PetscCall(DSGetSlepcSC(eps->ds,&sc));
    367:   sc->comparison    = SlepcCompareLargestMagnitude;
    368:   sc->comparisonctx = NULL;
    369:   sc->map           = NULL;
    370:   sc->mapobj        = NULL;
    371:   PetscFunctionReturn(PETSC_SUCCESS);
    372: }

    374: static PetscErrorCode EPSSolve_CISS(EPS eps)
    375: {
    376:   EPS_CISS         *ctx = (EPS_CISS*)eps->data;
    377:   SlepcContourData contour = ctx->contour;
    378:   Mat              A,B,X,M,pA,pB,T,J,Pa=NULL,Pb=NULL;
    379:   BV               V;
    380:   PetscInt         i,j,ld,nmat,L_add=0,nv=0,L_base=ctx->L,inner,nlocal,*inside,nsplit;
    381:   PetscScalar      *Mu,*H0,*H1=NULL,*rr,*temp;
    382:   PetscReal        error,max_error,norm;
    383:   PetscBool        *fl1;
    384:   Vec              si,si1=NULL,w[3];
    385:   PetscRandom      rand;
    386: #if defined(PETSC_USE_COMPLEX)
    387:   PetscBool        isellipse;
    388:   PetscReal        est_eig,eta;
    389: #else
    390:   PetscReal        normi;
    391: #endif

    393:   PetscFunctionBegin;
    394:   w[0] = eps->work[0];
    395: #if defined(PETSC_USE_COMPLEX)
    396:   w[1] = NULL;
    397: #else
    398:   w[1] = eps->work[2];
    399: #endif
    400:   w[2] = eps->work[1];
    401:   PetscCall(VecGetLocalSize(w[0],&nlocal));
    402:   PetscCall(DSGetLeadingDimension(eps->ds,&ld));
    403:   PetscCall(RGComputeQuadrature(eps->rg,ctx->quad==EPS_CISS_QUADRULE_CHEBYSHEV?RG_QUADRULE_CHEBYSHEV:RG_QUADRULE_TRAPEZOIDAL,ctx->N,ctx->omega,ctx->pp,ctx->weight));
    404:   PetscCall(STGetNumMatrices(eps->st,&nmat));
    405:   PetscCall(STGetMatrix(eps->st,0,&A));
    406:   if (nmat>1) PetscCall(STGetMatrix(eps->st,1,&B));
    407:   else B = NULL;
    408:   J = (contour->pA && nmat>1)? contour->pA[1]: B;
    409:   V = contour->pA? ctx->pV: ctx->V;
    410:   if (!ctx->usest) {
    411:     T = contour->pA? contour->pA[0]: A;
    412:     PetscCall(STGetSplitPreconditionerInfo(eps->st,&nsplit,NULL));
    413:     if (nsplit) {
    414:       if (contour->pA) {
    415:         Pa = contour->pP[0];
    416:         if (nsplit>1) Pb = contour->pP[1];
    417:       } else {
    418:         PetscCall(STGetSplitPreconditionerTerm(eps->st,0,&Pa));
    419:         if (nsplit>1) PetscCall(STGetSplitPreconditionerTerm(eps->st,1,&Pb));
    420:       }
    421:     }
    422:     PetscCall(EPSCISSSetUp(eps,T,J,Pa,Pb));
    423:   }
    424:   PetscCall(BVSetActiveColumns(ctx->V,0,ctx->L));
    425:   PetscCall(BVSetRandomSign(ctx->V));
    426:   PetscCall(BVGetRandomContext(ctx->V,&rand));

    428:   if (contour->pA) PetscCall(BVScatter(ctx->V,ctx->pV,contour->scatterin,contour->xdup));
    429:   PetscCall(EPSCISSSolve(eps,J,V,0,ctx->L));
    430: #if defined(PETSC_USE_COMPLEX)
    431:   PetscCall(PetscObjectTypeCompare((PetscObject)eps->rg,RGELLIPSE,&isellipse));
    432:   if (isellipse) {
    433:     PetscCall(BVTraceQuadrature(ctx->Y,ctx->V,ctx->L,ctx->L,ctx->weight,contour->scatterin,contour->subcomm,contour->npoints,ctx->useconj,&est_eig));
    434:     PetscCall(PetscInfo(eps,"Estimated eigenvalue count: %f\n",(double)est_eig));
    435:     eta = PetscPowReal(10.0,-PetscLog10Real(eps->tol)/ctx->N);
    436:     L_add = PetscMax(0,(PetscInt)PetscCeilReal((est_eig*eta)/ctx->M)-ctx->L);
    437:     if (L_add>ctx->L_max-ctx->L) {
    438:       PetscCall(PetscInfo(eps,"Number of eigenvalues inside the contour path may be too large\n"));
    439:       L_add = ctx->L_max-ctx->L;
    440:     }
    441:   }
    442: #endif
    443:   if (L_add>0) {
    444:     PetscCall(PetscInfo(eps,"Changing L %" PetscInt_FMT " -> %" PetscInt_FMT " by Estimate #Eig\n",ctx->L,ctx->L+L_add));
    445:     PetscCall(BVCISSResizeBases(ctx->S,contour->pA?ctx->pV:ctx->V,ctx->Y,ctx->L,ctx->L+L_add,ctx->M,contour->npoints));
    446:     PetscCall(BVSetActiveColumns(ctx->V,ctx->L,ctx->L+L_add));
    447:     PetscCall(BVSetRandomSign(ctx->V));
    448:     if (contour->pA) PetscCall(BVScatter(ctx->V,ctx->pV,contour->scatterin,contour->xdup));
    449:     ctx->L += L_add;
    450:     PetscCall(EPSCISSSolve(eps,J,V,ctx->L-L_add,ctx->L));
    451:   }
    452:   PetscCall(PetscMalloc2(ctx->L*ctx->L*ctx->M*2,&Mu,ctx->L*ctx->M*ctx->L*ctx->M,&H0));
    453:   for (i=0;i<ctx->refine_blocksize;i++) {
    454:     PetscCall(BVDotQuadrature(ctx->Y,(contour->pA)?ctx->pV:ctx->V,Mu,ctx->M,ctx->L,ctx->L,ctx->weight,ctx->pp,contour->subcomm,contour->npoints,ctx->useconj));
    455:     PetscCall(CISS_BlockHankel(Mu,0,ctx->L,ctx->M,H0));
    456:     PetscCall(PetscLogEventBegin(EPS_CISS_SVD,eps,0,0,0));
    457:     PetscCall(SlepcCISS_BH_SVD(H0,ctx->L*ctx->M,ctx->delta,ctx->sigma,&nv));
    458:     PetscCall(PetscLogEventEnd(EPS_CISS_SVD,eps,0,0,0));
    459:     if (ctx->sigma[0]<=ctx->delta || nv < ctx->L*ctx->M || ctx->L == ctx->L_max) break;
    460:     L_add = L_base;
    461:     if (ctx->L+L_add>ctx->L_max) L_add = ctx->L_max-ctx->L;
    462:     PetscCall(PetscInfo(eps,"Changing L %" PetscInt_FMT " -> %" PetscInt_FMT " by SVD(H0)\n",ctx->L,ctx->L+L_add));
    463:     PetscCall(BVCISSResizeBases(ctx->S,contour->pA?ctx->pV:ctx->V,ctx->Y,ctx->L,ctx->L+L_add,ctx->M,contour->npoints));
    464:     PetscCall(BVSetActiveColumns(ctx->V,ctx->L,ctx->L+L_add));
    465:     PetscCall(BVSetRandomSign(ctx->V));
    466:     if (contour->pA) PetscCall(BVScatter(ctx->V,ctx->pV,contour->scatterin,contour->xdup));
    467:     ctx->L += L_add;
    468:     PetscCall(EPSCISSSolve(eps,J,V,ctx->L-L_add,ctx->L));
    469:     if (L_add) {
    470:       PetscCall(PetscFree2(Mu,H0));
    471:       PetscCall(PetscMalloc2(ctx->L*ctx->L*ctx->M*2,&Mu,ctx->L*ctx->M*ctx->L*ctx->M,&H0));
    472:     }
    473:   }
    474:   if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) PetscCall(PetscMalloc1(ctx->L*ctx->M*ctx->L*ctx->M,&H1));

