Date: 2024-09-25T09:33:20+00:00

Actual source code: power.c
slepc-3.21.2 2024-09-25
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      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: "power"

     13:    Method: Power Iteration

     15:    Algorithm:

     17:        This solver implements the power iteration for finding dominant
     18:        eigenpairs. It also includes the following well-known methods:
     19:        - Inverse Iteration: when used in combination with shift-and-invert
     20:          spectral transformation.
     21:        - Rayleigh Quotient Iteration (RQI): also with shift-and-invert plus
     22:          a variable shift.

     24:        It can also be used for nonlinear inverse iteration on the problem
     25:        A(x)*x=lambda*B(x)*x, where A and B are not constant but depend on x.

     27:    References:

     29:        [1] "Single Vector Iteration Methods in SLEPc", SLEPc Technical Report
     30:            STR-2, available at https://slepc.upv.es.
     31: */

     33: #include <slepc/private/epsimpl.h>
     34: #include <slepcblaslapack.h>
     35: /* petsc headers */
     36: #include <petscdm.h>
     37: #include <petscsnes.h>

     39: static PetscErrorCode EPSPowerFormFunction_Update(SNES,Vec,Vec,void*);
     40: static PetscErrorCode EPSSolve_Power(EPS);
     41: static PetscErrorCode EPSSolve_TS_Power(EPS);

     43: typedef struct {
     44:   EPSPowerShiftType shift_type;
     45:   PetscBool         nonlinear;
     46:   PetscBool         update;
     47:   PetscBool         sign_normalization;
     48:   SNES              snes;
     49:   PetscErrorCode    (*formFunctionB)(SNES,Vec,Vec,void*);
     50:   void              *formFunctionBctx;
     51:   PetscErrorCode    (*formFunctionA)(SNES,Vec,Vec,void*);
     52:   void              *formFunctionActx;
     53:   PetscErrorCode    (*formFunctionAB)(SNES,Vec,Vec,Vec,void*);
     54:   PetscErrorCode    (*formNorm)(SNES,Vec,PetscReal*,void*);
     55:   void              *formNormCtx;
     56:   PetscInt          idx;  /* index of the first nonzero entry in the iteration vector */
     57:   PetscMPIInt       p;    /* process id of the owner of idx */
     58:   PetscReal         norm0; /* norm of initial vector */
     59: } EPS_POWER;

     61: static PetscErrorCode SNESMonitor_PowerUpdate(SNES snes,PetscInt its,PetscReal fnorm,void *ctx)
     62: {
     63:   EPS            eps;

     65:   PetscFunctionBegin;
     66:   PetscCall(PetscObjectQuery((PetscObject)snes,"eps",(PetscObject *)&eps));
     67:   PetscCheck(eps,PetscObjectComm((PetscObject)snes),PETSC_ERR_ARG_NULL,"No composed EPS");
     68:   /* Call EPS monitor on each SNES iteration */
     69:   PetscCall(EPSMonitor(eps,its,eps->nconv,eps->eigr,eps->eigi,eps->errest,PetscMin(eps->nconv+1,eps->nev)));
     70:   PetscFunctionReturn(PETSC_SUCCESS);
     71: }

     73: static PetscErrorCode EPSSetUp_Power(EPS eps)
     74: {
     75:   EPS_POWER      *power = (EPS_POWER*)eps->data;
     76:   STMatMode      mode;
     77:   Mat            A,B,P;
     78:   Vec            res;
     79:   PetscContainer container;
     80:   PetscErrorCode (*formFunctionA)(SNES,Vec,Vec,void*);
     81:   PetscErrorCode (*formJacobianA)(SNES,Vec,Mat,Mat,void*);
     82:   PetscErrorCode (*formNorm)(SNES,Vec,PetscReal*,void*);
     83:   void           *ctx;

     85:   PetscFunctionBegin;
     86:   if (eps->ncv!=PETSC_DEFAULT) {
     87:     PetscCheck(eps->ncv>=eps->nev,PetscObjectComm((PetscObject)eps),PETSC_ERR_USER_INPUT,"The value of ncv must be at least nev");
     88:   } else eps->ncv = eps->nev;
     89:   if (eps->mpd!=PETSC_DEFAULT) PetscCall(PetscInfo(eps,"Warning: parameter mpd ignored\n"));
     90:   if (eps->max_it==PETSC_DEFAULT) {
     91:     /* SNES will directly return the solution for us, and we need to do only one iteration */
     92:     if (power->nonlinear && power->update) eps->max_it = 1;
     93:     else eps->max_it = PetscMax(1000*eps->nev,100*eps->n);
     94:   }
     95:   if (!eps->which) PetscCall(EPSSetWhichEigenpairs_Default(eps));
     96:   PetscCheck(eps->which==EPS_LARGEST_MAGNITUDE || eps->which==EPS_TARGET_MAGNITUDE,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"This solver supports only largest magnitude or target magnitude eigenvalues");
     97:   if (power->shift_type != EPS_POWER_SHIFT_CONSTANT) {
     98:     PetscCheck(!power->nonlinear,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"Variable shifts not allowed in nonlinear problems");
     99:     EPSCheckSinvertCayleyCondition(eps,PETSC_TRUE," (with variable shifts)");
    100:     PetscCall(STGetMatMode(eps->st,&mode));
    101:     PetscCheck(mode!=ST_MATMODE_INPLACE,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"ST matrix mode inplace does not work with variable shifts");
    102:   }
    103:   EPSCheckUnsupported(eps,EPS_FEATURE_BALANCE | EPS_FEATURE_ARBITRARY | EPS_FEATURE_REGION | EPS_FEATURE_CONVERGENCE);
    104:   EPSCheckIgnored(eps,EPS_FEATURE_EXTRACTION);
    105:   PetscCall(EPSAllocateSolution(eps,0));
    106:   PetscCall(EPS_SetInnerProduct(eps));

    108:   if (power->nonlinear) {
    109:     PetscCheck(eps->nev==1,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"Nonlinear inverse iteration cannot compute more than one eigenvalue");
    110:     PetscCall(EPSSetWorkVecs(eps,3));
    111:     PetscCheck(!power->update || eps->max_it==1,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"More than one iteration is not allowed for Newton eigensolver (SNES)");

    113:     /* Set up SNES solver */
    114:     /* If SNES was setup, we need to reset it so that it will be consistent with the current EPS */
    115:     if (power->snes) PetscCall(SNESReset(power->snes));
    116:     else PetscCall(EPSPowerGetSNES(eps,&power->snes));

    118:     /* For nonlinear solver (Newton), we should scale the initial vector back.
    119:        The initial vector will be scaled in EPSSetUp. */
    120:     if (eps->IS) PetscCall(VecNorm(eps->IS[0],NORM_2,&power->norm0));

    122:     PetscCall(EPSGetOperators(eps,&A,&B));

    124:     /* form function */
    125:     PetscCall(PetscObjectQueryFunction((PetscObject)A,"formFunction",&formFunctionA));
    126:     PetscCheck(formFunctionA,PetscObjectComm((PetscObject)eps),PETSC_ERR_USER,"For nonlinear inverse iteration you must compose a callback function 'formFunction' in matrix A");
    127:     PetscCall(PetscObjectQuery((PetscObject)A,"formFunctionCtx",(PetscObject*)&container));
    128:     if (container) PetscCall(PetscContainerGetPointer(container,&ctx));
    129:     else ctx = NULL;
    130:     PetscCall(MatCreateVecs(A,&res,NULL));
    131:     power->formFunctionA = formFunctionA;
    132:     power->formFunctionActx = ctx;
    133:     if (power->update) {
    134:       PetscCall(SNESSetFunction(power->snes,res,EPSPowerFormFunction_Update,ctx));
    135:       PetscCall(PetscObjectQueryFunction((PetscObject)A,"formFunctionAB",&power->formFunctionAB));
    136:       PetscCall(SNESMonitorSet(power->snes,SNESMonitor_PowerUpdate,NULL,NULL));
    137:     }
    138:     else PetscCall(SNESSetFunction(power->snes,res,formFunctionA,ctx));
    139:     PetscCall(VecDestroy(&res));

