Actual source code: ciss.c

      1: /*
      2:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      3:    SLEPc - Scalable Library for Eigenvalue Problem Computations
      4:    Copyright (c) 2002-, Universitat Politecnica de Valencia, Spain

      6:    This file is part of SLEPc.
      7:    SLEPc is distributed under a 2-clause BSD license (see LICENSE).
      8:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      9: */
     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] = ((eps->eigr[i]+1.0)*(b-a)/2.0+a)*rgscale;
    182:           if (a==b) {
    183: #if defined(PETSC_USE_COMPLEX)
    184:             eps->eigr[i] = ((eps->eigr[i]+1.0)*(d-c)/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:   EPSCheckNotStructured(eps);
    227:   if (eps->ncv==PETSC_DETERMINE) {
    228:     if (eps->nev==0) eps->nev = 1;
    229:     eps->ncv = ctx->L_max*ctx->M;
    230:     if (eps->ncv>eps->n) {
    231:       eps->ncv = eps->n;
    232:       ctx->L_max = eps->ncv/ctx->M;
    233:       PetscCheck(ctx->L_max,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"Cannot adjust solver parameters, try setting a smaller value of M (moment size)");
    234:     }
    235:   } else {
    236:     PetscCall(EPSSetDimensions_Default(eps,&eps->nev,&eps->ncv,&eps->mpd));
    237:     ctx->L_max = eps->ncv/ctx->M;
    238:     if (!ctx->L_max) {
    239:       ctx->L_max = 1;
    240:       eps->ncv = ctx->L_max*ctx->M;
    241:     }
    242:   }
    243:   ctx->L = PetscMin(ctx->L,ctx->L_max);
    244:   if (eps->max_it==PETSC_DETERMINE) eps->max_it = 5;
    245:   if (eps->mpd==PETSC_DETERMINE) eps->mpd = eps->ncv;
    246:   if (!eps->which) eps->which = EPS_ALL;
    247:   PetscCheck(eps->which==EPS_ALL,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"This solver supports only computing all eigenvalues");
    248:   EPSCheckUnsupported(eps,EPS_FEATURE_BALANCE | EPS_FEATURE_ARBITRARY | EPS_FEATURE_EXTRACTION | EPS_FEATURE_STOPPING | EPS_FEATURE_TWOSIDED);

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

    260:   /* if the region has changed, then reset contour data */
    261:   PetscCall(PetscObjectGetId((PetscObject)eps->rg,&id));
    262:   PetscCall(PetscObjectStateGet((PetscObject)eps->rg,&state));
    263:   if (ctx->rgid && (id != ctx->rgid || state != ctx->rgstate)) {
    264:     PetscCall(SlepcContourDataDestroy(&ctx->contour));
    265:     PetscCall(PetscInfo(eps,"Resetting the contour data structure due to a change of region\n"));
    266:     ctx->rgid = id; ctx->rgstate = state;
    267:   }

    269: #if !defined(PETSC_USE_COMPLEX)
    270:   PetscCheck(!isring,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"Ring region only supported for complex scalars");
    271: #endif
    272:   if (isinterval) {
    273:     PetscCall(RGIntervalGetEndpoints(eps->rg,NULL,NULL,&c,&d));
    274: #if !defined(PETSC_USE_COMPLEX)
    275:     PetscCheck(c==d && c==0.0,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"In real scalars, endpoints of the imaginary axis must be both zero");
    276: #endif
    277:     if (!ctx->quad && c==d) ctx->quad = EPS_CISS_QUADRULE_CHEBYSHEV;
    278:   }
    279:   if (!ctx->quad) ctx->quad = EPS_CISS_QUADRULE_TRAPEZOIDAL;

    281:   /* create contour data structure */
    282:   if (!ctx->contour) {
    283:     PetscCall(RGCanUseConjugates(eps->rg,ctx->isreal,&ctx->useconj));
    284:     PetscCall(SlepcContourDataCreate(ctx->useconj?ctx->N/2:ctx->N,ctx->npart,(PetscObject)eps,&ctx->contour));
    285:   }

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

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

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

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

    306:   /* check if a user-defined split preconditioner has been set */
    307:   PetscCall(STGetSplitPreconditionerInfo(eps->st,&nsplit,NULL));
    308:   if (nsplit) {
    309:     PetscCall(STGetSplitPreconditionerTerm(eps->st,0,&Psplit[0]));
    310:     if (eps->isgeneralized) PetscCall(STGetSplitPreconditionerTerm(eps->st,1,&Psplit[1]));
    311:   }

    313:   contour = ctx->contour;
    314:   PetscCall(SlepcContourRedundantMat(contour,eps->isgeneralized?2:1,A,nsplit?Psplit:NULL));
    315:   if (contour->pA) {
    316:     PetscCall(BVGetColumn(ctx->V,0,&v0));
    317:     PetscCall(SlepcContourScatterCreate(contour,v0));
    318:     PetscCall(BVRestoreColumn(ctx->V,0,&v0));
    319:     PetscCall(BVDestroy(&ctx->pV));
    320:     PetscCall(BVCreate(PetscObjectComm((PetscObject)contour->xsub),&ctx->pV));
    321:     PetscCall(BVSetSizesFromVec(ctx->pV,contour->xsub,eps->n));
    322:     PetscCall(BVSetFromOptions(ctx->pV));
    323:     PetscCall(BVResize(ctx->pV,ctx->L,PETSC_FALSE));
    324:   }

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

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

    337:   if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) PetscCall(DSSetType(eps->ds,DSGNHEP));
    338:   else if (eps->isgeneralized) {
    339:     if (eps->ishermitian && eps->ispositive) PetscCall(DSSetType(eps->ds,DSGHEP));
    340:     else PetscCall(DSSetType(eps->ds,DSGNHEP));
    341:   } else {
    342:     if (eps->ishermitian) PetscCall(DSSetType(eps->ds,DSHEP));
    343:     else PetscCall(DSSetType(eps->ds,DSNHEP));
    344:   }
    345:   PetscCall(DSAllocate(eps->ds,eps->ncv));

    347: #if !defined(PETSC_USE_COMPLEX)
    348:   PetscCall(EPSSetWorkVecs(eps,3));
    349:   if (!eps->ishermitian) PetscCall(PetscInfo(eps,"Warning: complex eigenvalues are not calculated exactly without --with-scalar-type=complex in PETSc\n"));
    350: #else
    351:   PetscCall(EPSSetWorkVecs(eps,2));
    352: #endif
    353:   PetscFunctionReturn(PETSC_SUCCESS);
    354: }

    356: static PetscErrorCode EPSSetUpSort_CISS(EPS eps)
    357: {
    358:   SlepcSC        sc;

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

    367:   /* fill sorting criterion for DS */
    368:   PetscCall(DSGetSlepcSC(eps->ds,&sc));
    369:   sc->comparison    = SlepcCompareLargestMagnitude;
    370:   sc->comparisonctx = NULL;
    371:   sc->map           = NULL;
    372:   sc->mapobj        = NULL;
    373:   PetscFunctionReturn(PETSC_SUCCESS);
    374: }