    476:   while (eps->reason == EPS_CONVERGED_ITERATING) {
    477:     eps->its++;
    478:     for (inner=0;inner<=ctx->refine_inner;inner++) {
    479:       if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) {
    480:         PetscCall(BVDotQuadrature(ctx->Y,(contour->pA)?ctx->pV:ctx->V,Mu,ctx->M,ctx->L,ctx->L,ctx->weight,ctx->pp,contour->subcomm,contour->npoints,ctx->useconj));
    481:         PetscCall(CISS_BlockHankel(Mu,0,ctx->L,ctx->M,H0));
    482:         PetscCall(PetscLogEventBegin(EPS_CISS_SVD,eps,0,0,0));
    483:         PetscCall(SlepcCISS_BH_SVD(H0,ctx->L*ctx->M,ctx->delta,ctx->sigma,&nv));
    484:         PetscCall(PetscLogEventEnd(EPS_CISS_SVD,eps,0,0,0));
    485:         break;
    486:       } else {
    487:         PetscCall(BVSumQuadrature(ctx->S,ctx->Y,ctx->M,ctx->L,ctx->L,ctx->weight,ctx->pp,contour->scatterin,contour->subcomm,contour->npoints,ctx->useconj));
    488:         PetscCall(BVSetActiveColumns(ctx->S,0,ctx->L));
    489:         PetscCall(BVSetActiveColumns(ctx->V,0,ctx->L));
    490:         PetscCall(BVCopy(ctx->S,ctx->V));
    491:         PetscCall(BVSVDAndRank(ctx->S,ctx->M,ctx->L,ctx->delta,BV_SVD_METHOD_REFINE,H0,ctx->sigma,&nv));
    492:         if (ctx->sigma[0]>ctx->delta && nv==ctx->L*ctx->M && inner!=ctx->refine_inner) {
    493:           if (contour->pA) PetscCall(BVScatter(ctx->V,ctx->pV,contour->scatterin,contour->xdup));
    494:           PetscCall(EPSCISSSolve(eps,J,V,0,ctx->L));
    495:         } else break;
    496:       }
    497:     }
    498:     eps->nconv = 0;
    499:     if (nv == 0) eps->reason = EPS_CONVERGED_TOL;
    500:     else {
    501:       PetscCall(DSSetDimensions(eps->ds,nv,0,0));
    502:       PetscCall(DSSetState(eps->ds,DS_STATE_RAW));

    504:       if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) {
    505:         PetscCall(CISS_BlockHankel(Mu,0,ctx->L,ctx->M,H0));
    506:         PetscCall(CISS_BlockHankel(Mu,1,ctx->L,ctx->M,H1));
    507:         PetscCall(DSGetArray(eps->ds,DS_MAT_A,&temp));
    508:         for (j=0;j<nv;j++) {
    509:           for (i=0;i<nv;i++) {
    510:             temp[i+j*ld] = H1[i+j*ctx->L*ctx->M];
    511:           }
    512:         }
    513:         PetscCall(DSRestoreArray(eps->ds,DS_MAT_A,&temp));
    514:         PetscCall(DSGetArray(eps->ds,DS_MAT_B,&temp));
    515:         for (j=0;j<nv;j++) {
    516:           for (i=0;i<nv;i++) {
    517:             temp[i+j*ld] = H0[i+j*ctx->L*ctx->M];
    518:           }
    519:         }
    520:         PetscCall(DSRestoreArray(eps->ds,DS_MAT_B,&temp));
    521:       } else {
    522:         PetscCall(BVSetActiveColumns(ctx->S,0,nv));
    523:         PetscCall(DSGetMat(eps->ds,DS_MAT_A,&pA));
    524:         PetscCall(MatZeroEntries(pA));
    525:         PetscCall(BVMatProject(ctx->S,A,ctx->S,pA));
    526:         PetscCall(DSRestoreMat(eps->ds,DS_MAT_A,&pA));
    527:         if (B) {
    528:           PetscCall(DSGetMat(eps->ds,DS_MAT_B,&pB));
    529:           PetscCall(MatZeroEntries(pB));
    530:           PetscCall(BVMatProject(ctx->S,B,ctx->S,pB));
    531:           PetscCall(DSRestoreMat(eps->ds,DS_MAT_B,&pB));
    532:         }
    533:       }

    535:       PetscCall(DSSolve(eps->ds,eps->eigr,eps->eigi));
    536:       PetscCall(DSSynchronize(eps->ds,eps->eigr,eps->eigi));

    538:       PetscCall(PetscMalloc3(nv,&fl1,nv,&inside,nv,&rr));
    539:       PetscCall(rescale_eig(eps,nv));
    540:       PetscCall(DSVectors(eps->ds,DS_MAT_X,NULL,NULL));
    541:       PetscCall(DSGetMat(eps->ds,DS_MAT_X,&X));
    542:       PetscCall(SlepcCISS_isGhost(X,nv,ctx->sigma,ctx->spurious_threshold,fl1));
    543:       PetscCall(DSRestoreMat(eps->ds,DS_MAT_X,&X));
    544:       PetscCall(RGCheckInside(eps->rg,nv,eps->eigr,eps->eigi,inside));
    545:       for (i=0;i<nv;i++) {
    546:         if (fl1[i] && inside[i]>=0) {
    547:           rr[i] = 1.0;
    548:           eps->nconv++;
    549:         } else rr[i] = 0.0;
    550:       }
    551:       PetscCall(DSSort(eps->ds,eps->eigr,eps->eigi,rr,NULL,&eps->nconv));
    552:       PetscCall(DSSynchronize(eps->ds,eps->eigr,eps->eigi));
    553:       PetscCall(rescale_eig(eps,nv));
    554:       PetscCall(PetscFree3(fl1,inside,rr));
    555:       PetscCall(BVSetActiveColumns(eps->V,0,nv));
    556:       if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) {
    557:         PetscCall(BVSumQuadrature(ctx->S,ctx->Y,ctx->M,ctx->L,ctx->L,ctx->weight,ctx->pp,contour->scatterin,contour->subcomm,contour->npoints,ctx->useconj));
    558:         PetscCall(BVSetActiveColumns(ctx->S,0,ctx->L));
    559:         PetscCall(BVCopy(ctx->S,ctx->V));
    560:         PetscCall(BVSetActiveColumns(ctx->S,0,nv));
    561:       }
    562:       PetscCall(BVCopy(ctx->S,eps->V));