    141:     /* form Jacobian */
    142:     PetscCall(PetscObjectQueryFunction((PetscObject)A,"formJacobian",&formJacobianA));
    143:     PetscCheck(formJacobianA,PetscObjectComm((PetscObject)eps),PETSC_ERR_USER,"For nonlinear inverse iteration you must compose a callback function 'formJacobian' in matrix A");
    144:     PetscCall(PetscObjectQuery((PetscObject)A,"formJacobianCtx",(PetscObject*)&container));
    145:     if (container) PetscCall(PetscContainerGetPointer(container,&ctx));
    146:     else ctx = NULL;
    147:     /* This allows users to compute a different preconditioning matrix than A.
    148:      * It is useful when A and B are shell matrices.
    149:      */
    150:     PetscCall(STGetPreconditionerMat(eps->st,&P));
    151:     /* If users do not provide a matrix, we simply use A */
    152:     PetscCall(SNESSetJacobian(power->snes,A,P? P:A,formJacobianA,ctx));
    153:     PetscCall(SNESSetFromOptions(power->snes));
    154:     PetscCall(SNESSetUp(power->snes));

    156:     ctx = NULL;
    157:     formNorm = NULL;
    158:     if (B) {
    159:       PetscCall(PetscObjectQueryFunction((PetscObject)B,"formFunction",&power->formFunctionB));
    160:       PetscCall(PetscObjectQuery((PetscObject)B,"formFunctionCtx",(PetscObject*)&container));
    161:       if (power->formFunctionB && container) PetscCall(PetscContainerGetPointer(container,&power->formFunctionBctx));
    162:       else power->formFunctionBctx = NULL;

    164:       /* form norm */
    165:       PetscCall(PetscObjectQueryFunction((PetscObject)B,"formNorm",&formNorm));
    166:       if (formNorm) {
    167:         PetscCall(PetscObjectQuery((PetscObject)B,"formNormCtx",(PetscObject*)&container));
    168:         if (container) PetscCall(PetscContainerGetPointer(container,&ctx));
    169:       }
    170:     }
    171:     power->formNorm = formNorm;
    172:     power->formNormCtx = ctx;
    173:   } else {
    174:     if (eps->twosided) PetscCall(EPSSetWorkVecs(eps,3));
    175:     else PetscCall(EPSSetWorkVecs(eps,2));
    176:     PetscCall(DSSetType(eps->ds,DSNHEP));
    177:     PetscCall(DSAllocate(eps->ds,eps->nev));
    178:   }
    179:   /* dispatch solve method */
    180:   if (eps->twosided) {
    181:     PetscCheck(!power->nonlinear,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"Nonlinear inverse iteration does not have two-sided variant");
    182:     PetscCheck(power->shift_type!=EPS_POWER_SHIFT_WILKINSON,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"Two-sided variant does not support Wilkinson shifts");
    183:     eps->ops->solve = EPSSolve_TS_Power;
    184:   } else eps->ops->solve = EPSSolve_Power;
    185:   PetscFunctionReturn(PETSC_SUCCESS);
    186: }

    188: /*
    189:    Find the index of the first nonzero entry of x, and the process that owns it.
    190: */
    191: static PetscErrorCode FirstNonzeroIdx(Vec x,PetscInt *idx,PetscMPIInt *p)
    192: {
    193:   PetscInt          i,first,last,N;
    194:   PetscLayout       map;
    195:   const PetscScalar *xx;

    197:   PetscFunctionBegin;
    198:   PetscCall(VecGetSize(x,&N));
    199:   PetscCall(VecGetOwnershipRange(x,&first,&last));
    200:   PetscCall(VecGetArrayRead(x,&xx));
    201:   for (i=first;i<last;i++) {
    202:     if (PetscAbsScalar(xx[i-first])>10*PETSC_MACHINE_EPSILON) break;
    203:   }
    204:   PetscCall(VecRestoreArrayRead(x,&xx));
    205:   if (i==last) i=N;
    206:   PetscCall(MPIU_Allreduce(&i,idx,1,MPIU_INT,MPI_MIN,PetscObjectComm((PetscObject)x)));
    207:   PetscCheck(*idx!=N,PetscObjectComm((PetscObject)x),PETSC_ERR_PLIB,"Zero vector found");
    208:   PetscCall(VecGetLayout(x,&map));
    209:   PetscCall(PetscLayoutFindOwner(map,*idx,p));
    210:   PetscFunctionReturn(PETSC_SUCCESS);
    211: }

    213: /*
    214:    Normalize a vector x with respect to a given norm as well as, optionally, the
    215:    sign of the first nonzero entry (assumed to be idx in process p).
    216: */
    217: static PetscErrorCode Normalize(Vec x,PetscReal norm,PetscInt idx,PetscMPIInt p,PetscBool sign_normalization,PetscScalar *sign)
    218: {
    219:   PetscScalar       alpha=1.0;
    220:   PetscInt          first,last;
    221:   PetscReal         absv;
    222:   const PetscScalar *xx;

    224:   PetscFunctionBegin;
    225:   if (sign_normalization) {
    226:     PetscCall(VecGetOwnershipRange(x,&first,&last));
    227:     if (idx>=first && idx<last) {
    228:       PetscCall(VecGetArrayRead(x,&xx));
    229:       absv = PetscAbsScalar(xx[idx-first]);
    230:       if (absv>10*PETSC_MACHINE_EPSILON) alpha = xx[idx-first]/absv;
    231:       PetscCall(VecRestoreArrayRead(x,&xx));
    232:     }
    233:     PetscCallMPI(MPI_Bcast(&alpha,1,MPIU_SCALAR,p,PetscObjectComm((PetscObject)x)));
    234:   }
    235:   if (sign) *sign = alpha;
    236:   alpha *= norm;
    237:   PetscCall(VecScale(x,1.0/alpha));
    238:   PetscFunctionReturn(PETSC_SUCCESS);
    239: }

    241: static PetscErrorCode EPSPowerUpdateFunctionB(EPS eps,Vec x,Vec Bx)
    242: {
    243:   EPS_POWER      *power = (EPS_POWER*)eps->data;
    244:   Mat            B;

    246:   PetscFunctionBegin;
    247:   PetscCall(STResetMatrixState(eps->st));
    248:   PetscCall(EPSGetOperators(eps,NULL,&B));
    249:   if (B) {
    250:     if (power->formFunctionB) PetscCall((*power->formFunctionB)(power->snes,x,Bx,power->formFunctionBctx));
    251:     else PetscCall(MatMult(B,x,Bx));
    252:   } else PetscCall(VecCopy(x,Bx));
    253:   PetscFunctionReturn(PETSC_SUCCESS);
    254: }

    256: static PetscErrorCode EPSPowerUpdateFunctionA(EPS eps,Vec x,Vec Ax)
    257: {
    258:   EPS_POWER      *power = (EPS_POWER*)eps->data;
    259:   Mat            A;

    261:   PetscFunctionBegin;
    262:   PetscCall(STResetMatrixState(eps->st));
    263:   PetscCall(EPSGetOperators(eps,&A,NULL));
    264:   PetscCheck(A,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_NULL,"Matrix A is required for an eigenvalue problem");
    265:   if (power->formFunctionA) PetscCall((*power->formFunctionA)(power->snes,x,Ax,power->formFunctionActx));
    266:   else PetscCall(MatMult(A,x,Ax));
    267:   PetscFunctionReturn(PETSC_SUCCESS);
    268: }