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

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

    430:   if (contour->pA) PetscCall(BVScatter(ctx->V,ctx->pV,contour->scatterin,contour->xdup));
    431:   PetscCall(EPSCISSSolve(eps,J,V,0,ctx->L));
    432: #if defined(PETSC_USE_COMPLEX)
    433:   PetscCall(PetscObjectTypeCompare((PetscObject)eps->rg,RGELLIPSE,&isellipse));
    434:   if (isellipse) {
    435:     PetscCall(BVTraceQuadrature(ctx->Y,ctx->V,ctx->L,ctx->L,ctx->weight,contour->scatterin,contour->subcomm,contour->npoints,ctx->useconj,&est_eig));
    436:     PetscCall(PetscInfo(eps,"Estimated eigenvalue count: %f\n",(double)est_eig));
    437:     eta = PetscPowReal(10.0,-PetscLog10Real(eps->tol)/ctx->N);
    438:     L_add = PetscMax(0,(PetscInt)PetscCeilReal((est_eig*eta)/ctx->M)-ctx->L);
    439:     if (L_add>ctx->L_max-ctx->L) {
    440:       PetscCall(PetscInfo(eps,"Number of eigenvalues inside the contour path may be too large\n"));
    441:       L_add = ctx->L_max-ctx->L;
    442:     }
    443:   }
    444: #endif
    445:   if (L_add>0) {
    446:     PetscCall(PetscInfo(eps,"Changing L %" PetscInt_FMT " -> %" PetscInt_FMT " by Estimate #Eig\n",ctx->L,ctx->L+L_add));
    447:     PetscCall(BVCISSResizeBases(ctx->S,contour->pA?ctx->pV:ctx->V,ctx->Y,ctx->L,ctx->L+L_add,ctx->M,contour->npoints));
    448:     PetscCall(BVSetActiveColumns(ctx->V,ctx->L,ctx->L+L_add));
    449:     PetscCall(BVSetRandomSign(ctx->V));
    450:     if (contour->pA) PetscCall(BVScatter(ctx->V,ctx->pV,contour->scatterin,contour->xdup));
    451:     ctx->L += L_add;
    452:     PetscCall(EPSCISSSolve(eps,J,V,ctx->L-L_add,ctx->L));
    453:   }
    454:   PetscCall(PetscMalloc2(ctx->L*ctx->L*ctx->M*2,&Mu,ctx->L*ctx->M*ctx->L*ctx->M,&H0));
    455:   for (i=0;i<ctx->refine_blocksize;i++) {
    456:     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));
    457:     PetscCall(CISS_BlockHankel(Mu,0,ctx->L,ctx->M,H0));
    458:     PetscCall(PetscLogEventBegin(EPS_CISS_SVD,eps,0,0,0));
    459:     PetscCall(SlepcCISS_BH_SVD(H0,ctx->L*ctx->M,ctx->delta,ctx->sigma,&nv));
    460:     PetscCall(PetscLogEventEnd(EPS_CISS_SVD,eps,0,0,0));
    461:     if (ctx->sigma[0]<=ctx->delta || nv < ctx->L*ctx->M || ctx->L == ctx->L_max) break;
    462:     L_add = L_base;
    463:     if (ctx->L+L_add>ctx->L_max) L_add = ctx->L_max-ctx->L;
    464:     PetscCall(PetscInfo(eps,"Changing L %" PetscInt_FMT " -> %" PetscInt_FMT " by SVD(H0)\n",ctx->L,ctx->L+L_add));
    465:     PetscCall(BVCISSResizeBases(ctx->S,contour->pA?ctx->pV:ctx->V,ctx->Y,ctx->L,ctx->L+L_add,ctx->M,contour->npoints));
    466:     PetscCall(BVSetActiveColumns(ctx->V,ctx->L,ctx->L+L_add));
    467:     PetscCall(BVSetRandomSign(ctx->V));
    468:     if (contour->pA) PetscCall(BVScatter(ctx->V,ctx->pV,contour->scatterin,contour->xdup));
    469:     ctx->L += L_add;
    470:     PetscCall(EPSCISSSolve(eps,J,V,ctx->L-L_add,ctx->L));
    471:     if (L_add) {
    472:       PetscCall(PetscFree2(Mu,H0));
    473:       PetscCall(PetscMalloc2(ctx->L*ctx->L*ctx->M*2,&Mu,ctx->L*ctx->M*ctx->L*ctx->M,&H0));
    474:     }
    475:   }
    476:   if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) PetscCall(PetscMalloc1(ctx->L*ctx->M*ctx->L*ctx->M,&H1));

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

    506:       if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) {
    507:         PetscCall(CISS_BlockHankel(Mu,0,ctx->L,ctx->M,H0));
    508:         PetscCall(CISS_BlockHankel(Mu,1,ctx->L,ctx->M,H1));
    509:         PetscCall(DSGetArray(eps->ds,DS_MAT_A,&temp));
    510:         for (j=0;j<nv;j++) {
    511:           for (i=0;i<nv;i++) {
    512:             temp[i+j*ld] = H1[i+j*ctx->L*ctx->M];
    513:           }
    514:         }
    515:         PetscCall(DSRestoreArray(eps->ds,DS_MAT_A,&temp));
    516:         PetscCall(DSGetArray(eps->ds,DS_MAT_B,&temp));
    517:         for (j=0;j<nv;j++) {
    518:           for (i=0;i<nv;i++) {
    519:             temp[i+j*ld] = H0[i+j*ctx->L*ctx->M];
    520:           }
    521:         }
    522:         PetscCall(DSRestoreArray(eps->ds,DS_MAT_B,&temp));
    523:       } else {
    524:         PetscCall(BVSetActiveColumns(ctx->S,0,nv));
    525:         PetscCall(DSGetMat(eps->ds,DS_MAT_A,&pA));
    526:         PetscCall(MatZeroEntries(pA));
    527:         PetscCall(BVMatProject(ctx->S,A,ctx->S,pA));
    528:         PetscCall(DSRestoreMat(eps->ds,DS_MAT_A,&pA));
    529:         if (B) {
    530:           PetscCall(DSGetMat(eps->ds,DS_MAT_B,&pB));
    531:           PetscCall(MatZeroEntries(pB));
    532:           PetscCall(BVMatProject(ctx->S,B,ctx->S,pB));
    533:           PetscCall(DSRestoreMat(eps->ds,DS_MAT_B,&pB));
    534:         }
    535:       }

    537:       PetscCall(DSSolve(eps->ds,eps->eigr,eps->eigi));
    538:       PetscCall(DSSynchronize(eps->ds,eps->eigr,eps->eigi));

    540:       PetscCall(PetscMalloc3(nv,&fl1,nv,&inside,nv,&rr));
    541:       PetscCall(rescale_eig(eps,nv));
    542:       PetscCall(DSVectors(eps->ds,DS_MAT_X,NULL,NULL));
    543:       PetscCall(DSGetMat(eps->ds,DS_MAT_X,&X));
    544:       PetscCall(SlepcCISS_isGhost(X,nv,ctx->sigma,ctx->spurious_threshold,fl1));
    545:       PetscCall(DSRestoreMat(eps->ds,DS_MAT_X,&X));
    546:       PetscCall(RGCheckInside(eps->rg,nv,eps->eigr,eps->eigi,inside));
    547:       for (i=0;i<nv;i++) {
    548:         if (fl1[i] && inside[i]>=0) {
    549:           rr[i] = 1.0;
    550:           eps->nconv++;
    551:         } else rr[i] = 0.0;
    552:       }
    553:       PetscCall(DSSort(eps->ds,eps->eigr,eps->eigi,rr,NULL,&eps->nconv));
    554:       PetscCall(DSSynchronize(eps->ds,eps->eigr,eps->eigi));
    555:       PetscCall(rescale_eig(eps,nv));
    556:       PetscCall(PetscFree3(fl1,inside,rr));
    557:       PetscCall(BVSetActiveColumns(eps->V,0,nv));
    558:       if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) {
    559:         PetscCall(BVSumQuadrature(ctx->S,ctx->Y,ctx->M,ctx->L,ctx->L,ctx->weight,ctx->pp,contour->scatterin,contour->subcomm,contour->npoints,ctx->useconj));
    560:         PetscCall(BVSetActiveColumns(ctx->S,0,ctx->L));
    561:         PetscCall(BVCopy(ctx->S,ctx->V));
    562:         PetscCall(BVSetActiveColumns(ctx->S,0,nv));
    563:       }
    564:       PetscCall(BVCopy(ctx->S,eps->V));