    564:       PetscCall(DSVectors(eps->ds,DS_MAT_X,NULL,NULL));
    565:       PetscCall(DSGetMat(eps->ds,DS_MAT_X,&X));
    566:       PetscCall(BVMultInPlace(ctx->S,X,0,eps->nconv));
    567:       if (eps->ishermitian) PetscCall(BVMultInPlace(eps->V,X,0,eps->nconv));
    568:       PetscCall(DSRestoreMat(eps->ds,DS_MAT_X,&X));
    569:       max_error = 0.0;
    570:       for (i=0;i<eps->nconv;i++) {
    571:         PetscCall(BVGetColumn(ctx->S,i,&si));
    572: #if !defined(PETSC_USE_COMPLEX)
    573:         if (eps->eigi[i]!=0.0) PetscCall(BVGetColumn(ctx->S,i+1,&si1));
    574: #endif
    575:         PetscCall(EPSComputeResidualNorm_Private(eps,PETSC_FALSE,eps->eigr[i],eps->eigi[i],si,si1,w,&error));
    576:         if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) {  /* vector is not normalized */
    577:           PetscCall(VecNorm(si,NORM_2,&norm));
    578: #if !defined(PETSC_USE_COMPLEX)
    579:           if (eps->eigi[i]!=0.0) {
    580:             PetscCall(VecNorm(si1,NORM_2,&normi));
    581:             norm = SlepcAbsEigenvalue(norm,normi);
    582:           }
    583: #endif
    584:           error /= norm;
    585:         }
    586:         PetscCall((*eps->converged)(eps,eps->eigr[i],eps->eigi[i],error,&error,eps->convergedctx));
    587:         PetscCall(BVRestoreColumn(ctx->S,i,&si));
    588: #if !defined(PETSC_USE_COMPLEX)
    589:         if (eps->eigi[i]!=0.0) {
    590:           PetscCall(BVRestoreColumn(ctx->S,i+1,&si1));
    591:           i++;
    592:         }
    593: #endif
    594:         max_error = PetscMax(max_error,error);
    595:       }

    597:       if (max_error <= eps->tol) eps->reason = EPS_CONVERGED_TOL;
    598:       else if (eps->its >= eps->max_it) eps->reason = EPS_DIVERGED_ITS;
    599:       else {
    600:         if (eps->nconv > ctx->L) nv = eps->nconv;
    601:         else if (ctx->L > nv) nv = ctx->L;
    602:         nv = PetscMin(nv,ctx->L*ctx->M);
    603:         PetscCall(MatCreateSeqDense(PETSC_COMM_SELF,nv,ctx->L,NULL,&M));
    604:         PetscCall(MatSetRandom(M,rand));
    605:         PetscCall(BVSetActiveColumns(ctx->S,0,nv));
    606:         PetscCall(BVMultInPlace(ctx->S,M,0,ctx->L));
    607:         PetscCall(MatDestroy(&M));
    608:         PetscCall(BVSetActiveColumns(ctx->S,0,ctx->L));
    609:         PetscCall(BVSetActiveColumns(ctx->V,0,ctx->L));
    610:         PetscCall(BVCopy(ctx->S,ctx->V));
    611:         if (contour->pA) PetscCall(BVScatter(ctx->V,ctx->pV,contour->scatterin,contour->xdup));
    612:         PetscCall(EPSCISSSolve(eps,J,V,0,ctx->L));
    613:       }
    614:     }
    615:   }
    616:   if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) PetscCall(PetscFree(H1));
    617:   PetscCall(PetscFree2(Mu,H0));
    618:   PetscFunctionReturn(PETSC_SUCCESS);
    619: }

    621: static PetscErrorCode EPSComputeVectors_CISS(EPS eps)
    622: {
    623:   EPS_CISS       *ctx = (EPS_CISS*)eps->data;
    624:   PetscInt       n;
    625:   Mat            Z,B=NULL;

    627:   PetscFunctionBegin;
    628:   if (eps->ishermitian) {
    629:     if (eps->isgeneralized && !eps->ispositive) PetscCall(EPSComputeVectors_Indefinite(eps));
    630:     else PetscCall(EPSComputeVectors_Hermitian(eps));
    631:     if (eps->isgeneralized && eps->ispositive && ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) {
    632:       /* normalize to have unit B-norm */
    633:       PetscCall(STGetMatrix(eps->st,1,&B));
    634:       PetscCall(BVSetMatrix(eps->V,B,PETSC_FALSE));
    635:       PetscCall(BVNormalize(eps->V,NULL));
    636:       PetscCall(BVSetMatrix(eps->V,NULL,PETSC_FALSE));
    637:     }
    638:     PetscFunctionReturn(PETSC_SUCCESS);
    639:   }
    640:   PetscCall(DSGetDimensions(eps->ds,&n,NULL,NULL,NULL));
    641:   PetscCall(BVSetActiveColumns(eps->V,0,n));

    643:   /* right eigenvectors */
    644:   PetscCall(DSVectors(eps->ds,DS_MAT_X,NULL,NULL));

    646:   /* V = V * Z */
    647:   PetscCall(DSGetMat(eps->ds,DS_MAT_X,&Z));
    648:   PetscCall(BVMultInPlace(eps->V,Z,0,n));
    649:   PetscCall(DSRestoreMat(eps->ds,DS_MAT_X,&Z));
    650:   PetscCall(BVSetActiveColumns(eps->V,0,eps->nconv));

    652:   /* normalize */
    653:   if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) PetscCall(BVNormalize(eps->V,NULL));
    654:   PetscFunctionReturn(PETSC_SUCCESS);
    655: }

    657: static PetscErrorCode EPSCISSSetSizes_CISS(EPS eps,PetscInt ip,PetscInt bs,PetscInt ms,PetscInt npart,PetscInt bsmax,PetscBool realmats)
    658: {
    659:   EPS_CISS       *ctx = (EPS_CISS*)eps->data;
    660:   PetscInt       oN,oL,oM,oLmax,onpart;
    661:   PetscMPIInt    size;

    663:   PetscFunctionBegin;
    664:   oN = ctx->N;
    665:   if (ip == PETSC_DECIDE || ip == PETSC_DEFAULT) {
    666:     if (ctx->N!=32) { ctx->N =32; ctx->M = ctx->N/4; }
    667:   } else {
    668:     PetscCheck(ip>0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The ip argument must be > 0");
    669:     PetscCheck(ip%2==0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The ip argument must be an even number");
    670:     if (ctx->N!=ip) { ctx->N = ip; ctx->M = ctx->N/4; }
    671:   }
    672:   oL = ctx->L;
    673:   if (bs == PETSC_DECIDE || bs == PETSC_DEFAULT) {
    674:     ctx->L = 16;
    675:   } else {
    676:     PetscCheck(bs>0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The bs argument must be > 0");
    677:     ctx->L = bs;
    678:   }
    679:   oM = ctx->M;
    680:   if (ms == PETSC_DECIDE || ms == PETSC_DEFAULT) {
    681:     ctx->M = ctx->N/4;
    682:   } else {
    683:     PetscCheck(ms>0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The ms argument must be > 0");
    684:     PetscCheck(ms<=ctx->N,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The ms argument must be less than or equal to the number of integration points");
    685:     ctx->M = ms;
    686:   }
    687:   onpart = ctx->npart;
    688:   if (npart == PETSC_DECIDE || npart == PETSC_DEFAULT) {
    689:     ctx->npart = 1;
    690:   } else {
    691:     PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)eps),&size));
    692:     PetscCheck(npart>0 && npart<=size,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"Illegal value of npart");
    693:     ctx->npart = npart;
    694:   }
    695:   oLmax = ctx->L_max;
    696:   if (bsmax == PETSC_DECIDE || bsmax == PETSC_DEFAULT) {
    697:     ctx->L_max = 64;
    698:   } else {
    699:     PetscCheck(bsmax>0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The bsmax argument must be > 0");
    700:     ctx->L_max = PetscMax(bsmax,ctx->L);
    701:   }
    702:   if (onpart != ctx->npart || oN != ctx->N || realmats != ctx->isreal) {
    703:     PetscCall(SlepcContourDataDestroy(&ctx->contour));
    704:     PetscCall(PetscInfo(eps,"Resetting the contour data structure due to a change of parameters\n"));
    705:     eps->state = EPS_STATE_INITIAL;
    706:   }
    707:   ctx->isreal = realmats;
    708:   if (oL != ctx->L || oM != ctx->M || oLmax != ctx->L_max) eps->state = EPS_STATE_INITIAL;
    709:   PetscFunctionReturn(PETSC_SUCCESS);
    710: }

    712: /*@
    713:    EPSCISSSetSizes - Sets the values of various size parameters in the CISS solver.