    270: static PetscErrorCode EPSPowerFormFunction_Update(SNES snes,Vec x,Vec y,void *ctx)
    271: {
    272:   EPS            eps;
    273:   PetscReal      bx;
    274:   Vec            Bx;
    275:   PetscScalar    sign;
    276:   EPS_POWER      *power;

    278:   PetscFunctionBegin;
    279:   PetscCall(PetscObjectQuery((PetscObject)snes,"eps",(PetscObject *)&eps));
    280:   PetscCheck(eps,PetscObjectComm((PetscObject)snes),PETSC_ERR_ARG_NULL,"No composed EPS");
    281:   PetscCall(STResetMatrixState(eps->st));
    282:   power = (EPS_POWER*)eps->data;
    283:   Bx = eps->work[2];
    284:   if (power->formFunctionAB) PetscCall((*power->formFunctionAB)(snes,x,y,Bx,ctx));
    285:   else {
    286:     PetscCall(EPSPowerUpdateFunctionA(eps,x,y));
    287:     PetscCall(EPSPowerUpdateFunctionB(eps,x,Bx));
    288:   }
    289:   if (power->formNorm) PetscCall((*power->formNorm)(snes,Bx,&bx,power->formNormCtx));
    290:   else PetscCall(VecNorm(Bx,NORM_2,&bx));
    291:   PetscCall(Normalize(Bx,bx,power->idx,power->p,power->sign_normalization,&sign));
    292:   PetscCall(VecAXPY(y,-1.0,Bx));
    293:   /* Keep tracking eigenvalue update. It would be useful when we want to monitor solver progress via snes monitor. */
    294:   eps->eigr[(eps->nconv < eps->nev)? eps->nconv:(eps->nconv-1)] = 1.0/(bx*sign);
    295:   PetscFunctionReturn(PETSC_SUCCESS);
    296: }

    298: /*
    299:    Use SNES to compute y = A^{-1}*B*x for the nonlinear problem
    300: */
    301: static PetscErrorCode EPSPowerApply_SNES(EPS eps,Vec x,Vec y)
    302: {
    303:   EPS_POWER      *power = (EPS_POWER*)eps->data;
    304:   Vec            Bx;

    306:   PetscFunctionBegin;
    307:   PetscCall(VecCopy(x,y));
    308:   if (power->update) PetscCall(SNESSolve(power->snes,NULL,y));
    309:   else {
    310:     Bx = eps->work[2];
    311:     PetscCall(SNESSolve(power->snes,Bx,y));
    312:   }
    313:   PetscFunctionReturn(PETSC_SUCCESS);
    314: }

    316: /*
    317:    Use nonlinear inverse power to compute an initial guess
    318: */
    319: static PetscErrorCode EPSPowerComputeInitialGuess_Update(EPS eps)
    320: {
    321:   EPS            powereps;
    322:   Mat            A,B,P;
    323:   Vec            v1,v2;
    324:   SNES           snes;
    325:   DM             dm,newdm;
    326:   PetscBool      sign_normalization;

    328:   PetscFunctionBegin;
    329:   PetscCall(EPSCreate(PetscObjectComm((PetscObject)eps),&powereps));
    330:   PetscCall(EPSGetOperators(eps,&A,&B));
    331:   PetscCall(EPSSetType(powereps,EPSPOWER));
    332:   PetscCall(EPSSetOperators(powereps,A,B));
    333:   PetscCall(EPSSetTolerances(powereps,1e-6,4));
    334:   PetscCall(EPSSetOptionsPrefix(powereps,((PetscObject)eps)->prefix));
    335:   PetscCall(EPSAppendOptionsPrefix(powereps,"init_"));
    336:   PetscCall(EPSSetProblemType(powereps,EPS_GNHEP));
    337:   PetscCall(EPSSetWhichEigenpairs(powereps,EPS_TARGET_MAGNITUDE));
    338:   PetscCall(EPSPowerSetNonlinear(powereps,PETSC_TRUE));
    339:   PetscCall(STGetPreconditionerMat(eps->st,&P));
    340:   /* attach dm to initial solve */
    341:   PetscCall(EPSPowerGetSNES(eps,&snes));
    342:   PetscCall(SNESGetDM(snes,&dm));
    343:   /* use  dmshell to temporarily store snes context */
    344:   PetscCall(DMCreate(PetscObjectComm((PetscObject)eps),&newdm));
    345:   PetscCall(DMSetType(newdm,DMSHELL));
    346:   PetscCall(DMSetUp(newdm));
    347:   PetscCall(DMCopyDMSNES(dm,newdm));
    348:   PetscCall(EPSPowerGetSNES(powereps,&snes));
    349:   PetscCall(SNESSetDM(snes,dm));
    350:   PetscCall(EPSPowerGetSignNormalization(eps,&sign_normalization));
    351:   PetscCall(EPSPowerSetSignNormalization(powereps,sign_normalization));
    352:   PetscCall(EPSSetFromOptions(powereps));
    353:   if (P) PetscCall(STSetPreconditionerMat(powereps->st,P));
    354:   PetscCall(EPSSolve(powereps));
    355:   PetscCall(BVGetColumn(eps->V,0,&v2));
    356:   PetscCall(BVGetColumn(powereps->V,0,&v1));
    357:   PetscCall(VecCopy(v1,v2));
    358:   PetscCall(BVRestoreColumn(powereps->V,0,&v1));
    359:   PetscCall(BVRestoreColumn(eps->V,0,&v2));
    360:   PetscCall(EPSDestroy(&powereps));
    361:   /* restore context back to the old nonlinear solver */
    362:   PetscCall(DMCopyDMSNES(newdm,dm));
    363:   PetscCall(DMDestroy(&newdm));
    364:   PetscFunctionReturn(PETSC_SUCCESS);
    365: }

    367: static PetscErrorCode EPSSolve_Power(EPS eps)
    368: {
    369:   EPS_POWER           *power = (EPS_POWER*)eps->data;
    370:   PetscInt            k,ld;
    371:   Vec                 v,y,e,Bx;
    372:   Mat                 A;
    373:   KSP                 ksp;
    374:   PetscReal           relerr,norm,norm1,rt1,rt2,cs1;
    375:   PetscScalar         theta,rho,delta,sigma,alpha2,beta1,sn1,*T,sign;
    376:   PetscBool           breakdown;
    377:   KSPConvergedReason  reason;
    378:   SNESConvergedReason snesreason;

    380:   PetscFunctionBegin;
    381:   e = eps->work[0];
    382:   y = eps->work[1];
    383:   if (power->nonlinear) Bx = eps->work[2];
    384:   else Bx = NULL;