    566:       PetscCall(DSVectors(eps->ds,DS_MAT_X,NULL,NULL));
    567:       PetscCall(DSGetMat(eps->ds,DS_MAT_X,&X));
    568:       PetscCall(BVMultInPlace(ctx->S,X,0,eps->nconv));
    569:       if (eps->ishermitian) PetscCall(BVMultInPlace(eps->V,X,0,eps->nconv));
    570:       PetscCall(DSRestoreMat(eps->ds,DS_MAT_X,&X));
    571:       max_error = 0.0;
    572:       for (i=0;i<eps->nconv;i++) {
    573:         PetscCall(BVGetColumn(ctx->S,i,&si));
    574: #if !defined(PETSC_USE_COMPLEX)
    575:         if (eps->eigi[i]!=0.0) PetscCall(BVGetColumn(ctx->S,i+1,&si1));
    576: #endif
    577:         PetscCall(EPSComputeResidualNorm_Private(eps,PETSC_FALSE,eps->eigr[i],eps->eigi[i],si,si1,w,&error));
    578:         if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) {  /* vector is not normalized */
    579:           PetscCall(VecNorm(si,NORM_2,&norm));
    580: #if !defined(PETSC_USE_COMPLEX)
    581:           if (eps->eigi[i]!=0.0) {
    582:             PetscCall(VecNorm(si1,NORM_2,&normi));
    583:             norm = SlepcAbsEigenvalue(norm,normi);
    584:           }
    585: #endif
    586:           error /= norm;
    587:         }
    588:         PetscCall((*eps->converged)(eps,eps->eigr[i],eps->eigi[i],error,&error,eps->convergedctx));
    589:         PetscCall(BVRestoreColumn(ctx->S,i,&si));
    590: #if !defined(PETSC_USE_COMPLEX)
    591:         if (eps->eigi[i]!=0.0) {
    592:           PetscCall(BVRestoreColumn(ctx->S,i+1,&si1));
    593:           i++;
    594:         }
    595: #endif
    596:         max_error = PetscMax(max_error,error);
    597:       }

    599:       if (max_error <= eps->tol) eps->reason = EPS_CONVERGED_TOL;
    600:       else if (eps->its >= eps->max_it) eps->reason = EPS_DIVERGED_ITS;
    601:       else {
    602:         if (eps->nconv > ctx->L) nv = eps->nconv;
    603:         else if (ctx->L > nv) nv = ctx->L;
    604:         nv = PetscMin(nv,ctx->L*ctx->M);
    605:         PetscCall(MatCreateSeqDense(PETSC_COMM_SELF,nv,ctx->L,NULL,&M));
    606:         PetscCall(MatSetRandom(M,rand));
    607:         PetscCall(BVSetActiveColumns(ctx->S,0,nv));
    608:         PetscCall(BVMultInPlace(ctx->S,M,0,ctx->L));
    609:         PetscCall(MatDestroy(&M));
    610:         PetscCall(BVSetActiveColumns(ctx->S,0,ctx->L));
    611:         PetscCall(BVSetActiveColumns(ctx->V,0,ctx->L));
    612:         PetscCall(BVCopy(ctx->S,ctx->V));
    613:         if (contour->pA) PetscCall(BVScatter(ctx->V,ctx->pV,contour->scatterin,contour->xdup));
    614:         PetscCall(EPSCISSSolve(eps,J,V,0,ctx->L));
    615:       }
    616:     }
    617:   }
    618:   if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) PetscCall(PetscFree(H1));
    619:   PetscCall(PetscFree2(Mu,H0));
    620:   PetscFunctionReturn(PETSC_SUCCESS);
    621: }

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

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

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

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

    654:   /* normalize */
    655:   if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) PetscCall(BVNormalize(eps->V,NULL));
    656:   PetscFunctionReturn(PETSC_SUCCESS);
    657: }

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

    665:   PetscFunctionBegin;
    666:   oN = ctx->N;
    667:   if (ip == PETSC_DETERMINE) {
    668:     if (ctx->N!=32) { ctx->N =32; ctx->M = ctx->N/4; }
    669:   } else if (ip != PETSC_CURRENT) {
    670:     PetscCheck(ip>0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The ip argument must be > 0");
    671:     PetscCheck(ip%2==0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The ip argument must be an even number");
    672:     if (ctx->N!=ip) { ctx->N = ip; ctx->M = ctx->N/4; }
    673:   }
    674:   oL = ctx->L;
    675:   if (bs == PETSC_DETERMINE) {
    676:     ctx->L = 16;
    677:   } else if (bs != PETSC_CURRENT) {
    678:     PetscCheck(bs>0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The bs argument must be > 0");
    679:     ctx->L = bs;
    680:   }
    681:   oM = ctx->M;
    682:   if (ms == PETSC_DETERMINE) {
    683:     ctx->M = ctx->N/4;
    684:   } else if (ms != PETSC_CURRENT) {
    685:     PetscCheck(ms>0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The ms argument must be > 0");
    686:     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");
    687:     ctx->M = ms;
    688:   }
    689:   onpart = ctx->npart;
    690:   if (npart == PETSC_DETERMINE) {
    691:     ctx->npart = 1;
    692:   } else if (npart != PETSC_CURRENT) {
    693:     PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)eps),&size));
    694:     PetscCheck(npart>0 && npart<=size,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"Illegal value of npart");
    695:     ctx->npart = npart;
    696:   }
    697:   oLmax = ctx->L_max;
    698:   if (bsmax == PETSC_DETERMINE) {
    699:     ctx->L_max = 64;
    700:   } else if (bsmax != PETSC_CURRENT) {
    701:     PetscCheck(bsmax>0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The bsmax argument must be > 0");
    702:     ctx->L_max = PetscMax(bsmax,ctx->L);
    703:   }
    704:   if (onpart != ctx->npart || oN != ctx->N || realmats != ctx->isreal) {
    705:     PetscCall(SlepcContourDataDestroy(&ctx->contour));
    706:     PetscCall(PetscInfo(eps,"Resetting the contour data structure due to a change of parameters\n"));
    707:     eps->state = EPS_STATE_INITIAL;
    708:   }
    709:   ctx->isreal = realmats;
    710:   if (oL != ctx->L || oM != ctx->M || oLmax != ctx->L_max) eps->state = EPS_STATE_INITIAL;
    711:   PetscFunctionReturn(PETSC_SUCCESS);
    712: }

    714: /*@
    715:    EPSCISSSetSizes - Sets the values of various size parameters in the CISS solver.

    717:    Logically Collective

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

    728:    Options Database Keys:
    729: +  -eps_ciss_integration_points \<ip\> - sets the number of integration points
    730: .  -eps_ciss_blocksize \<bs\>          - sets the block size
    731: .  -eps_ciss_moments \<ms\>            - sets the moment size
    732: .  -eps_ciss_partitions \<npart\>      - sets the number of partitions
    733: .  -eps_ciss_maxblocksize \<bsmax\>    - sets the maximum block size
    734: -  -eps_ciss_realmats                  - $A$ and $B$ are real

    736:    Notes:
    737:    For all integer arguments, you can use `PETSC_CURRENT` to keep the current value, and
    738:    `PETSC_DETERMINE` to set them to a default value.

    740:    The default number of partitions is 1. This means the internal `KSP` object is shared
    741:    among all processes of the `EPS` communicator. Otherwise, the communicator is split
    742:    into `npart` communicators, so that `npart` `KSP` solves proceed simultaneously.

    744:    For a detailed description of the parameters see {cite:p}`Mae16`.