    715:    Logically Collective

    717:    Input Parameters:
    718: +  eps   - the eigenproblem solver context
    719: .  ip    - number of integration points
    720: .  bs    - block size
    721: .  ms    - moment size
    722: .  npart - number of partitions when splitting the communicator
    723: .  bsmax - max block size
    724: -  realmats - A and B are real

    726:    Options Database Keys:
    727: +  -eps_ciss_integration_points - Sets the number of integration points
    728: .  -eps_ciss_blocksize - Sets the block size
    729: .  -eps_ciss_moments - Sets the moment size
    730: .  -eps_ciss_partitions - Sets the number of partitions
    731: .  -eps_ciss_maxblocksize - Sets the maximum block size
    732: -  -eps_ciss_realmats - A and B are real

    734:    Note:
    735:    The default number of partitions is 1. This means the internal KSP object is shared
    736:    among all processes of the EPS communicator. Otherwise, the communicator is split
    737:    into npart communicators, so that npart KSP solves proceed simultaneously.

    739:    Level: advanced

    741: .seealso: EPSCISSGetSizes()
    742: @*/
    743: PetscErrorCode EPSCISSSetSizes(EPS eps,PetscInt ip,PetscInt bs,PetscInt ms,PetscInt npart,PetscInt bsmax,PetscBool realmats)
    744: {
    745:   PetscFunctionBegin;
    753:   PetscTryMethod(eps,"EPSCISSSetSizes_C",(EPS,PetscInt,PetscInt,PetscInt,PetscInt,PetscInt,PetscBool),(eps,ip,bs,ms,npart,bsmax,realmats));
    754:   PetscFunctionReturn(PETSC_SUCCESS);
    755: }

    757: static PetscErrorCode EPSCISSGetSizes_CISS(EPS eps,PetscInt *ip,PetscInt *bs,PetscInt *ms,PetscInt *npart,PetscInt *bsmax,PetscBool *realmats)
    758: {
    759:   EPS_CISS *ctx = (EPS_CISS*)eps->data;

    761:   PetscFunctionBegin;
    762:   if (ip) *ip = ctx->N;
    763:   if (bs) *bs = ctx->L;
    764:   if (ms) *ms = ctx->M;
    765:   if (npart) *npart = ctx->npart;
    766:   if (bsmax) *bsmax = ctx->L_max;
    767:   if (realmats) *realmats = ctx->isreal;
    768:   PetscFunctionReturn(PETSC_SUCCESS);
    769: }

    771: /*@
    772:    EPSCISSGetSizes - Gets the values of various size parameters in the CISS solver.

    774:    Not Collective

    776:    Input Parameter:
    777: .  eps - the eigenproblem solver context

    779:    Output Parameters:
    780: +  ip    - number of integration points
    781: .  bs    - block size
    782: .  ms    - moment size
    783: .  npart - number of partitions when splitting the communicator
    784: .  bsmax - max block size
    785: -  realmats - A and B are real

    787:    Level: advanced

    789: .seealso: EPSCISSSetSizes()
    790: @*/
    791: PetscErrorCode EPSCISSGetSizes(EPS eps,PetscInt *ip,PetscInt *bs,PetscInt *ms,PetscInt *npart,PetscInt *bsmax,PetscBool *realmats)
    792: {
    793:   PetscFunctionBegin;
    795:   PetscUseMethod(eps,"EPSCISSGetSizes_C",(EPS,PetscInt*,PetscInt*,PetscInt*,PetscInt*,PetscInt*,PetscBool*),(eps,ip,bs,ms,npart,bsmax,realmats));
    796:   PetscFunctionReturn(PETSC_SUCCESS);
    797: }

    799: static PetscErrorCode EPSCISSSetThreshold_CISS(EPS eps,PetscReal delta,PetscReal spur)
    800: {
    801:   EPS_CISS *ctx = (EPS_CISS*)eps->data;

    803:   PetscFunctionBegin;
    804:   if (delta == (PetscReal)PETSC_DEFAULT) {
    805:     ctx->delta = SLEPC_DEFAULT_TOL*1e-4;
    806:   } else {
    807:     PetscCheck(delta>0.0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The delta argument must be > 0.0");
    808:     ctx->delta = delta;
    809:   }
    810:   if (spur == (PetscReal)PETSC_DEFAULT) {
    811:     ctx->spurious_threshold = PetscSqrtReal(SLEPC_DEFAULT_TOL);
    812:   } else {
    813:     PetscCheck(spur>0.0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The spurious threshold argument must be > 0.0");
    814:     ctx->spurious_threshold = spur;
    815:   }
    816:   PetscFunctionReturn(PETSC_SUCCESS);
    817: }

    819: /*@
    820:    EPSCISSSetThreshold - Sets the values of various threshold parameters in
    821:    the CISS solver.

    823:    Logically Collective

    825:    Input Parameters:
    826: +  eps   - the eigenproblem solver context
    827: .  delta - threshold for numerical rank
    828: -  spur  - spurious threshold (to discard spurious eigenpairs)

    830:    Options Database Keys:
    831: +  -eps_ciss_delta - Sets the delta
    832: -  -eps_ciss_spurious_threshold - Sets the spurious threshold

    834:    Level: advanced

    836: .seealso: EPSCISSGetThreshold()
    837: @*/
    838: PetscErrorCode EPSCISSSetThreshold(EPS eps,PetscReal delta,PetscReal spur)
    839: {
    840:   PetscFunctionBegin;
    844:   PetscTryMethod(eps,"EPSCISSSetThreshold_C",(EPS,PetscReal,PetscReal),(eps,delta,spur));
    845:   PetscFunctionReturn(PETSC_SUCCESS);
    846: }

    848: static PetscErrorCode EPSCISSGetThreshold_CISS(EPS eps,PetscReal *delta,PetscReal *spur)
    849: {
    850:   EPS_CISS *ctx = (EPS_CISS*)eps->data;

    852:   PetscFunctionBegin;
    853:   if (delta) *delta = ctx->delta;
    854:   if (spur)  *spur = ctx->spurious_threshold;
    855:   PetscFunctionReturn(PETSC_SUCCESS);
    856: }

    858: /*@
    859:    EPSCISSGetThreshold - Gets the values of various threshold parameters
    860:    in the CISS solver.

    862:    Not Collective

    864:    Input Parameter:
    865: .  eps - the eigenproblem solver context

    867:    Output Parameters:
    868: +  delta - threshold for numerical rank
    869: -  spur  - spurious threshold (to discard spurious eigenpairs)

    871:    Level: advanced

    873: .seealso: EPSCISSSetThreshold()
    874: @*/
    875: PetscErrorCode EPSCISSGetThreshold(EPS eps,PetscReal *delta,PetscReal *spur)
    876: {
    877:   PetscFunctionBegin;
    879:   PetscUseMethod(eps,"EPSCISSGetThreshold_C",(EPS,PetscReal*,PetscReal*),(eps,delta,spur));
    880:   PetscFunctionReturn(PETSC_SUCCESS);
    881: }

    883: static PetscErrorCode EPSCISSSetRefinement_CISS(EPS eps,PetscInt inner,PetscInt blsize)
    884: {
    885:   EPS_CISS *ctx = (EPS_CISS*)eps->data;

    887:   PetscFunctionBegin;
    888:   if (inner == PETSC_DEFAULT) {
    889:     ctx->refine_inner = 0;
    890:   } else {
    891:     PetscCheck(inner>=0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The refine inner argument must be >= 0");
    892:     ctx->refine_inner = inner;
    893:   }
    894:   if (blsize == PETSC_DEFAULT) {
    895:     ctx->refine_blocksize = 0;
    896:   } else {
    897:     PetscCheck(blsize>=0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The refine blocksize argument must be >= 0");
    898:     ctx->refine_blocksize = blsize;
    899:   }
    900:   PetscFunctionReturn(PETSC_SUCCESS);
    901: }

    903: /*@
    904:    EPSCISSSetRefinement - Sets the values of various refinement parameters
    905:    in the CISS solver.