    386:   if (power->shift_type != EPS_POWER_SHIFT_CONSTANT) PetscCall(STGetKSP(eps->st,&ksp));
    387:   if (power->nonlinear) {
    388:     PetscCall(PetscObjectCompose((PetscObject)power->snes,"eps",(PetscObject)eps));
    389:     /* Compute an initial guess only when users do not provide one */
    390:     if (power->update && !eps->nini) PetscCall(EPSPowerComputeInitialGuess_Update(eps));
    391:   } else PetscCall(DSGetLeadingDimension(eps->ds,&ld));
    392:   if (!power->update) PetscCall(EPSGetStartVector(eps,0,NULL));
    393:   if (power->nonlinear) {
    394:     PetscCall(BVGetColumn(eps->V,0,&v));
    395:     if (eps->nini) {
    396:       /* We scale the initial vector back if the initial vector was provided by users */
    397:       PetscCall(VecScale(v,power->norm0));
    398:     }
    399:     /* Do a couple things:
    400:      * 1) Determine the first non-zero index for Bx and the proc that owns it. This will be
    401:      *    used if performing normalization by the sign of the first nonzero element of Bx.
    402:      * 2) Scale Bx by its norm. For non-update power iterations, Bx (in code terms) is used
    403:      *    as the RHS argument to SNESSolve. And recall that the formula for generalized
    404:      *    inverse power iterations in this case is: (Ax)_n = (Bx)_{n-1}/|(Bx)_{n-1}| (in
    405:      *    math terms)
    406:      */
    407:     PetscCall(EPSPowerUpdateFunctionB(eps,v,Bx));
    408:     PetscCall(BVRestoreColumn(eps->V,0,&v));
    409:     if (power->formNorm) PetscCall((*power->formNorm)(power->snes,Bx,&norm,power->formNormCtx));
    410:     else PetscCall(VecNorm(Bx,NORM_2,&norm));
    411:     PetscCall(FirstNonzeroIdx(Bx,&power->idx,&power->p));
    412:     PetscCall(Normalize(Bx,norm,power->idx,power->p,power->sign_normalization,NULL));
    413:   }

    415:   PetscCall(STGetShift(eps->st,&sigma));    /* original shift */
    416:   rho = sigma;

    418:   while (eps->reason == EPS_CONVERGED_ITERATING) {
    419:     eps->its++;
    420:     k = eps->nconv;

    422:     /* y = OP v */
    423:     PetscCall(BVGetColumn(eps->V,k,&v));
    424:     if (power->nonlinear) PetscCall(EPSPowerApply_SNES(eps,v,y));
    425:     else PetscCall(STApply(eps->st,v,y));
    426:     PetscCall(BVRestoreColumn(eps->V,k,&v));

    428:     /* purge previously converged eigenvectors */
    429:     if (PetscUnlikely(power->nonlinear)) {
    430:       /* We do not need to call this for Newton eigensolver since eigenvalue is
    431:        * updated in function evaluations.
    432:        */
    433:       if (!power->update) {
    434:         PetscCall(EPSPowerUpdateFunctionB(eps,y,Bx));
    435:         if (power->formNorm) PetscCall((*power->formNorm)(power->snes,Bx,&norm,power->formNormCtx));
    436:         else PetscCall(VecNorm(Bx,NORM_2,&norm));
    437:         PetscCall(Normalize(Bx,norm,power->idx,power->p,power->sign_normalization,&sign));
    438:       }
    439:     } else {
    440:       PetscCall(DSGetArray(eps->ds,DS_MAT_A,&T));
    441:       PetscCall(BVSetActiveColumns(eps->V,0,k));
    442:       PetscCall(BVOrthogonalizeVec(eps->V,y,T+k*ld,&norm,NULL));
    443:     }

    445:     /* theta = (v,y)_B */
    446:     PetscCall(BVSetActiveColumns(eps->V,k,k+1));
    447:     PetscCall(BVDotVec(eps->V,y,&theta));
    448:     if (!power->nonlinear) {
    449:       T[k+k*ld] = theta;
    450:       PetscCall(DSRestoreArray(eps->ds,DS_MAT_A,&T));
    451:     }

    453:     /* Eigenvalue is already stored in function evaluations.
    454:      * Assign eigenvalue to theta to make the rest of the code consistent
    455:      */
    456:     if (power->update) theta = eps->eigr[eps->nconv];
    457:     else if (power->nonlinear) theta = 1.0/(norm*sign); /* Eigenvalue: 1/|Bx| */

    459:     if (power->shift_type == EPS_POWER_SHIFT_CONSTANT) { /* direct & inverse iteration */

    461:       /* approximate eigenvalue is the Rayleigh quotient */
    462:       eps->eigr[eps->nconv] = theta;

    464:       /**
    465:        * If the Newton method (update, SNES) is used, we do not compute "relerr"
    466:        * since SNES determines the convergence.
    467:        */
    468:       if (PetscUnlikely(power->update)) relerr = 0.;
    469:       else {
    470:         /* compute relative error as ||y-theta v||_2/|theta| */
    471:         PetscCall(VecCopy(y,e));
    472:         PetscCall(BVGetColumn(eps->V,k,&v));
    473:         PetscCall(VecAXPY(e,power->nonlinear?-1.0:-theta,v));
    474:         PetscCall(BVRestoreColumn(eps->V,k,&v));
    475:         PetscCall(VecNorm(e,NORM_2,&relerr));
    476:         if (PetscUnlikely(power->nonlinear)) relerr *= PetscAbsScalar(theta);
    477:         else relerr /= PetscAbsScalar(theta);
    478:       }

    480:     } else {  /* RQI */

    482:       /* delta = ||y||_B */
    483:       delta = norm;

    485:       /* compute relative error */
    486:       if (rho == 0.0) relerr = PETSC_MAX_REAL;
    487:       else relerr = 1.0 / (norm*PetscAbsScalar(rho));

    489:       /* approximate eigenvalue is the shift */
    490:       eps->eigr[eps->nconv] = rho;

    492:       /* compute new shift */
    493:       if (relerr<eps->tol) {
    494:         rho = sigma;  /* if converged, restore original shift */
    495:         PetscCall(STSetShift(eps->st,rho));
    496:       } else {
    497:         rho = rho + PetscConj(theta)/(delta*delta);  /* Rayleigh quotient R(v) */
    498:         if (power->shift_type == EPS_POWER_SHIFT_WILKINSON) {
    499:           /* beta1 is the norm of the residual associated with R(v) */
    500:           PetscCall(BVGetColumn(eps->V,k,&v));
    501:           PetscCall(VecAXPY(v,-PetscConj(theta)/(delta*delta),y));
    502:           PetscCall(BVRestoreColumn(eps->V,k,&v));
    503:           PetscCall(BVScaleColumn(eps->V,k,1.0/delta));
    504:           PetscCall(BVNormColumn(eps->V,k,NORM_2,&norm1));
    505:           beta1 = norm1;

    507:           /* alpha2 = (e'*A*e)/(beta1*beta1), where e is the residual */
    508:           PetscCall(STGetMatrix(eps->st,0,&A));
    509:           PetscCall(BVGetColumn(eps->V,k,&v));
    510:           PetscCall(MatMult(A,v,e));
    511:           PetscCall(VecDot(v,e,&alpha2));
    512:           PetscCall(BVRestoreColumn(eps->V,k,&v));
    513:           alpha2 = alpha2 / (beta1 * beta1);

    515:           /* choose the eigenvalue of [rho beta1; beta1 alpha2] closest to rho */
    516:           PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF));
    517:           PetscCallBLAS("LAPACKlaev2",LAPACKlaev2_(&rho,&beta1,&alpha2,&rt1,&rt2,&cs1,&sn1));
    518:           PetscCall(PetscFPTrapPop());
    519:           if (PetscAbsScalar(rt1-rho) < PetscAbsScalar(rt2-rho)) rho = rt1;
    520:           else rho = rt2;
    521:         }
    522:         /* update operator according to new shift */
    523:         PetscCall(KSPSetErrorIfNotConverged(ksp,PETSC_FALSE));
    524:         PetscCall(STSetShift(eps->st,rho));
    525:         PetscCall(KSPGetConvergedReason(ksp,&reason));
    526:         if (reason) {
    527:           PetscCall(PetscInfo(eps,"Factorization failed, repeat with a perturbed shift\n"));
    528:           rho *= 1+10*PETSC_MACHINE_EPSILON;
    529:           PetscCall(STSetShift(eps->st,rho));
    530:           PetscCall(KSPGetConvergedReason(ksp,&reason));
    531:           PetscCheck(!reason,PetscObjectComm((PetscObject)ksp),PETSC_ERR_CONV_FAILED,"Second factorization failed");
    532:         }
    533:         PetscCall(KSPSetErrorIfNotConverged(ksp,PETSC_TRUE));
    534:       }
    535:     }
    536:     eps->errest[eps->nconv] = relerr;