    746:    Level: advanced

    748: .seealso: [](ch:eps), `EPSCISS`, `EPSCISSGetSizes()`, `EPSCISSSetThreshold()`, `EPSCISSSetRefinement()`
    749: @*/
    750: PetscErrorCode EPSCISSSetSizes(EPS eps,PetscInt ip,PetscInt bs,PetscInt ms,PetscInt npart,PetscInt bsmax,PetscBool realmats)
    751: {
    752:   PetscFunctionBegin;
    760:   PetscTryMethod(eps,"EPSCISSSetSizes_C",(EPS,PetscInt,PetscInt,PetscInt,PetscInt,PetscInt,PetscBool),(eps,ip,bs,ms,npart,bsmax,realmats));
    761:   PetscFunctionReturn(PETSC_SUCCESS);
    762: }

    764: static PetscErrorCode EPSCISSGetSizes_CISS(EPS eps,PetscInt *ip,PetscInt *bs,PetscInt *ms,PetscInt *npart,PetscInt *bsmax,PetscBool *realmats)
    765: {
    766:   EPS_CISS *ctx = (EPS_CISS*)eps->data;

    768:   PetscFunctionBegin;
    769:   if (ip) *ip = ctx->N;
    770:   if (bs) *bs = ctx->L;
    771:   if (ms) *ms = ctx->M;
    772:   if (npart) *npart = ctx->npart;
    773:   if (bsmax) *bsmax = ctx->L_max;
    774:   if (realmats) *realmats = ctx->isreal;
    775:   PetscFunctionReturn(PETSC_SUCCESS);
    776: }

    778: /*@
    779:    EPSCISSGetSizes - Gets the values of various size parameters in the CISS solver.

    781:    Not Collective

    783:    Input Parameter:
    784: .  eps - the linear eigensolver context

    786:    Output Parameters:
    787: +  ip    - number of integration points
    788: .  bs    - block size
    789: .  ms    - moment size
    790: .  npart - number of partitions when splitting the communicator
    791: .  bsmax - max block size
    792: -  realmats - $A$ and $B$ are real

    794:    Level: advanced

    796: .seealso: [](ch:eps), `EPSCISS`, `EPSCISSSetSizes()`
    797: @*/
    798: PetscErrorCode EPSCISSGetSizes(EPS eps,PetscInt *ip,PetscInt *bs,PetscInt *ms,PetscInt *npart,PetscInt *bsmax,PetscBool *realmats)
    799: {
    800:   PetscFunctionBegin;
    802:   PetscUseMethod(eps,"EPSCISSGetSizes_C",(EPS,PetscInt*,PetscInt*,PetscInt*,PetscInt*,PetscInt*,PetscBool*),(eps,ip,bs,ms,npart,bsmax,realmats));
    803:   PetscFunctionReturn(PETSC_SUCCESS);
    804: }

    806: static PetscErrorCode EPSCISSSetThreshold_CISS(EPS eps,PetscReal delta,PetscReal spur)
    807: {
    808:   EPS_CISS *ctx = (EPS_CISS*)eps->data;

    810:   PetscFunctionBegin;
    811:   if (delta == (PetscReal)PETSC_DETERMINE) {
    812:     ctx->delta = SLEPC_DEFAULT_TOL*1e-4;
    813:   } else if (delta != (PetscReal)PETSC_CURRENT) {
    814:     PetscCheck(delta>0.0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The delta argument must be > 0.0");
    815:     ctx->delta = delta;
    816:   }
    817:   if (spur == (PetscReal)PETSC_DETERMINE) {
    818:     ctx->spurious_threshold = PetscSqrtReal(SLEPC_DEFAULT_TOL);
    819:   } else if (spur != (PetscReal)PETSC_CURRENT) {
    820:     PetscCheck(spur>0.0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The spurious threshold argument must be > 0.0");
    821:     ctx->spurious_threshold = spur;
    822:   }
    823:   PetscFunctionReturn(PETSC_SUCCESS);
    824: }

    826: /*@
    827:    EPSCISSSetThreshold - Sets the values of various threshold parameters in
    828:    the CISS solver.

    830:    Logically Collective

    832:    Input Parameters:
    833: +  eps   - the linear eigensolver context
    834: .  delta - threshold for numerical rank
    835: -  spur  - spurious threshold (to discard spurious eigenpairs)

    837:    Options Database Keys:
    838: +  -eps_ciss_delta \<delta\>             - sets the delta
    839: -  -eps_ciss_spurious_threshold \<spur\> - sets the spurious threshold

    841:    Notes:
    842:    `PETSC_CURRENT` can be used to preserve the current value of any of the
    843:    arguments, and `PETSC_DETERMINE` to set them to a default value.

    845:    For a detailed description of the parameters see {cite:p}`Mae16`.

    847:    Level: advanced

    849: .seealso: [](ch:eps), `EPSCISS`, `EPSCISSGetThreshold()`, `EPSCISSSetSizes()`, `EPSCISSSetRefinement()`
    850: @*/
    851: PetscErrorCode EPSCISSSetThreshold(EPS eps,PetscReal delta,PetscReal spur)
    852: {
    853:   PetscFunctionBegin;
    857:   PetscTryMethod(eps,"EPSCISSSetThreshold_C",(EPS,PetscReal,PetscReal),(eps,delta,spur));
    858:   PetscFunctionReturn(PETSC_SUCCESS);
    859: }

    861: static PetscErrorCode EPSCISSGetThreshold_CISS(EPS eps,PetscReal *delta,PetscReal *spur)
    862: {
    863:   EPS_CISS *ctx = (EPS_CISS*)eps->data;

    865:   PetscFunctionBegin;
    866:   if (delta) *delta = ctx->delta;
    867:   if (spur)  *spur = ctx->spurious_threshold;
    868:   PetscFunctionReturn(PETSC_SUCCESS);
    869: }

    871: /*@
    872:    EPSCISSGetThreshold - Gets the values of various threshold parameters
    873:    in the CISS solver.

    875:    Not Collective

    877:    Input Parameter:
    878: .  eps - the linear eigensolver context

    880:    Output Parameters:
    881: +  delta - threshold for numerical rank
    882: -  spur  - spurious threshold (to discard spurious eigenpairs)

    884:    Level: advanced

    886: .seealso: [](ch:eps), `EPSCISS`, `EPSCISSSetThreshold()`
    887: @*/
    888: PetscErrorCode EPSCISSGetThreshold(EPS eps,PetscReal *delta,PetscReal *spur)
    889: {
    890:   PetscFunctionBegin;
    892:   PetscUseMethod(eps,"EPSCISSGetThreshold_C",(EPS,PetscReal*,PetscReal*),(eps,delta,spur));
    893:   PetscFunctionReturn(PETSC_SUCCESS);
    894: }

    896: static PetscErrorCode EPSCISSSetRefinement_CISS(EPS eps,PetscInt inner,PetscInt blsize)
    897: {
    898:   EPS_CISS *ctx = (EPS_CISS*)eps->data;

    900:   PetscFunctionBegin;
    901:   if (inner == PETSC_DETERMINE) {
    902:     ctx->refine_inner = 0;
    903:   } else if (inner != PETSC_CURRENT) {
    904:     PetscCheck(inner>=0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The refine inner argument must be >= 0");
    905:     ctx->refine_inner = inner;
    906:   }
    907:   if (blsize == PETSC_DETERMINE) {
    908:     ctx->refine_blocksize = 0;
    909:   } else if (blsize != PETSC_CURRENT) {
    910:     PetscCheck(blsize>=0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The refine blocksize argument must be >= 0");
    911:     ctx->refine_blocksize = blsize;
    912:   }
    913:   PetscFunctionReturn(PETSC_SUCCESS);
    914: }

    916: /*@
    917:    EPSCISSSetRefinement - Sets the values of various refinement parameters
    918:    in the CISS solver.

    920:    Logically Collective

    922:    Input Parameters:
    923: +  eps    - the linear eigensolver context
    924: .  inner  - number of iterative refinement iterations (inner loop)
    925: -  blsize - number of iterative refinement iterations (blocksize loop)

    927:    Options Database Keys:
    928: +  -eps_ciss_refine_inner \<inner\>      - sets number of inner iterations
    929: -  -eps_ciss_refine_blocksize \<blsize\> - sets number of blocksize iterations

    931:    Notes:
    932:    `PETSC_CURRENT` can be used to preserve the current value of any of the
    933:    arguments, and `PETSC_DETERMINE` to set them to a default of 0 (no refinement).