    907:    Logically Collective

    909:    Input Parameters:
    910: +  eps    - the eigenproblem solver context
    911: .  inner  - number of iterative refinement iterations (inner loop)
    912: -  blsize - number of iterative refinement iterations (blocksize loop)

    914:    Options Database Keys:
    915: +  -eps_ciss_refine_inner - Sets number of inner iterations
    916: -  -eps_ciss_refine_blocksize - Sets number of blocksize iterations

    918:    Level: advanced

    920: .seealso: EPSCISSGetRefinement()
    921: @*/
    922: PetscErrorCode EPSCISSSetRefinement(EPS eps,PetscInt inner,PetscInt blsize)
    923: {
    924:   PetscFunctionBegin;
    928:   PetscTryMethod(eps,"EPSCISSSetRefinement_C",(EPS,PetscInt,PetscInt),(eps,inner,blsize));
    929:   PetscFunctionReturn(PETSC_SUCCESS);
    930: }

    932: static PetscErrorCode EPSCISSGetRefinement_CISS(EPS eps,PetscInt *inner,PetscInt *blsize)
    933: {
    934:   EPS_CISS *ctx = (EPS_CISS*)eps->data;

    936:   PetscFunctionBegin;
    937:   if (inner)  *inner = ctx->refine_inner;
    938:   if (blsize) *blsize = ctx->refine_blocksize;
    939:   PetscFunctionReturn(PETSC_SUCCESS);
    940: }

    942: /*@
    943:    EPSCISSGetRefinement - Gets the values of various refinement parameters
    944:    in the CISS solver.

    946:    Not Collective

    948:    Input Parameter:
    949: .  eps - the eigenproblem solver context

    951:    Output Parameters:
    952: +  inner  - number of iterative refinement iterations (inner loop)
    953: -  blsize - number of iterative refinement iterations (blocksize loop)

    955:    Level: advanced

    957: .seealso: EPSCISSSetRefinement()
    958: @*/
    959: PetscErrorCode EPSCISSGetRefinement(EPS eps, PetscInt *inner, PetscInt *blsize)
    960: {
    961:   PetscFunctionBegin;
    963:   PetscUseMethod(eps,"EPSCISSGetRefinement_C",(EPS,PetscInt*,PetscInt*),(eps,inner,blsize));
    964:   PetscFunctionReturn(PETSC_SUCCESS);
    965: }

    967: static PetscErrorCode EPSCISSSetUseST_CISS(EPS eps,PetscBool usest)
    968: {
    969:   EPS_CISS *ctx = (EPS_CISS*)eps->data;

    971:   PetscFunctionBegin;
    972:   ctx->usest     = usest;
    973:   ctx->usest_set = PETSC_TRUE;
    974:   eps->state     = EPS_STATE_INITIAL;
    975:   PetscFunctionReturn(PETSC_SUCCESS);
    976: }

    978: /*@
    979:    EPSCISSSetUseST - Sets a flag indicating that the CISS solver will
    980:    use the ST object for the linear solves.

    982:    Logically Collective

    984:    Input Parameters:
    985: +  eps    - the eigenproblem solver context
    986: -  usest  - boolean flag to use the ST object or not

    988:    Options Database Keys:
    989: .  -eps_ciss_usest <bool> - whether the ST object will be used or not

    991:    Level: advanced

    993: .seealso: EPSCISSGetUseST()
    994: @*/
    995: PetscErrorCode EPSCISSSetUseST(EPS eps,PetscBool usest)
    996: {
    997:   PetscFunctionBegin;
    1000:   PetscTryMethod(eps,"EPSCISSSetUseST_C",(EPS,PetscBool),(eps,usest));
    1001:   PetscFunctionReturn(PETSC_SUCCESS);
    1002: }

    1004: static PetscErrorCode EPSCISSGetUseST_CISS(EPS eps,PetscBool *usest)
    1005: {
    1006:   EPS_CISS *ctx = (EPS_CISS*)eps->data;

    1008:   PetscFunctionBegin;
    1009:   *usest = ctx->usest;
    1010:   PetscFunctionReturn(PETSC_SUCCESS);
    1011: }

    1013: /*@
    1014:    EPSCISSGetUseST - Gets the flag for using the ST object
    1015:    in the CISS solver.

    1017:    Not Collective

    1019:    Input Parameter:
    1020: .  eps - the eigenproblem solver context

    1022:    Output Parameters:
    1023: .  usest - boolean flag indicating if the ST object is being used

    1025:    Level: advanced

    1027: .seealso: EPSCISSSetUseST()
    1028: @*/
    1029: PetscErrorCode EPSCISSGetUseST(EPS eps,PetscBool *usest)
    1030: {
    1031:   PetscFunctionBegin;
    1033:   PetscAssertPointer(usest,2);
    1034:   PetscUseMethod(eps,"EPSCISSGetUseST_C",(EPS,PetscBool*),(eps,usest));
    1035:   PetscFunctionReturn(PETSC_SUCCESS);
    1036: }

    1038: static PetscErrorCode EPSCISSSetQuadRule_CISS(EPS eps,EPSCISSQuadRule quad)
    1039: {
    1040:   EPS_CISS *ctx = (EPS_CISS*)eps->data;

    1042:   PetscFunctionBegin;
    1043:   if (ctx->quad != quad) {
    1044:     ctx->quad  = quad;
    1045:     eps->state = EPS_STATE_INITIAL;
    1046:   }
    1047:   PetscFunctionReturn(PETSC_SUCCESS);
    1048: }

    1050: /*@
    1051:    EPSCISSSetQuadRule - Sets the quadrature rule used in the CISS solver.

    1053:    Logically Collective

    1055:    Input Parameters:
    1056: +  eps  - the eigenproblem solver context
    1057: -  quad - the quadrature rule

    1059:    Options Database Key:
    1060: .  -eps_ciss_quadrule - Sets the quadrature rule (either 'trapezoidal' or
    1061:                            'chebyshev')

    1063:    Notes:
    1064:    By default, the trapezoidal rule is used (EPS_CISS_QUADRULE_TRAPEZOIDAL).

    1066:    If the 'chebyshev' option is specified (EPS_CISS_QUADRULE_CHEBYSHEV), then
    1067:    Chebyshev points are used as quadrature points.