    538:     /* normalize */
    539:     if (!power->nonlinear) PetscCall(Normalize(y,norm,power->idx,power->p,power->sign_normalization,NULL));
    540:     PetscCall(BVInsertVec(eps->V,k,y));

    542:     if (PetscUnlikely(power->update)) {
    543:       PetscCall(SNESGetConvergedReason(power->snes,&snesreason));
    544:       /* For Newton eigensolver, we are ready to return once SNES converged. */
    545:       if (snesreason>0) eps->nconv = 1;
    546:     } else if (PetscUnlikely(relerr<eps->tol)) {   /* accept eigenpair */
    547:       eps->nconv = eps->nconv + 1;
    548:       if (eps->nconv<eps->nev) {
    549:         PetscCall(EPSGetStartVector(eps,eps->nconv,&breakdown));
    550:         if (breakdown) {
    551:           eps->reason = EPS_DIVERGED_BREAKDOWN;
    552:           PetscCall(PetscInfo(eps,"Unable to generate more start vectors\n"));
    553:           break;
    554:         }
    555:       }
    556:     }
    557:     /* For Newton eigensolver, monitor will be called from SNES monitor */
    558:     if (!power->update) PetscCall(EPSMonitor(eps,eps->its,eps->nconv,eps->eigr,eps->eigi,eps->errest,PetscMin(eps->nconv+1,eps->nev)));
    559:     PetscCall((*eps->stopping)(eps,eps->its,eps->max_it,eps->nconv,eps->nev,&eps->reason,eps->stoppingctx));

    561:     /**
    562:      * When a customized stopping test is used, and reason can be set to be converged (EPS_CONVERGED_USER).
    563:      * In this case, we need to increase eps->nconv to "1" so users can retrieve the solution.
    564:      */
    565:     if (PetscUnlikely(power->nonlinear && eps->reason>0)) eps->nconv = 1;
    566:   }

    568:   if (power->nonlinear) PetscCall(PetscObjectCompose((PetscObject)power->snes,"eps",NULL));
    569:   else {
    570:     PetscCall(DSSetDimensions(eps->ds,eps->nconv,0,0));
    571:     PetscCall(DSSetState(eps->ds,DS_STATE_RAW));
    572:   }
    573:   PetscFunctionReturn(PETSC_SUCCESS);
    574: }

    576: static PetscErrorCode EPSSolve_TS_Power(EPS eps)
    577: {
    578:   EPS_POWER          *power = (EPS_POWER*)eps->data;
    579:   PetscInt           k,ld;
    580:   Vec                v,w,y,e,z;
    581:   KSP                ksp;
    582:   PetscReal          relerr=1.0,relerrl,delta;
    583:   PetscScalar        theta,rho,alpha,sigma;
    584:   PetscBool          breakdown,breakdownl;
    585:   KSPConvergedReason reason;

    587:   PetscFunctionBegin;
    588:   e = eps->work[0];
    589:   v = eps->work[1];
    590:   w = eps->work[2];

    592:   if (power->shift_type != EPS_POWER_SHIFT_CONSTANT) PetscCall(STGetKSP(eps->st,&ksp));
    593:   PetscCall(DSGetLeadingDimension(eps->ds,&ld));
    594:   PetscCall(EPSGetStartVector(eps,0,NULL));
    595:   PetscCall(EPSGetLeftStartVector(eps,0,NULL));
    596:   PetscCall(BVBiorthonormalizeColumn(eps->V,eps->W,0,NULL));
    597:   PetscCall(BVCopyVec(eps->V,0,v));
    598:   PetscCall(BVCopyVec(eps->W,0,w));
    599:   PetscCall(STGetShift(eps->st,&sigma));    /* original shift */
    600:   rho = sigma;

    602:   while (eps->reason == EPS_CONVERGED_ITERATING) {
    603:     eps->its++;
    604:     k = eps->nconv;

    606:     /* y = OP v, z = OP' w */
    607:     PetscCall(BVGetColumn(eps->V,k,&y));
    608:     PetscCall(STApply(eps->st,v,y));
    609:     PetscCall(BVRestoreColumn(eps->V,k,&y));
    610:     PetscCall(BVGetColumn(eps->W,k,&z));
    611:     PetscCall(STApplyHermitianTranspose(eps->st,w,z));
    612:     PetscCall(BVRestoreColumn(eps->W,k,&z));

    614:     /* purge previously converged eigenvectors */
    615:     PetscCall(BVBiorthogonalizeColumn(eps->V,eps->W,k));

    617:     /* theta = (w,y)_B */
    618:     PetscCall(BVSetActiveColumns(eps->V,k,k+1));
    619:     PetscCall(BVDotVec(eps->V,w,&theta));
    620:     theta = PetscConj(theta);

    622:     if (power->shift_type == EPS_POWER_SHIFT_CONSTANT) { /* direct & inverse iteration */

    624:       /* approximate eigenvalue is the Rayleigh quotient */
    625:       eps->eigr[eps->nconv] = theta;

    627:       /* compute relative errors as ||y-theta v||_2/|theta| and ||z-conj(theta) w||_2/|theta|*/
    628:       PetscCall(BVCopyVec(eps->V,k,e));
    629:       PetscCall(VecAXPY(e,-theta,v));
    630:       PetscCall(VecNorm(e,NORM_2,&relerr));
    631:       PetscCall(BVCopyVec(eps->W,k,e));
    632:       PetscCall(VecAXPY(e,-PetscConj(theta),w));
    633:       PetscCall(VecNorm(e,NORM_2,&relerrl));
    634:       relerr = PetscMax(relerr,relerrl)/PetscAbsScalar(theta);
    635:     }

    637:     /* normalize */
    638:     PetscCall(BVSetActiveColumns(eps->V,k,k+1));
    639:     PetscCall(BVGetColumn(eps->W,k,&z));
    640:     PetscCall(BVDotVec(eps->V,z,&alpha));
    641:     PetscCall(BVRestoreColumn(eps->W,k,&z));
    642:     delta = PetscSqrtReal(PetscAbsScalar(alpha));
    643:     PetscCheck(delta!=0.0,PetscObjectComm((PetscObject)eps),PETSC_ERR_CONV_FAILED,"Breakdown in two-sided Power/RQI");
    644:     PetscCall(BVScaleColumn(eps->V,k,1.0/PetscConj(alpha/delta)));
    645:     PetscCall(BVScaleColumn(eps->W,k,1.0/delta));
    646:     PetscCall(BVCopyVec(eps->V,k,v));
    647:     PetscCall(BVCopyVec(eps->W,k,w));

    649:     if (power->shift_type == EPS_POWER_SHIFT_RAYLEIGH) { /* RQI */

    651:       /* compute relative error */
    652:       if (rho == 0.0) relerr = PETSC_MAX_REAL;
    653:       else relerr = 1.0 / PetscAbsScalar(delta*rho);

    655:       /* approximate eigenvalue is the shift */
    656:       eps->eigr[eps->nconv] = rho;