    935:    For a detailed description of the parameters see {cite:p}`Mae16`.

    937:    Level: advanced

    939: .seealso: [](ch:eps), `EPSCISS`, `EPSCISSGetRefinement()`, `EPSCISSSetSizes()`, `EPSCISSSetThreshold()`
    940: @*/
    941: PetscErrorCode EPSCISSSetRefinement(EPS eps,PetscInt inner,PetscInt blsize)
    942: {
    943:   PetscFunctionBegin;
    947:   PetscTryMethod(eps,"EPSCISSSetRefinement_C",(EPS,PetscInt,PetscInt),(eps,inner,blsize));
    948:   PetscFunctionReturn(PETSC_SUCCESS);
    949: }

    951: static PetscErrorCode EPSCISSGetRefinement_CISS(EPS eps,PetscInt *inner,PetscInt *blsize)
    952: {
    953:   EPS_CISS *ctx = (EPS_CISS*)eps->data;

    955:   PetscFunctionBegin;
    956:   if (inner)  *inner = ctx->refine_inner;
    957:   if (blsize) *blsize = ctx->refine_blocksize;
    958:   PetscFunctionReturn(PETSC_SUCCESS);
    959: }

    961: /*@
    962:    EPSCISSGetRefinement - Gets the values of various refinement parameters
    963:    in the CISS solver.

    965:    Not Collective

    967:    Input Parameter:
    968: .  eps - the linear eigensolver context

    970:    Output Parameters:
    971: +  inner  - number of iterative refinement iterations (inner loop)
    972: -  blsize - number of iterative refinement iterations (blocksize loop)

    974:    Level: advanced

    976: .seealso: [](ch:eps), `EPSCISS`, `EPSCISSSetRefinement()`
    977: @*/
    978: PetscErrorCode EPSCISSGetRefinement(EPS eps, PetscInt *inner, PetscInt *blsize)
    979: {
    980:   PetscFunctionBegin;
    982:   PetscUseMethod(eps,"EPSCISSGetRefinement_C",(EPS,PetscInt*,PetscInt*),(eps,inner,blsize));
    983:   PetscFunctionReturn(PETSC_SUCCESS);
    984: }

    986: static PetscErrorCode EPSCISSSetUseST_CISS(EPS eps,PetscBool usest)
    987: {
    988:   EPS_CISS *ctx = (EPS_CISS*)eps->data;

    990:   PetscFunctionBegin;
    991:   ctx->usest     = usest;
    992:   ctx->usest_set = PETSC_TRUE;
    993:   eps->state     = EPS_STATE_INITIAL;
    994:   PetscFunctionReturn(PETSC_SUCCESS);
    995: }

    997: /*@
    998:    EPSCISSSetUseST - Sets a flag indicating that the CISS solver will
    999:    use the `ST` object for the linear solves.

    1001:    Logically Collective

    1003:    Input Parameters:
    1004: +  eps    - the linear eigensolver context
    1005: -  usest  - boolean flag to use the `ST` object or not

    1007:    Options Database Key:
    1008: .  -eps_ciss_usest - whether the `ST` object will be used or not

    1010:    Note:
    1011:    When this option is set, the linear solves can be configured by
    1012:    setting options for the `KSP` object obtained with `STGetKSP()`.
    1013:    Otherwise, several `KSP` objects are created, which can be accessed
    1014:    with `EPSCISSGetKSPs()`.

    1016:    The default is to use the `ST`, unless several partitions have been
    1017:    specified, see `EPSCISSSetSizes()`.

    1019:    Level: advanced

    1021: .seealso: [](ch:eps), `EPSCISS`, `EPSCISSGetUseST()`, `EPSCISSSetSizes()`, `EPSCISSGetKSPs()`, `STGetKSP()`
    1022: @*/
    1023: PetscErrorCode EPSCISSSetUseST(EPS eps,PetscBool usest)
    1024: {
    1025:   PetscFunctionBegin;
    1028:   PetscTryMethod(eps,"EPSCISSSetUseST_C",(EPS,PetscBool),(eps,usest));
    1029:   PetscFunctionReturn(PETSC_SUCCESS);
    1030: }

    1032: static PetscErrorCode EPSCISSGetUseST_CISS(EPS eps,PetscBool *usest)
    1033: {
    1034:   EPS_CISS *ctx = (EPS_CISS*)eps->data;

    1036:   PetscFunctionBegin;
    1037:   *usest = ctx->usest;
    1038:   PetscFunctionReturn(PETSC_SUCCESS);
    1039: }

    1041: /*@
    1042:    EPSCISSGetUseST - Gets the flag for using the `ST` object
    1043:    in the CISS solver.

    1045:    Not Collective

    1047:    Input Parameter:
    1048: .  eps - the linear eigensolver context

    1050:    Output Parameter:
    1051: .  usest - boolean flag indicating if the `ST` object is being used

    1053:    Level: advanced

    1055: .seealso: [](ch:eps), `EPSCISS`, `EPSCISSSetUseST()`
    1056: @*/
    1057: PetscErrorCode EPSCISSGetUseST(EPS eps,PetscBool *usest)
    1058: {
    1059:   PetscFunctionBegin;
    1061:   PetscAssertPointer(usest,2);
    1062:   PetscUseMethod(eps,"EPSCISSGetUseST_C",(EPS,PetscBool*),(eps,usest));
    1063:   PetscFunctionReturn(PETSC_SUCCESS);
    1064: }

    1066: static PetscErrorCode EPSCISSSetQuadRule_CISS(EPS eps,EPSCISSQuadRule quad)
    1067: {
    1068:   EPS_CISS *ctx = (EPS_CISS*)eps->data;

    1070:   PetscFunctionBegin;
    1071:   if (ctx->quad != quad) {
    1072:     ctx->quad  = quad;
    1073:     eps->state = EPS_STATE_INITIAL;
    1074:   }
    1075:   PetscFunctionReturn(PETSC_SUCCESS);
    1076: }

    1078: /*@
    1079:    EPSCISSSetQuadRule - Sets the quadrature rule used in the CISS solver.

    1081:    Logically Collective

    1083:    Input Parameters:
    1084: +  eps  - the linear eigensolver context
    1085: -  quad - the quadrature rule, see `EPSCISSQuadRule` for possible values

    1087:    Options Database Key:
    1088: .  -eps_ciss_quadrule \<quad\> - sets the quadrature rule, either `trapezoidal` or `chebyshev`

    1090:    Notes:
    1091:    By default, the trapezoidal rule is used (`EPS_CISS_QUADRULE_TRAPEZOIDAL`).

    1093:    If the `chebyshev` option is specified (`EPS_CISS_QUADRULE_CHEBYSHEV`), then
    1094:    Chebyshev points are used as quadrature points.

    1096:    Level: advanced

    1098: .seealso: [](ch:eps), `EPSCISS`, `EPSCISSGetQuadRule()`, `EPSCISSQuadRule`
    1099: @*/
    1100: PetscErrorCode EPSCISSSetQuadRule(EPS eps,EPSCISSQuadRule quad)
    1101: {
    1102:   PetscFunctionBegin;
    1105:   PetscTryMethod(eps,"EPSCISSSetQuadRule_C",(EPS,EPSCISSQuadRule),(eps,quad));
    1106:   PetscFunctionReturn(PETSC_SUCCESS);
    1107: }

    1109: static PetscErrorCode EPSCISSGetQuadRule_CISS(EPS eps,EPSCISSQuadRule *quad)
    1110: {
    1111:   EPS_CISS *ctx = (EPS_CISS*)eps->data;

    1113:   PetscFunctionBegin;
    1114:   *quad = ctx->quad;
    1115:   PetscFunctionReturn(PETSC_SUCCESS);
    1116: }

    1118: /*@
    1119:    EPSCISSGetQuadRule - Gets the quadrature rule used in the CISS solver.