    1069:    Level: advanced

    1071: .seealso: EPSCISSGetQuadRule(), EPSCISSQuadRule
    1072: @*/
    1073: PetscErrorCode EPSCISSSetQuadRule(EPS eps,EPSCISSQuadRule quad)
    1074: {
    1075:   PetscFunctionBegin;
    1078:   PetscTryMethod(eps,"EPSCISSSetQuadRule_C",(EPS,EPSCISSQuadRule),(eps,quad));
    1079:   PetscFunctionReturn(PETSC_SUCCESS);
    1080: }

    1082: static PetscErrorCode EPSCISSGetQuadRule_CISS(EPS eps,EPSCISSQuadRule *quad)
    1083: {
    1084:   EPS_CISS *ctx = (EPS_CISS*)eps->data;

    1086:   PetscFunctionBegin;
    1087:   *quad = ctx->quad;
    1088:   PetscFunctionReturn(PETSC_SUCCESS);
    1089: }

    1091: /*@
    1092:    EPSCISSGetQuadRule - Gets the quadrature rule used in the CISS solver.

    1094:    Not Collective

    1096:    Input Parameter:
    1097: .  eps - the eigenproblem solver context

    1099:    Output Parameters:
    1100: .  quad - quadrature rule

    1102:    Level: advanced

    1104: .seealso: EPSCISSSetQuadRule() EPSCISSQuadRule
    1105: @*/
    1106: PetscErrorCode EPSCISSGetQuadRule(EPS eps,EPSCISSQuadRule *quad)
    1107: {
    1108:   PetscFunctionBegin;
    1110:   PetscAssertPointer(quad,2);
    1111:   PetscUseMethod(eps,"EPSCISSGetQuadRule_C",(EPS,EPSCISSQuadRule*),(eps,quad));
    1112:   PetscFunctionReturn(PETSC_SUCCESS);
    1113: }

    1115: static PetscErrorCode EPSCISSSetExtraction_CISS(EPS eps,EPSCISSExtraction extraction)
    1116: {
    1117:   EPS_CISS *ctx = (EPS_CISS*)eps->data;

    1119:   PetscFunctionBegin;
    1120:   if (ctx->extraction != extraction) {
    1121:     ctx->extraction = extraction;
    1122:     eps->state      = EPS_STATE_INITIAL;
    1123:   }
    1124:   PetscFunctionReturn(PETSC_SUCCESS);
    1125: }

    1127: /*@
    1128:    EPSCISSSetExtraction - Sets the extraction technique used in the CISS solver.

    1130:    Logically Collective

    1132:    Input Parameters:
    1133: +  eps        - the eigenproblem solver context
    1134: -  extraction - the extraction technique

    1136:    Options Database Key:
    1137: .  -eps_ciss_extraction - Sets the extraction technique (either 'ritz' or
    1138:                            'hankel')

    1140:    Notes:
    1141:    By default, the Rayleigh-Ritz extraction is used (EPS_CISS_EXTRACTION_RITZ).

    1143:    If the 'hankel' option is specified (EPS_CISS_EXTRACTION_HANKEL), then
    1144:    the Block Hankel method is used for extracting eigenpairs.

    1146:    Level: advanced

    1148: .seealso: EPSCISSGetExtraction(), EPSCISSExtraction
    1149: @*/
    1150: PetscErrorCode EPSCISSSetExtraction(EPS eps,EPSCISSExtraction extraction)
    1151: {
    1152:   PetscFunctionBegin;
    1155:   PetscTryMethod(eps,"EPSCISSSetExtraction_C",(EPS,EPSCISSExtraction),(eps,extraction));
    1156:   PetscFunctionReturn(PETSC_SUCCESS);
    1157: }

    1159: static PetscErrorCode EPSCISSGetExtraction_CISS(EPS eps,EPSCISSExtraction *extraction)
    1160: {
    1161:   EPS_CISS *ctx = (EPS_CISS*)eps->data;

    1163:   PetscFunctionBegin;
    1164:   *extraction = ctx->extraction;
    1165:   PetscFunctionReturn(PETSC_SUCCESS);
    1166: }

    1168: /*@
    1169:    EPSCISSGetExtraction - Gets the extraction technique used in the CISS solver.

    1171:    Not Collective

    1173:    Input Parameter:
    1174: .  eps - the eigenproblem solver context

    1176:    Output Parameters:
    1177: .  extraction - extraction technique

    1179:    Level: advanced

    1181: .seealso: EPSCISSSetExtraction() EPSCISSExtraction
    1182: @*/
    1183: PetscErrorCode EPSCISSGetExtraction(EPS eps,EPSCISSExtraction *extraction)
    1184: {
    1185:   PetscFunctionBegin;
    1187:   PetscAssertPointer(extraction,2);
    1188:   PetscUseMethod(eps,"EPSCISSGetExtraction_C",(EPS,EPSCISSExtraction*),(eps,extraction));
    1189:   PetscFunctionReturn(PETSC_SUCCESS);
    1190: }

    1192: static PetscErrorCode EPSCISSGetKSPs_CISS(EPS eps,PetscInt *nsolve,KSP **ksp)
    1193: {
    1194:   EPS_CISS         *ctx = (EPS_CISS*)eps->data;
    1195:   SlepcContourData contour;
    1196:   PetscInt         i,nsplit;
    1197:   PC               pc;
    1198:   MPI_Comm         child;

    1200:   PetscFunctionBegin;
    1201:   if (!ctx->contour) {  /* initialize contour data structure first */
    1202:     PetscCall(RGCanUseConjugates(eps->rg,ctx->isreal,&ctx->useconj));
    1203:     PetscCall(SlepcContourDataCreate(ctx->useconj?ctx->N/2:ctx->N,ctx->npart,(PetscObject)eps,&ctx->contour));
    1204:   }
    1205:   contour = ctx->contour;
    1206:   if (!contour->ksp) {
    1207:     PetscCall(PetscMalloc1(contour->npoints,&contour->ksp));
    1208:     PetscCall(EPSGetST(eps,&eps->st));
    1209:     PetscCall(STGetSplitPreconditionerInfo(eps->st,&nsplit,NULL));
    1210:     PetscCall(PetscSubcommGetChild(contour->subcomm,&child));
    1211:     for (i=0;i<contour->npoints;i++) {
    1212:       PetscCall(KSPCreate(child,&contour->ksp[i]));
    1213:       PetscCall(PetscObjectIncrementTabLevel((PetscObject)contour->ksp[i],(PetscObject)eps,1));
    1214:       PetscCall(KSPSetOptionsPrefix(contour->ksp[i],((PetscObject)eps)->prefix));
    1215:       PetscCall(KSPAppendOptionsPrefix(contour->ksp[i],"eps_ciss_"));
    1216:       PetscCall(PetscObjectSetOptions((PetscObject)contour->ksp[i],((PetscObject)eps)->options));
    1217:       PetscCall(KSPSetErrorIfNotConverged(contour->ksp[i],PETSC_TRUE));
    1218:       PetscCall(KSPSetTolerances(contour->ksp[i],SlepcDefaultTol(eps->tol),PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT));
    1219:       PetscCall(KSPGetPC(contour->ksp[i],&pc));
    1220:       if (nsplit) {
    1221:         PetscCall(KSPSetType(contour->ksp[i],KSPBCGS));
    1222:         PetscCall(PCSetType(pc,PCBJACOBI));
    1223:       } else {
    1224:         PetscCall(KSPSetType(contour->ksp[i],KSPPREONLY));
    1225:         PetscCall(PCSetType(pc,PCLU));
    1226:       }
    1227:     }
    1228:   }
    1229:   if (nsolve) *nsolve = contour->npoints;
    1230:   if (ksp)    *ksp    = contour->ksp;
    1231:   PetscFunctionReturn(PETSC_SUCCESS);
    1232: }

    1234: /*@C
    1235:    EPSCISSGetKSPs - Retrieve the array of linear solver objects associated with
    1236:    the CISS solver.