    658:       /* compute new shift */
    659:       if (relerr<eps->tol) {
    660:         rho = sigma;  /* if converged, restore original shift */
    661:         PetscCall(STSetShift(eps->st,rho));
    662:       } else {
    663:         rho = rho + PetscConj(theta)/(delta*delta);  /* Rayleigh quotient R(v) */
    664:         /* update operator according to new shift */
    665:         PetscCall(KSPSetErrorIfNotConverged(ksp,PETSC_FALSE));
    666:         PetscCall(STSetShift(eps->st,rho));
    667:         PetscCall(KSPGetConvergedReason(ksp,&reason));
    668:         if (reason) {
    669:           PetscCall(PetscInfo(eps,"Factorization failed, repeat with a perturbed shift\n"));
    670:           rho *= 1+10*PETSC_MACHINE_EPSILON;
    671:           PetscCall(STSetShift(eps->st,rho));
    672:           PetscCall(KSPGetConvergedReason(ksp,&reason));
    673:           PetscCheck(!reason,PetscObjectComm((PetscObject)ksp),PETSC_ERR_CONV_FAILED,"Second factorization failed");
    674:         }
    675:         PetscCall(KSPSetErrorIfNotConverged(ksp,PETSC_TRUE));
    676:       }
    677:     }
    678:     eps->errest[eps->nconv] = relerr;

    680:     /* if relerr<tol, accept eigenpair */
    681:     if (relerr<eps->tol) {
    682:       eps->nconv = eps->nconv + 1;
    683:       if (eps->nconv<eps->nev) {
    684:         PetscCall(EPSGetStartVector(eps,eps->nconv,&breakdown));
    685:         PetscCall(EPSGetLeftStartVector(eps,eps->nconv,&breakdownl));
    686:         if (breakdown || breakdownl) {
    687:           eps->reason = EPS_DIVERGED_BREAKDOWN;
    688:           PetscCall(PetscInfo(eps,"Unable to generate more start vectors\n"));
    689:           break;
    690:         }
    691:         PetscCall(BVBiorthonormalizeColumn(eps->V,eps->W,eps->nconv,NULL));
    692:       }
    693:     }
    694:     PetscCall(EPSMonitor(eps,eps->its,eps->nconv,eps->eigr,eps->eigi,eps->errest,PetscMin(eps->nconv+1,eps->nev)));
    695:     PetscCall((*eps->stopping)(eps,eps->its,eps->max_it,eps->nconv,eps->nev,&eps->reason,eps->stoppingctx));
    696:   }

    698:   PetscCall(DSSetDimensions(eps->ds,eps->nconv,0,0));
    699:   PetscCall(DSSetState(eps->ds,DS_STATE_RAW));
    700:   PetscFunctionReturn(PETSC_SUCCESS);
    701: }

    703: static PetscErrorCode EPSStopping_Power(EPS eps,PetscInt its,PetscInt max_it,PetscInt nconv,PetscInt nev,EPSConvergedReason *reason,void *ctx)
    704: {
    705:   EPS_POWER      *power = (EPS_POWER*)eps->data;
    706:   SNESConvergedReason snesreason;

    708:   PetscFunctionBegin;
    709:   if (PetscUnlikely(power->update)) {
    710:     PetscCall(SNESGetConvergedReason(power->snes,&snesreason));
    711:     if (snesreason < 0) {
    712:       *reason = EPS_DIVERGED_BREAKDOWN;
    713:       PetscFunctionReturn(PETSC_SUCCESS);
    714:     }
    715:   }
    716:   PetscCall(EPSStoppingBasic(eps,its,max_it,nconv,nev,reason,ctx));
    717:   PetscFunctionReturn(PETSC_SUCCESS);
    718: }

    720: static PetscErrorCode EPSBackTransform_Power(EPS eps)
    721: {
    722:   EPS_POWER      *power = (EPS_POWER*)eps->data;

    724:   PetscFunctionBegin;
    725:   if (power->nonlinear) eps->eigr[0] = 1.0/eps->eigr[0];
    726:   else if (power->shift_type == EPS_POWER_SHIFT_CONSTANT) PetscCall(EPSBackTransform_Default(eps));
    727:   PetscFunctionReturn(PETSC_SUCCESS);
    728: }

    730: static PetscErrorCode EPSSetFromOptions_Power(EPS eps,PetscOptionItems *PetscOptionsObject)
    731: {
    732:   EPS_POWER         *power = (EPS_POWER*)eps->data;
    733:   PetscBool         flg,val;
    734:   EPSPowerShiftType shift;

    736:   PetscFunctionBegin;
    737:   PetscOptionsHeadBegin(PetscOptionsObject,"EPS Power Options");

    739:     PetscCall(PetscOptionsEnum("-eps_power_shift_type","Shift type","EPSPowerSetShiftType",EPSPowerShiftTypes,(PetscEnum)power->shift_type,(PetscEnum*)&shift,&flg));
    740:     if (flg) PetscCall(EPSPowerSetShiftType(eps,shift));

    742:     PetscCall(PetscOptionsBool("-eps_power_nonlinear","Use nonlinear inverse iteration","EPSPowerSetNonlinear",power->nonlinear,&val,&flg));
    743:     if (flg) PetscCall(EPSPowerSetNonlinear(eps,val));

    745:     PetscCall(PetscOptionsBool("-eps_power_update","Update residual monolithically","EPSPowerSetUpdate",power->update,&val,&flg));
    746:     if (flg) PetscCall(EPSPowerSetUpdate(eps,val));

    748:     PetscCall(PetscOptionsBool("-eps_power_sign_normalization","Normalize Bx with sign of first nonzero entry","EPSPowerSetSignNormalization",power->sign_normalization,&power->sign_normalization,&flg));

    750:   PetscOptionsHeadEnd();
    751:   PetscFunctionReturn(PETSC_SUCCESS);
    752: }

    754: static PetscErrorCode EPSPowerSetShiftType_Power(EPS eps,EPSPowerShiftType shift)
    755: {
    756:   EPS_POWER *power = (EPS_POWER*)eps->data;

    758:   PetscFunctionBegin;
    759:   switch (shift) {
    760:     case EPS_POWER_SHIFT_CONSTANT:
    761:     case EPS_POWER_SHIFT_RAYLEIGH:
    762:     case EPS_POWER_SHIFT_WILKINSON:
    763:       if (power->shift_type != shift) {
    764:         power->shift_type = shift;
    765:         eps->state = EPS_STATE_INITIAL;
    766:       }
    767:       break;
    768:     default:
    769:       SETERRQ(PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"Invalid shift type");
    770:   }
    771:   PetscFunctionReturn(PETSC_SUCCESS);
    772: }

    774: /*@
    775:    EPSPowerSetShiftType - Sets the type of shifts used during the power
    776:    iteration. This can be used to emulate the Rayleigh Quotient Iteration
    777:    (RQI) method.

    779:    Logically Collective

    781:    Input Parameters:
    782: +  eps - the eigenproblem solver context
    783: -  shift - the type of shift

    785:    Options Database Key:
    786: .  -eps_power_shift_type - Sets the shift type (either 'constant' or
    787:                            'rayleigh' or 'wilkinson')

    789:    Notes:
    790:    By default, shifts are constant (EPS_POWER_SHIFT_CONSTANT) and the iteration
    791:    is the simple power method (or inverse iteration if a shift-and-invert
    792:    transformation is being used).

    794:    A variable shift can be specified (EPS_POWER_SHIFT_RAYLEIGH or
    795:    EPS_POWER_SHIFT_WILKINSON). In this case, the iteration behaves rather like
    796:    a cubic converging method such as RQI.