    1121:    Not Collective

    1123:    Input Parameter:
    1124: .  eps - the linear eigensolver context

    1126:    Output Parameter:
    1127: .  quad - quadrature rule

    1129:    Level: advanced

    1131: .seealso: [](ch:eps), `EPSCISS`, `EPSCISSSetQuadRule()`, `EPSCISSQuadRule`
    1132: @*/
    1133: PetscErrorCode EPSCISSGetQuadRule(EPS eps,EPSCISSQuadRule *quad)
    1134: {
    1135:   PetscFunctionBegin;
    1137:   PetscAssertPointer(quad,2);
    1138:   PetscUseMethod(eps,"EPSCISSGetQuadRule_C",(EPS,EPSCISSQuadRule*),(eps,quad));
    1139:   PetscFunctionReturn(PETSC_SUCCESS);
    1140: }

    1142: static PetscErrorCode EPSCISSSetExtraction_CISS(EPS eps,EPSCISSExtraction extraction)
    1143: {
    1144:   EPS_CISS *ctx = (EPS_CISS*)eps->data;

    1146:   PetscFunctionBegin;
    1147:   if (ctx->extraction != extraction) {
    1148:     ctx->extraction = extraction;
    1149:     eps->state      = EPS_STATE_INITIAL;
    1150:   }
    1151:   PetscFunctionReturn(PETSC_SUCCESS);
    1152: }

    1154: /*@
    1155:    EPSCISSSetExtraction - Sets the extraction technique used in the CISS solver.

    1157:    Logically Collective

    1159:    Input Parameters:
    1160: +  eps        - the linear eigensolver context
    1161: -  extraction - the extraction technique, see `EPSCISSExtraction` for possible values

    1163:    Options Database Key:
    1164: .  -eps_ciss_extraction \<extraction\> - sets the extraction technique, either `ritz` or `hankel`

    1166:    Notes:
    1167:    By default, the Rayleigh-Ritz extraction is used (`EPS_CISS_EXTRACTION_RITZ`),
    1168:    see {cite:p}`Sak07`.

    1170:    If the `hankel` option is specified (`EPS_CISS_EXTRACTION_HANKEL`), then
    1171:    the block Hankel method is used for extracting eigenpairs {cite:p}`Sak03`.

    1173:    Level: advanced

    1175: .seealso: [](ch:eps), `EPSCISS`, `EPSCISSGetExtraction()`, `EPSCISSExtraction`
    1176: @*/
    1177: PetscErrorCode EPSCISSSetExtraction(EPS eps,EPSCISSExtraction extraction)
    1178: {
    1179:   PetscFunctionBegin;
    1182:   PetscTryMethod(eps,"EPSCISSSetExtraction_C",(EPS,EPSCISSExtraction),(eps,extraction));
    1183:   PetscFunctionReturn(PETSC_SUCCESS);
    1184: }

    1186: static PetscErrorCode EPSCISSGetExtraction_CISS(EPS eps,EPSCISSExtraction *extraction)
    1187: {
    1188:   EPS_CISS *ctx = (EPS_CISS*)eps->data;

    1190:   PetscFunctionBegin;
    1191:   *extraction = ctx->extraction;
    1192:   PetscFunctionReturn(PETSC_SUCCESS);
    1193: }

    1195: /*@
    1196:    EPSCISSGetExtraction - Gets the extraction technique used in the CISS solver.

    1198:    Not Collective

    1200:    Input Parameter:
    1201: .  eps - the linear eigensolver context

    1203:    Output Parameter:
    1204: .  extraction - extraction technique

    1206:    Level: advanced

    1208: .seealso: [](ch:eps), `EPSCISS`, `EPSCISSSetExtraction()`, `EPSCISSExtraction`
    1209: @*/
    1210: PetscErrorCode EPSCISSGetExtraction(EPS eps,EPSCISSExtraction *extraction)
    1211: {
    1212:   PetscFunctionBegin;
    1214:   PetscAssertPointer(extraction,2);
    1215:   PetscUseMethod(eps,"EPSCISSGetExtraction_C",(EPS,EPSCISSExtraction*),(eps,extraction));
    1216:   PetscFunctionReturn(PETSC_SUCCESS);
    1217: }

    1219: static PetscErrorCode EPSCISSGetKSPs_CISS(EPS eps,PetscInt *nsolve,KSP **ksp)
    1220: {
    1221:   EPS_CISS         *ctx = (EPS_CISS*)eps->data;
    1222:   SlepcContourData contour;
    1223:   PetscInt         i,nsplit;
    1224:   PC               pc;
    1225:   MPI_Comm         child;

    1227:   PetscFunctionBegin;
    1228:   if (!ctx->contour) {  /* initialize contour data structure first */
    1229:     PetscCall(RGCanUseConjugates(eps->rg,ctx->isreal,&ctx->useconj));
    1230:     PetscCall(SlepcContourDataCreate(ctx->useconj?ctx->N/2:ctx->N,ctx->npart,(PetscObject)eps,&ctx->contour));
    1231:   }
    1232:   contour = ctx->contour;
    1233:   if (!contour->ksp) {
    1234:     PetscCall(PetscMalloc1(contour->npoints,&contour->ksp));
    1235:     PetscCall(EPSGetST(eps,&eps->st));
    1236:     PetscCall(STGetSplitPreconditionerInfo(eps->st,&nsplit,NULL));
    1237:     PetscCall(PetscSubcommGetChild(contour->subcomm,&child));
    1238:     for (i=0;i<contour->npoints;i++) {
    1239:       PetscCall(KSPCreate(child,&contour->ksp[i]));
    1240:       PetscCall(PetscObjectIncrementTabLevel((PetscObject)contour->ksp[i],(PetscObject)eps,1));
    1241:       PetscCall(KSPSetOptionsPrefix(contour->ksp[i],((PetscObject)eps)->prefix));
    1242:       PetscCall(KSPAppendOptionsPrefix(contour->ksp[i],"eps_ciss_"));
    1243:       PetscCall(PetscObjectSetOptions((PetscObject)contour->ksp[i],((PetscObject)eps)->options));
    1244:       PetscCall(KSPSetErrorIfNotConverged(contour->ksp[i],PETSC_TRUE));
    1245:       PetscCall(KSPSetTolerances(contour->ksp[i],SlepcDefaultTol(eps->tol),PETSC_CURRENT,PETSC_CURRENT,PETSC_CURRENT));
    1246:       PetscCall(KSPGetPC(contour->ksp[i],&pc));
    1247:       if (nsplit) {
    1248:         PetscCall(KSPSetType(contour->ksp[i],KSPBCGS));
    1249:         PetscCall(PCSetType(pc,PCBJACOBI));
    1250:       } else {
    1251:         PetscCall(KSPSetType(contour->ksp[i],KSPPREONLY));
    1252:         PetscCall(PCSetType(pc,PCLU));
    1253:       }
    1254:     }
    1255:   }
    1256:   if (nsolve) *nsolve = contour->npoints;
    1257:   if (ksp)    *ksp    = contour->ksp;
    1258:   PetscFunctionReturn(PETSC_SUCCESS);
    1259: }

    1261: /*@C
    1262:    EPSCISSGetKSPs - Retrieve the array of linear solver objects associated with
    1263:    the CISS solver.

    1265:    Not Collective

    1267:    Input Parameter:
    1268: .  eps - the linear eigensolver context

    1270:    Output Parameters:
    1271: +  nsolve - number of solver objects
    1272: -  ksp - array of linear solver object

    1274:    Note:
    1275:    The number of `KSP` solvers is equal to the number of integration points divided by
    1276:    the number of partitions, see `EPSCISSSetSizes()`. This value is halved in the case
    1277:    of real matrices with a region centered at the real axis.