    1238:    Not Collective

    1240:    Input Parameter:
    1241: .  eps - the eigenproblem solver solver

    1243:    Output Parameters:
    1244: +  nsolve - number of solver objects
    1245: -  ksp - array of linear solver object

    1247:    Notes:
    1248:    The number of KSP solvers is equal to the number of integration points divided by
    1249:    the number of partitions. This value is halved in the case of real matrices with
    1250:    a region centered at the real axis.

    1252:    Level: advanced

    1254: .seealso: EPSCISSSetSizes()
    1255: @*/
    1256: PetscErrorCode EPSCISSGetKSPs(EPS eps,PetscInt *nsolve,KSP **ksp)
    1257: {
    1258:   PetscFunctionBegin;
    1260:   PetscUseMethod(eps,"EPSCISSGetKSPs_C",(EPS,PetscInt*,KSP**),(eps,nsolve,ksp));
    1261:   PetscFunctionReturn(PETSC_SUCCESS);
    1262: }

    1264: static PetscErrorCode EPSReset_CISS(EPS eps)
    1265: {
    1266:   EPS_CISS       *ctx = (EPS_CISS*)eps->data;

    1268:   PetscFunctionBegin;
    1269:   PetscCall(BVDestroy(&ctx->S));
    1270:   PetscCall(BVDestroy(&ctx->V));
    1271:   PetscCall(BVDestroy(&ctx->Y));
    1272:   if (!ctx->usest) PetscCall(SlepcContourDataReset(ctx->contour));
    1273:   PetscCall(BVDestroy(&ctx->pV));
    1274:   PetscFunctionReturn(PETSC_SUCCESS);
    1275: }

    1277: static PetscErrorCode EPSSetFromOptions_CISS(EPS eps,PetscOptionItems *PetscOptionsObject)
    1278: {
    1279:   PetscReal         r3,r4;
    1280:   PetscInt          i,i1,i2,i3,i4,i5,i6,i7;
    1281:   PetscBool         b1,b2,flg,flg2,flg3,flg4,flg5,flg6;
    1282:   EPS_CISS          *ctx = (EPS_CISS*)eps->data;
    1283:   EPSCISSQuadRule   quad;
    1284:   EPSCISSExtraction extraction;

    1286:   PetscFunctionBegin;
    1287:   PetscOptionsHeadBegin(PetscOptionsObject,"EPS CISS Options");

    1289:     PetscCall(EPSCISSGetSizes(eps,&i1,&i2,&i3,&i4,&i5,&b1));
    1290:     PetscCall(PetscOptionsInt("-eps_ciss_integration_points","Number of integration points","EPSCISSSetSizes",i1,&i1,&flg));
    1291:     PetscCall(PetscOptionsInt("-eps_ciss_blocksize","Block size","EPSCISSSetSizes",i2,&i2,&flg2));
    1292:     PetscCall(PetscOptionsInt("-eps_ciss_moments","Moment size","EPSCISSSetSizes",i3,&i3,&flg3));
    1293:     PetscCall(PetscOptionsInt("-eps_ciss_partitions","Number of partitions","EPSCISSSetSizes",i4,&i4,&flg4));
    1294:     PetscCall(PetscOptionsInt("-eps_ciss_maxblocksize","Maximum block size","EPSCISSSetSizes",i5,&i5,&flg5));
    1295:     PetscCall(PetscOptionsBool("-eps_ciss_realmats","True if A and B are real","EPSCISSSetSizes",b1,&b1,&flg6));
    1296:     if (flg || flg2 || flg3 || flg4 || flg5 || flg6) PetscCall(EPSCISSSetSizes(eps,i1,i2,i3,i4,i5,b1));

    1298:     PetscCall(EPSCISSGetThreshold(eps,&r3,&r4));
    1299:     PetscCall(PetscOptionsReal("-eps_ciss_delta","Threshold for numerical rank","EPSCISSSetThreshold",r3,&r3,&flg));
    1300:     PetscCall(PetscOptionsReal("-eps_ciss_spurious_threshold","Threshold for the spurious eigenpairs","EPSCISSSetThreshold",r4,&r4,&flg2));
    1301:     if (flg || flg2) PetscCall(EPSCISSSetThreshold(eps,r3,r4));

    1303:     PetscCall(EPSCISSGetRefinement(eps,&i6,&i7));
    1304:     PetscCall(PetscOptionsInt("-eps_ciss_refine_inner","Number of inner iterative refinement iterations","EPSCISSSetRefinement",i6,&i6,&flg));
    1305:     PetscCall(PetscOptionsInt("-eps_ciss_refine_blocksize","Number of blocksize iterative refinement iterations","EPSCISSSetRefinement",i7,&i7,&flg2));
    1306:     if (flg || flg2) PetscCall(EPSCISSSetRefinement(eps,i6,i7));

    1308:     PetscCall(EPSCISSGetUseST(eps,&b2));
    1309:     PetscCall(PetscOptionsBool("-eps_ciss_usest","Use ST for linear solves","EPSCISSSetUseST",b2,&b2,&flg));
    1310:     if (flg) PetscCall(EPSCISSSetUseST(eps,b2));

    1312:     PetscCall(PetscOptionsEnum("-eps_ciss_quadrule","Quadrature rule","EPSCISSSetQuadRule",EPSCISSQuadRules,(PetscEnum)ctx->quad,(PetscEnum*)&quad,&flg));
    1313:     if (flg) PetscCall(EPSCISSSetQuadRule(eps,quad));

    1315:     PetscCall(PetscOptionsEnum("-eps_ciss_extraction","Extraction technique","EPSCISSSetExtraction",EPSCISSExtractions,(PetscEnum)ctx->extraction,(PetscEnum*)&extraction,&flg));
    1316:     if (flg) PetscCall(EPSCISSSetExtraction(eps,extraction));

    1318:   PetscOptionsHeadEnd();

    1320:   if (!eps->rg) PetscCall(EPSGetRG(eps,&eps->rg));
    1321:   PetscCall(RGSetFromOptions(eps->rg)); /* this is necessary here to set useconj */
    1322:   if (!ctx->contour || !ctx->contour->ksp) PetscCall(EPSCISSGetKSPs(eps,NULL,NULL));
    1323:   PetscAssert(ctx->contour && ctx->contour->ksp,PetscObjectComm((PetscObject)eps),PETSC_ERR_PLIB,"Something went wrong with EPSCISSGetKSPs()");
    1324:   for (i=0;i<ctx->contour->npoints;i++) PetscCall(KSPSetFromOptions(ctx->contour->ksp[i]));
    1325:   PetscCall(PetscSubcommSetFromOptions(ctx->contour->subcomm));
    1326:   PetscFunctionReturn(PETSC_SUCCESS);
    1327: }

    1329: static PetscErrorCode EPSDestroy_CISS(EPS eps)
    1330: {
    1331:   EPS_CISS       *ctx = (EPS_CISS*)eps->data;

    1333:   PetscFunctionBegin;
    1334:   PetscCall(SlepcContourDataDestroy(&ctx->contour));
    1335:   PetscCall(PetscFree4(ctx->weight,ctx->omega,ctx->pp,ctx->sigma));
    1336:   PetscCall(PetscFree(eps->data));
    1337:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetSizes_C",NULL));
    1338:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetSizes_C",NULL));
    1339:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetThreshold_C",NULL));
    1340:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetThreshold_C",NULL));
    1341:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetRefinement_C",NULL));
    1342:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetRefinement_C",NULL));
    1343:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetUseST_C",NULL));
    1344:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetUseST_C",NULL));
    1345:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetQuadRule_C",NULL));
    1346:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetQuadRule_C",NULL));
    1347:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetExtraction_C",NULL));
    1348:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetExtraction_C",NULL));
    1349:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetKSPs_C",NULL));
    1350:   PetscFunctionReturn(PETSC_SUCCESS);
    1351: }