    798:    Level: advanced

    800: .seealso: EPSPowerGetShiftType(), STSetShift(), EPSPowerShiftType
    801: @*/
    802: PetscErrorCode EPSPowerSetShiftType(EPS eps,EPSPowerShiftType shift)
    803: {
    804:   PetscFunctionBegin;
    807:   PetscTryMethod(eps,"EPSPowerSetShiftType_C",(EPS,EPSPowerShiftType),(eps,shift));
    808:   PetscFunctionReturn(PETSC_SUCCESS);
    809: }

    811: static PetscErrorCode EPSPowerGetShiftType_Power(EPS eps,EPSPowerShiftType *shift)
    812: {
    813:   EPS_POWER *power = (EPS_POWER*)eps->data;

    815:   PetscFunctionBegin;
    816:   *shift = power->shift_type;
    817:   PetscFunctionReturn(PETSC_SUCCESS);
    818: }

    820: /*@
    821:    EPSPowerGetShiftType - Gets the type of shifts used during the power
    822:    iteration.

    824:    Not Collective

    826:    Input Parameter:
    827: .  eps - the eigenproblem solver context

    829:    Output Parameter:
    830: .  shift - the type of shift

    832:    Level: advanced

    834: .seealso: EPSPowerSetShiftType(), EPSPowerShiftType
    835: @*/
    836: PetscErrorCode EPSPowerGetShiftType(EPS eps,EPSPowerShiftType *shift)
    837: {
    838:   PetscFunctionBegin;
    840:   PetscAssertPointer(shift,2);
    841:   PetscUseMethod(eps,"EPSPowerGetShiftType_C",(EPS,EPSPowerShiftType*),(eps,shift));
    842:   PetscFunctionReturn(PETSC_SUCCESS);
    843: }

    845: static PetscErrorCode EPSPowerSetNonlinear_Power(EPS eps,PetscBool nonlinear)
    846: {
    847:   EPS_POWER *power = (EPS_POWER*)eps->data;

    849:   PetscFunctionBegin;
    850:   if (power->nonlinear != nonlinear) {
    851:     power->nonlinear = nonlinear;
    852:     eps->useds = PetscNot(nonlinear);
    853:     eps->ops->setupsort = nonlinear? NULL: EPSSetUpSort_Default;
    854:     eps->state = EPS_STATE_INITIAL;
    855:   }
    856:   PetscFunctionReturn(PETSC_SUCCESS);
    857: }

    859: /*@
    860:    EPSPowerSetNonlinear - Sets a flag to indicate that the problem is nonlinear.

    862:    Logically Collective

    864:    Input Parameters:
    865: +  eps - the eigenproblem solver context
    866: -  nonlinear - whether the problem is nonlinear or not

    868:    Options Database Key:
    869: .  -eps_power_nonlinear - Sets the nonlinear flag

    871:    Notes:
    872:    If this flag is set, the solver assumes that the problem is nonlinear,
    873:    that is, the operators that define the eigenproblem are not constant
    874:    matrices, but depend on the eigenvector, A(x)*x=lambda*B(x)*x. This is
    875:    different from the case of nonlinearity with respect to the eigenvalue
    876:    (use the NEP solver class for this kind of problems).

    878:    The way in which nonlinear operators are specified is very similar to
    879:    the case of PETSc's SNES solver. The difference is that the callback
    880:    functions are provided via composed functions "formFunction" and
    881:    "formJacobian" in each of the matrix objects passed as arguments of
    882:    EPSSetOperators(). The application context required for these functions
    883:    can be attached via a composed PetscContainer.

    885:    Level: advanced

    887: .seealso: EPSPowerGetNonlinear(), EPSSetOperators()
    888: @*/
    889: PetscErrorCode EPSPowerSetNonlinear(EPS eps,PetscBool nonlinear)
    890: {
    891:   PetscFunctionBegin;
    894:   PetscTryMethod(eps,"EPSPowerSetNonlinear_C",(EPS,PetscBool),(eps,nonlinear));
    895:   PetscFunctionReturn(PETSC_SUCCESS);
    896: }

    898: static PetscErrorCode EPSPowerGetNonlinear_Power(EPS eps,PetscBool *nonlinear)
    899: {
    900:   EPS_POWER *power = (EPS_POWER*)eps->data;

    902:   PetscFunctionBegin;
    903:   *nonlinear = power->nonlinear;
    904:   PetscFunctionReturn(PETSC_SUCCESS);
    905: }

    907: /*@
    908:    EPSPowerGetNonlinear - Returns a flag indicating if the problem is nonlinear.

    910:    Not Collective

    912:    Input Parameter:
    913: .  eps - the eigenproblem solver context

    915:    Output Parameter:
    916: .  nonlinear - the nonlinear flag

    918:    Level: advanced

    920: .seealso: EPSPowerSetUpdate(), EPSPowerSetNonlinear()
    921: @*/
    922: PetscErrorCode EPSPowerGetNonlinear(EPS eps,PetscBool *nonlinear)
    923: {
    924:   PetscFunctionBegin;
    926:   PetscAssertPointer(nonlinear,2);
    927:   PetscUseMethod(eps,"EPSPowerGetNonlinear_C",(EPS,PetscBool*),(eps,nonlinear));
    928:   PetscFunctionReturn(PETSC_SUCCESS);
    929: }

    931: static PetscErrorCode EPSPowerSetUpdate_Power(EPS eps,PetscBool update)
    932: {
    933:   EPS_POWER *power = (EPS_POWER*)eps->data;

    935:   PetscFunctionBegin;
    936:   PetscCheck(power->nonlinear,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_INCOMP,"This option does not make sense for linear problems");
    937:   power->update = update;
    938:   eps->state = EPS_STATE_INITIAL;
    939:   PetscFunctionReturn(PETSC_SUCCESS);
    940: }

    942: /*@
    943:    EPSPowerSetUpdate - Sets a flag to indicate that the residual is updated monolithically
    944:    for nonlinear problems. This potentially has a better convergence.

    946:    Logically Collective

    948:    Input Parameters:
    949: +  eps - the eigenproblem solver context
    950: -  update - whether the residual is updated monolithically or not

    952:    Options Database Key:
    953: .  -eps_power_update - Sets the update flag

    955:    Level: advanced

    957: .seealso: EPSPowerGetUpdate(), EPSPowerGetNonlinear(), EPSSetOperators()
    958: @*/
    959: PetscErrorCode EPSPowerSetUpdate(EPS eps,PetscBool update)
    960: {
    961:   PetscFunctionBegin;
    964:   PetscTryMethod(eps,"EPSPowerSetUpdate_C",(EPS,PetscBool),(eps,update));
    965:   PetscFunctionReturn(PETSC_SUCCESS);
    966: }

    968: static PetscErrorCode EPSPowerGetUpdate_Power(EPS eps,PetscBool *update)
    969: {
    970:   EPS_POWER *power = (EPS_POWER*)eps->data;

    972:   PetscFunctionBegin;
    973:   *update = power->update;
    974:   PetscFunctionReturn(PETSC_SUCCESS);
    975: }

    977: /*@
    978:    EPSPowerGetUpdate - Returns a flag indicating if the residual is updated monolithically
    979:    for nonlinear problems.

    981:    Not Collective

    983:    Input Parameter:
    984: .  eps - the eigenproblem solver context

    986:    Output Parameter:
    987: .  update - the update flag

    989:    Level: advanced

    991: .seealso: EPSPowerSetUpdate(), EPSPowerSetNonlinear()
    992: @*/
    993: PetscErrorCode EPSPowerGetUpdate(EPS eps,PetscBool *update)
    994: {
    995:   PetscFunctionBegin;
    997:   PetscAssertPointer(update,2);
    998:   PetscUseMethod(eps,"EPSPowerGetUpdate_C",(EPS,PetscBool*),(eps,update));
    999:   PetscFunctionReturn(PETSC_SUCCESS);
    1000: }

    1002: static PetscErrorCode EPSPowerSetSignNormalization_Power(EPS eps,PetscBool sign_normalization)
    1003: {
    1004:   EPS_POWER *power = (EPS_POWER*)eps->data;

    1006:   PetscFunctionBegin;
    1007:   power->sign_normalization = sign_normalization;
    1008:   PetscFunctionReturn(PETSC_SUCCESS);
    1009: }

    1011: /*@
    1012:    EPSPowerSetSignNormalization - Sets a flag to indicate whether the Bx vector
    1013:    should be normalized by the sign of the first non-zero element in the vector.
    1014:    E.g., if this is true, the post-normalization value of the first non-zero element
    1015:    in the vector is guaranteed to be positive.