    1279:    Level: advanced

    1281: .seealso: [](ch:eps), `EPSCISS`, `EPSCISSSetSizes()`
    1282: @*/
    1283: PetscErrorCode EPSCISSGetKSPs(EPS eps,PetscInt *nsolve,KSP **ksp)
    1284: {
    1285:   PetscFunctionBegin;
    1287:   PetscUseMethod(eps,"EPSCISSGetKSPs_C",(EPS,PetscInt*,KSP**),(eps,nsolve,ksp));
    1288:   PetscFunctionReturn(PETSC_SUCCESS);
    1289: }

    1291: static PetscErrorCode EPSReset_CISS(EPS eps)
    1292: {
    1293:   EPS_CISS       *ctx = (EPS_CISS*)eps->data;

    1295:   PetscFunctionBegin;
    1296:   PetscCall(BVDestroy(&ctx->S));
    1297:   PetscCall(BVDestroy(&ctx->V));
    1298:   PetscCall(BVDestroy(&ctx->Y));
    1299:   if (!ctx->usest) PetscCall(SlepcContourDataReset(ctx->contour));
    1300:   PetscCall(BVDestroy(&ctx->pV));
    1301:   PetscFunctionReturn(PETSC_SUCCESS);
    1302: }

    1304: static PetscErrorCode EPSSetFromOptions_CISS(EPS eps,PetscOptionItems PetscOptionsObject)
    1305: {
    1306:   PetscReal         r3,r4;
    1307:   PetscInt          i,i1,i2,i3,i4,i5,i6,i7;
    1308:   PetscBool         b1,b2,flg,flg2,flg3,flg4,flg5,flg6;
    1309:   EPS_CISS          *ctx = (EPS_CISS*)eps->data;
    1310:   EPSCISSQuadRule   quad;
    1311:   EPSCISSExtraction extraction;

    1313:   PetscFunctionBegin;
    1314:   PetscOptionsHeadBegin(PetscOptionsObject,"EPS CISS Options");

    1316:     PetscCall(EPSCISSGetSizes(eps,&i1,&i2,&i3,&i4,&i5,&b1));
    1317:     PetscCall(PetscOptionsInt("-eps_ciss_integration_points","Number of integration points","EPSCISSSetSizes",i1,&i1,&flg));
    1318:     PetscCall(PetscOptionsInt("-eps_ciss_blocksize","Block size","EPSCISSSetSizes",i2,&i2,&flg2));
    1319:     PetscCall(PetscOptionsInt("-eps_ciss_moments","Moment size","EPSCISSSetSizes",i3,&i3,&flg3));
    1320:     PetscCall(PetscOptionsInt("-eps_ciss_partitions","Number of partitions","EPSCISSSetSizes",i4,&i4,&flg4));
    1321:     PetscCall(PetscOptionsInt("-eps_ciss_maxblocksize","Maximum block size","EPSCISSSetSizes",i5,&i5,&flg5));
    1322:     PetscCall(PetscOptionsBool("-eps_ciss_realmats","True if A and B are real","EPSCISSSetSizes",b1,&b1,&flg6));
    1323:     if (flg || flg2 || flg3 || flg4 || flg5 || flg6) PetscCall(EPSCISSSetSizes(eps,i1,i2,i3,i4,i5,b1));

    1325:     PetscCall(EPSCISSGetThreshold(eps,&r3,&r4));
    1326:     PetscCall(PetscOptionsReal("-eps_ciss_delta","Threshold for numerical rank","EPSCISSSetThreshold",r3,&r3,&flg));
    1327:     PetscCall(PetscOptionsReal("-eps_ciss_spurious_threshold","Threshold for the spurious eigenpairs","EPSCISSSetThreshold",r4,&r4,&flg2));
    1328:     if (flg || flg2) PetscCall(EPSCISSSetThreshold(eps,r3,r4));

    1330:     PetscCall(EPSCISSGetRefinement(eps,&i6,&i7));
    1331:     PetscCall(PetscOptionsInt("-eps_ciss_refine_inner","Number of inner iterative refinement iterations","EPSCISSSetRefinement",i6,&i6,&flg));
    1332:     PetscCall(PetscOptionsInt("-eps_ciss_refine_blocksize","Number of blocksize iterative refinement iterations","EPSCISSSetRefinement",i7,&i7,&flg2));
    1333:     if (flg || flg2) PetscCall(EPSCISSSetRefinement(eps,i6,i7));

    1335:     PetscCall(EPSCISSGetUseST(eps,&b2));
    1336:     PetscCall(PetscOptionsBool("-eps_ciss_usest","Use ST for linear solves","EPSCISSSetUseST",b2,&b2,&flg));
    1337:     if (flg) PetscCall(EPSCISSSetUseST(eps,b2));

    1339:     PetscCall(PetscOptionsEnum("-eps_ciss_quadrule","Quadrature rule","EPSCISSSetQuadRule",EPSCISSQuadRules,(PetscEnum)ctx->quad,(PetscEnum*)&quad,&flg));
    1340:     if (flg) PetscCall(EPSCISSSetQuadRule(eps,quad));

    1342:     PetscCall(PetscOptionsEnum("-eps_ciss_extraction","Extraction technique","EPSCISSSetExtraction",EPSCISSExtractions,(PetscEnum)ctx->extraction,(PetscEnum*)&extraction,&flg));
    1343:     if (flg) PetscCall(EPSCISSSetExtraction(eps,extraction));

    1345:   PetscOptionsHeadEnd();

    1347:   if (!eps->rg) PetscCall(EPSGetRG(eps,&eps->rg));
    1348:   PetscCall(RGSetFromOptions(eps->rg)); /* this is necessary here to set useconj */
    1349:   if (!ctx->contour || !ctx->contour->ksp) PetscCall(EPSCISSGetKSPs(eps,NULL,NULL));
    1350:   PetscAssert(ctx->contour && ctx->contour->ksp,PetscObjectComm((PetscObject)eps),PETSC_ERR_PLIB,"Something went wrong with EPSCISSGetKSPs()");
    1351:   for (i=0;i<ctx->contour->npoints;i++) PetscCall(KSPSetFromOptions(ctx->contour->ksp[i]));
    1352:   PetscCall(PetscSubcommSetFromOptions(ctx->contour->subcomm));
    1353:   PetscFunctionReturn(PETSC_SUCCESS);
    1354: }

    1356: static PetscErrorCode EPSDestroy_CISS(EPS eps)
    1357: {
    1358:   EPS_CISS       *ctx = (EPS_CISS*)eps->data;

    1360:   PetscFunctionBegin;
    1361:   PetscCall(SlepcContourDataDestroy(&ctx->contour));
    1362:   PetscCall(PetscFree4(ctx->weight,ctx->omega,ctx->pp,ctx->sigma));
    1363:   PetscCall(PetscFree(eps->data));
    1364:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetSizes_C",NULL));
    1365:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetSizes_C",NULL));
    1366:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetThreshold_C",NULL));
    1367:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetThreshold_C",NULL));
    1368:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetRefinement_C",NULL));
    1369:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetRefinement_C",NULL));
    1370:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetUseST_C",NULL));
    1371:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetUseST_C",NULL));
    1372:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetQuadRule_C",NULL));
    1373:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetQuadRule_C",NULL));
    1374:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetExtraction_C",NULL));
    1375:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetExtraction_C",NULL));
    1376:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetKSPs_C",NULL));
    1377:   PetscFunctionReturn(PETSC_SUCCESS);
    1378: }

    1380: static PetscErrorCode EPSView_CISS(EPS eps,PetscViewer viewer)
    1381: {
    1382:   EPS_CISS       *ctx = (EPS_CISS*)eps->data;
    1383:   PetscBool      isascii;
    1384:   PetscViewer    sviewer;