    1353: static PetscErrorCode EPSView_CISS(EPS eps,PetscViewer viewer)
    1354: {
    1355:   EPS_CISS       *ctx = (EPS_CISS*)eps->data;
    1356:   PetscBool      isascii;
    1357:   PetscViewer    sviewer;

    1359:   PetscFunctionBegin;
    1360:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isascii));
    1361:   if (isascii) {
    1362:     PetscCall(PetscViewerASCIIPrintf(viewer,"  sizes { integration points: %" PetscInt_FMT ", block size: %" PetscInt_FMT ", moment size: %" PetscInt_FMT ", partitions: %" PetscInt_FMT ", maximum block size: %" PetscInt_FMT " }\n",ctx->N,ctx->L,ctx->M,ctx->npart,ctx->L_max));
    1363:     if (ctx->isreal) PetscCall(PetscViewerASCIIPrintf(viewer,"  exploiting symmetry of integration points\n"));
    1364:     PetscCall(PetscViewerASCIIPrintf(viewer,"  threshold { delta: %g, spurious threshold: %g }\n",(double)ctx->delta,(double)ctx->spurious_threshold));
    1365:     PetscCall(PetscViewerASCIIPrintf(viewer,"  iterative refinement { inner: %" PetscInt_FMT ", blocksize: %" PetscInt_FMT " }\n",ctx->refine_inner, ctx->refine_blocksize));
    1366:     PetscCall(PetscViewerASCIIPrintf(viewer,"  extraction: %s\n",EPSCISSExtractions[ctx->extraction]));
    1367:     PetscCall(PetscViewerASCIIPrintf(viewer,"  quadrature rule: %s\n",EPSCISSQuadRules[ctx->quad]));
    1368:     if (ctx->usest) PetscCall(PetscViewerASCIIPrintf(viewer,"  using ST for linear solves\n"));
    1369:     else {
    1370:       if (!ctx->contour || !ctx->contour->ksp) PetscCall(EPSCISSGetKSPs(eps,NULL,NULL));
    1371:       PetscAssert(ctx->contour && ctx->contour->ksp,PetscObjectComm((PetscObject)eps),PETSC_ERR_PLIB,"Something went wrong with EPSCISSGetKSPs()");
    1372:       PetscCall(PetscViewerASCIIPushTab(viewer));
    1373:       if (ctx->npart>1 && ctx->contour->subcomm) {
    1374:         PetscCall(PetscViewerGetSubViewer(viewer,ctx->contour->subcomm->child,&sviewer));
    1375:         if (!ctx->contour->subcomm->color) PetscCall(KSPView(ctx->contour->ksp[0],sviewer));
    1376:         PetscCall(PetscViewerFlush(sviewer));
    1377:         PetscCall(PetscViewerRestoreSubViewer(viewer,ctx->contour->subcomm->child,&sviewer));
    1378:         /* extra call needed because of the two calls to PetscViewerASCIIPushSynchronized() in PetscViewerGetSubViewer() */
    1379:         PetscCall(PetscViewerASCIIPopSynchronized(viewer));
    1380:       } else PetscCall(KSPView(ctx->contour->ksp[0],viewer));
    1381:       PetscCall(PetscViewerASCIIPopTab(viewer));
    1382:     }
    1383:   }
    1384:   PetscFunctionReturn(PETSC_SUCCESS);
    1385: }

    1387: static PetscErrorCode EPSSetDefaultST_CISS(EPS eps)
    1388: {
    1389:   EPS_CISS       *ctx = (EPS_CISS*)eps->data;
    1390:   PetscBool      usest = ctx->usest;
    1391:   KSP            ksp;
    1392:   PC             pc;

    1394:   PetscFunctionBegin;
    1395:   if (!((PetscObject)eps->st)->type_name) {
    1396:     if (!ctx->usest_set) usest = (ctx->npart>1)? PETSC_FALSE: PETSC_TRUE;
    1397:     if (usest) PetscCall(STSetType(eps->st,STSINVERT));
    1398:     else {
    1399:       /* we are not going to use ST, so avoid factorizing the matrix */
    1400:       PetscCall(STSetType(eps->st,STSHIFT));
    1401:       if (eps->isgeneralized) {
    1402:         PetscCall(STGetKSP(eps->st,&ksp));
    1403:         PetscCall(KSPGetPC(ksp,&pc));
    1404:         PetscCall(PCSetType(pc,PCNONE));
    1405:       }
    1406:     }
    1407:   }
    1408:   PetscFunctionReturn(PETSC_SUCCESS);
    1409: }

    1411: SLEPC_EXTERN PetscErrorCode EPSCreate_CISS(EPS eps)
    1412: {
    1413:   EPS_CISS       *ctx = (EPS_CISS*)eps->data;

    1415:   PetscFunctionBegin;
    1416:   PetscCall(PetscNew(&ctx));
    1417:   eps->data = ctx;

    1419:   eps->useds = PETSC_TRUE;
    1420:   eps->categ = EPS_CATEGORY_CONTOUR;

    1422:   eps->ops->solve          = EPSSolve_CISS;
    1423:   eps->ops->setup          = EPSSetUp_CISS;
    1424:   eps->ops->setupsort      = EPSSetUpSort_CISS;
    1425:   eps->ops->setfromoptions = EPSSetFromOptions_CISS;
    1426:   eps->ops->destroy        = EPSDestroy_CISS;
    1427:   eps->ops->reset          = EPSReset_CISS;
    1428:   eps->ops->view           = EPSView_CISS;
    1429:   eps->ops->computevectors = EPSComputeVectors_CISS;
    1430:   eps->ops->setdefaultst   = EPSSetDefaultST_CISS;

    1432:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetSizes_C",EPSCISSSetSizes_CISS));
    1433:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetSizes_C",EPSCISSGetSizes_CISS));
    1434:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetThreshold_C",EPSCISSSetThreshold_CISS));
    1435:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetThreshold_C",EPSCISSGetThreshold_CISS));
    1436:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetRefinement_C",EPSCISSSetRefinement_CISS));
    1437:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetRefinement_C",EPSCISSGetRefinement_CISS));
    1438:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetUseST_C",EPSCISSSetUseST_CISS));
    1439:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetUseST_C",EPSCISSGetUseST_CISS));
    1440:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetQuadRule_C",EPSCISSSetQuadRule_CISS));
    1441:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetQuadRule_C",EPSCISSGetQuadRule_CISS));
    1442:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetExtraction_C",EPSCISSSetExtraction_CISS));
    1443:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetExtraction_C",EPSCISSGetExtraction_CISS));
    1444:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetKSPs_C",EPSCISSGetKSPs_CISS));

    1446:   /* set default values of parameters */
    1447:   ctx->N                  = 32;
    1448:   ctx->L                  = 16;
    1449:   ctx->M                  = ctx->N/4;
    1450:   ctx->delta              = SLEPC_DEFAULT_TOL*1e-4;
    1451:   ctx->L_max              = 64;
    1452:   ctx->spurious_threshold = PetscSqrtReal(SLEPC_DEFAULT_TOL);
    1453:   ctx->usest              = PETSC_TRUE;
    1454:   ctx->usest_set          = PETSC_FALSE;
    1455:   ctx->isreal             = PETSC_FALSE;
    1456:   ctx->refine_inner       = 0;
    1457:   ctx->refine_blocksize   = 0;
    1458:   ctx->npart              = 1;
    1459:   ctx->quad               = (EPSCISSQuadRule)0;
    1460:   ctx->extraction         = EPS_CISS_EXTRACTION_RITZ;
    1461:   PetscFunctionReturn(PETSC_SUCCESS);
    1462: }