    1386:   PetscFunctionBegin;
    1387:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isascii));
    1388:   if (isascii) {
    1389:     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));
    1390:     if (ctx->isreal) PetscCall(PetscViewerASCIIPrintf(viewer,"  exploiting symmetry of integration points\n"));
    1391:     PetscCall(PetscViewerASCIIPrintf(viewer,"  threshold { delta: %g, spurious threshold: %g }\n",(double)ctx->delta,(double)ctx->spurious_threshold));
    1392:     PetscCall(PetscViewerASCIIPrintf(viewer,"  iterative refinement { inner: %" PetscInt_FMT ", blocksize: %" PetscInt_FMT " }\n",ctx->refine_inner, ctx->refine_blocksize));
    1393:     PetscCall(PetscViewerASCIIPrintf(viewer,"  extraction: %s\n",EPSCISSExtractions[ctx->extraction]));
    1394:     PetscCall(PetscViewerASCIIPrintf(viewer,"  quadrature rule: %s\n",EPSCISSQuadRules[ctx->quad]));
    1395:     if (ctx->usest) PetscCall(PetscViewerASCIIPrintf(viewer,"  using ST for linear solves\n"));
    1396:     else {
    1397:       if (!ctx->contour || !ctx->contour->ksp) PetscCall(EPSCISSGetKSPs(eps,NULL,NULL));
    1398:       PetscAssert(ctx->contour && ctx->contour->ksp,PetscObjectComm((PetscObject)eps),PETSC_ERR_PLIB,"Something went wrong with EPSCISSGetKSPs()");
    1399:       PetscCall(PetscViewerASCIIPushTab(viewer));
    1400:       if (ctx->npart>1 && ctx->contour->subcomm) {
    1401:         PetscCall(PetscViewerGetSubViewer(viewer,ctx->contour->subcomm->child,&sviewer));
    1402:         if (!ctx->contour->subcomm->color) PetscCall(KSPView(ctx->contour->ksp[0],sviewer));
    1403:         PetscCall(PetscViewerFlush(sviewer));
    1404:         PetscCall(PetscViewerRestoreSubViewer(viewer,ctx->contour->subcomm->child,&sviewer));
    1405:         /* extra call needed because of the two calls to PetscViewerASCIIPushSynchronized() in PetscViewerGetSubViewer() */
    1406:         PetscCall(PetscViewerASCIIPopSynchronized(viewer));
    1407:       } else PetscCall(KSPView(ctx->contour->ksp[0],viewer));
    1408:       PetscCall(PetscViewerASCIIPopTab(viewer));
    1409:     }
    1410:   }
    1411:   PetscFunctionReturn(PETSC_SUCCESS);
    1412: }

    1414: static PetscErrorCode EPSSetDefaultST_CISS(EPS eps)
    1415: {
    1416:   EPS_CISS       *ctx = (EPS_CISS*)eps->data;
    1417:   PetscBool      usest = ctx->usest;
    1418:   KSP            ksp;
    1419:   PC             pc;

    1421:   PetscFunctionBegin;
    1422:   if (!((PetscObject)eps->st)->type_name) {
    1423:     if (!ctx->usest_set) usest = (ctx->npart>1)? PETSC_FALSE: PETSC_TRUE;
    1424:     if (usest) PetscCall(STSetType(eps->st,STSINVERT));
    1425:     else {
    1426:       /* we are not going to use ST, so avoid factorizing the matrix */
    1427:       PetscCall(STSetType(eps->st,STSHIFT));
    1428:       if (eps->isgeneralized) {
    1429:         PetscCall(STGetKSP(eps->st,&ksp));
    1430:         PetscCall(KSPGetPC(ksp,&pc));
    1431:         PetscCall(PCSetType(pc,PCNONE));
    1432:       }
    1433:     }
    1434:   }
    1435:   PetscFunctionReturn(PETSC_SUCCESS);
    1436: }

    1438: /*MC
    1439:    EPSCISS - EPSCISS = "ciss" - A contour integral eigensolver based on the
    1440:    Sakurai-Sugiura scheme.

    1442:    Notes:
    1443:    This solver is based on the numerical contour integration idea
    1444:    proposed initially by {cite:t}`Sak03` and improved later by adding
    1445:    a Rayleigh-Ritz projection step {cite:p}`Sak07`.

    1447:    Contour integral methods are able to compute all eigenvalues
    1448:    lying inside a region of the complex plane. Use `EPSGetRG()` to
    1449:    specify the region. However, the computational cost is usually high
    1450:    because multiple linear systems must be solved. For this, we can
    1451:    use the `KSP` object inside `ST`, or several independent `KSP`s,
    1452:    see `EPSCISSSetUseST()`.

    1454:    Details of the implementation in SLEPc can be found in {cite:p}`Mae16`.

    1456:    Level: beginner

    1458: .seealso: [](ch:eps), `EPS`, `EPSType`, `EPSSetType()`, `EPSGetRG()`
    1459: M*/
    1460: SLEPC_EXTERN PetscErrorCode EPSCreate_CISS(EPS eps)
    1461: {
    1462:   EPS_CISS       *ctx = (EPS_CISS*)eps->data;

    1464:   PetscFunctionBegin;
    1465:   PetscCall(PetscNew(&ctx));
    1466:   eps->data = ctx;

    1468:   eps->useds = PETSC_TRUE;
    1469:   eps->categ = EPS_CATEGORY_CONTOUR;

    1471:   eps->ops->solve          = EPSSolve_CISS;
    1472:   eps->ops->setup          = EPSSetUp_CISS;
    1473:   eps->ops->setupsort      = EPSSetUpSort_CISS;
    1474:   eps->ops->setfromoptions = EPSSetFromOptions_CISS;
    1475:   eps->ops->destroy        = EPSDestroy_CISS;
    1476:   eps->ops->reset          = EPSReset_CISS;
    1477:   eps->ops->view           = EPSView_CISS;
    1478:   eps->ops->computevectors = EPSComputeVectors_CISS;
    1479:   eps->ops->setdefaultst   = EPSSetDefaultST_CISS;

    1481:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetSizes_C",EPSCISSSetSizes_CISS));
    1482:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetSizes_C",EPSCISSGetSizes_CISS));
    1483:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetThreshold_C",EPSCISSSetThreshold_CISS));
    1484:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetThreshold_C",EPSCISSGetThreshold_CISS));
    1485:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetRefinement_C",EPSCISSSetRefinement_CISS));
    1486:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetRefinement_C",EPSCISSGetRefinement_CISS));
    1487:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetUseST_C",EPSCISSSetUseST_CISS));
    1488:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetUseST_C",EPSCISSGetUseST_CISS));
    1489:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetQuadRule_C",EPSCISSSetQuadRule_CISS));
    1490:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetQuadRule_C",EPSCISSGetQuadRule_CISS));
    1491:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetExtraction_C",EPSCISSSetExtraction_CISS));
    1492:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetExtraction_C",EPSCISSGetExtraction_CISS));
    1493:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetKSPs_C",EPSCISSGetKSPs_CISS));

    1495:   /* set default values of parameters */
    1496:   ctx->N                  = 32;
    1497:   ctx->L                  = 16;
    1498:   ctx->M                  = ctx->N/4;
    1499:   ctx->delta              = SLEPC_DEFAULT_TOL*1e-4;
    1500:   ctx->L_max              = 64;
    1501:   ctx->spurious_threshold = PetscSqrtReal(SLEPC_DEFAULT_TOL);
    1502:   ctx->usest              = PETSC_TRUE;
    1503:   ctx->usest_set          = PETSC_FALSE;
    1504:   ctx->isreal             = PETSC_FALSE;
    1505:   ctx->refine_inner       = 0;
    1506:   ctx->refine_blocksize   = 0;
    1507:   ctx->npart              = 1;
    1508:   ctx->quad               = (EPSCISSQuadRule)0;
    1509:   ctx->extraction         = EPS_CISS_EXTRACTION_RITZ;
    1510:   PetscFunctionReturn(PETSC_SUCCESS);
    1511: }