    1017:    Logically Collective

    1019:    Input Parameters:
    1020: +  eps - the eigenproblem solver context
    1021: -  sign_normalization - whether Bx should be multiplied by the sign of the first non-zero
    1022:                         element when performing normalization steps

    1024:    Options Database Key:
    1025: .  -eps_power_sign_normalization - Sets the sign normalization flag

    1027:    Level: advanced

    1029: .seealso: EPSPowerGetSignNormalization()
    1030: @*/
    1031: PetscErrorCode EPSPowerSetSignNormalization(EPS eps,PetscBool sign_normalization)
    1032: {
    1033:   PetscFunctionBegin;
    1036:   PetscTryMethod(eps,"EPSPowerSetSignNormalization_C",(EPS,PetscBool),(eps,sign_normalization));
    1037:   PetscFunctionReturn(PETSC_SUCCESS);
    1038: }

    1040: static PetscErrorCode EPSPowerGetSignNormalization_Power(EPS eps,PetscBool *sign_normalization)
    1041: {
    1042:   EPS_POWER *power = (EPS_POWER*)eps->data;

    1044:   PetscFunctionBegin;
    1045:   *sign_normalization = power->sign_normalization;
    1046:   PetscFunctionReturn(PETSC_SUCCESS);
    1047: }

    1049: /*@
    1050:    EPSPowerGetSignNormalization - Returns a flag indicating whether the Bx vector
    1051:    is normalized by the sign of the first non-zero element in the vector. E.g.,
    1052:    if this is true, the post-normalization value of the first non-zero element in
    1053:    the vector is guaranteed to be positive.

    1055:    Not Collective

    1057:    Input Parameter:
    1058: .  eps - the eigenproblem solver context

    1060:    Output Parameter:
    1061: .  sign_normalization - the sign normalization flag

    1063:    Level: advanced

    1065: .seealso: EPSPowerSetSignNormalization()
    1066: @*/
    1067: PetscErrorCode EPSPowerGetSignNormalization(EPS eps,PetscBool *sign_normalization)
    1068: {
    1069:   PetscFunctionBegin;
    1071:   PetscAssertPointer(sign_normalization,2);
    1072:   PetscUseMethod(eps,"EPSPowerGetSignNormalization_C",(EPS,PetscBool*),(eps,sign_normalization));
    1073:   PetscFunctionReturn(PETSC_SUCCESS);
    1074: }

    1076: static PetscErrorCode EPSPowerSetSNES_Power(EPS eps,SNES snes)
    1077: {
    1078:   EPS_POWER      *power = (EPS_POWER*)eps->data;

    1080:   PetscFunctionBegin;
    1081:   PetscCall(PetscObjectReference((PetscObject)snes));
    1082:   PetscCall(SNESDestroy(&power->snes));
    1083:   power->snes = snes;
    1084:   eps->state = EPS_STATE_INITIAL;
    1085:   PetscFunctionReturn(PETSC_SUCCESS);
    1086: }

    1088: /*@
    1089:    EPSPowerSetSNES - Associate a nonlinear solver object (SNES) to the
    1090:    eigenvalue solver (to be used in nonlinear inverse iteration).

    1092:    Collective

    1094:    Input Parameters:
    1095: +  eps  - the eigenvalue solver
    1096: -  snes - the nonlinear solver object

    1098:    Level: advanced

    1100: .seealso: EPSPowerGetSNES()
    1101: @*/
    1102: PetscErrorCode EPSPowerSetSNES(EPS eps,SNES snes)
    1103: {
    1104:   PetscFunctionBegin;
    1107:   PetscCheckSameComm(eps,1,snes,2);
    1108:   PetscTryMethod(eps,"EPSPowerSetSNES_C",(EPS,SNES),(eps,snes));
    1109:   PetscFunctionReturn(PETSC_SUCCESS);
    1110: }

    1112: static PetscErrorCode EPSPowerGetSNES_Power(EPS eps,SNES *snes)
    1113: {
    1114:   EPS_POWER      *power = (EPS_POWER*)eps->data;

    1116:   PetscFunctionBegin;
    1117:   if (!power->snes) {
    1118:     PetscCall(SNESCreate(PetscObjectComm((PetscObject)eps),&power->snes));
    1119:     PetscCall(PetscObjectIncrementTabLevel((PetscObject)power->snes,(PetscObject)eps,1));
    1120:     PetscCall(SNESSetOptionsPrefix(power->snes,((PetscObject)eps)->prefix));
    1121:     PetscCall(SNESAppendOptionsPrefix(power->snes,"eps_power_"));
    1122:     PetscCall(PetscObjectSetOptions((PetscObject)power->snes,((PetscObject)eps)->options));
    1123:   }
    1124:   *snes = power->snes;
    1125:   PetscFunctionReturn(PETSC_SUCCESS);
    1126: }

    1128: /*@
    1129:    EPSPowerGetSNES - Retrieve the nonlinear solver object (SNES) associated
    1130:    with the eigenvalue solver.

    1132:    Not Collective

    1134:    Input Parameter:
    1135: .  eps - the eigenvalue solver

    1137:    Output Parameter:
    1138: .  snes - the nonlinear solver object

    1140:    Level: advanced

    1142: .seealso: EPSPowerSetSNES()
    1143: @*/
    1144: PetscErrorCode EPSPowerGetSNES(EPS eps,SNES *snes)
    1145: {
    1146:   PetscFunctionBegin;
    1148:   PetscAssertPointer(snes,2);
    1149:   PetscUseMethod(eps,"EPSPowerGetSNES_C",(EPS,SNES*),(eps,snes));
    1150:   PetscFunctionReturn(PETSC_SUCCESS);
    1151: }

    1153: static PetscErrorCode EPSReset_Power(EPS eps)
    1154: {
    1155:   EPS_POWER      *power = (EPS_POWER*)eps->data;

    1157:   PetscFunctionBegin;
    1158:   if (power->snes) PetscCall(SNESReset(power->snes));
    1159:   PetscFunctionReturn(PETSC_SUCCESS);
    1160: }

    1162: static PetscErrorCode EPSDestroy_Power(EPS eps)
    1163: {
    1164:   EPS_POWER      *power = (EPS_POWER*)eps->data;

    1166:   PetscFunctionBegin;
    1167:   if (power->nonlinear) PetscCall(SNESDestroy(&power->snes));
    1168:   PetscCall(PetscFree(eps->data));
    1169:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSPowerSetShiftType_C",NULL));
    1170:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSPowerGetShiftType_C",NULL));
    1171:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSPowerSetNonlinear_C",NULL));
    1172:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSPowerGetNonlinear_C",NULL));
    1173:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSPowerSetUpdate_C",NULL));
    1174:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSPowerGetUpdate_C",NULL));
    1175:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSPowerSetSignNormalization_C",NULL));
    1176:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSPowerGetSignNormalization_C",NULL));
    1177:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSPowerSetSNES_C",NULL));
    1178:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSPowerGetSNES_C",NULL));
    1179:   PetscFunctionReturn(PETSC_SUCCESS);
    1180: }

    1182: static PetscErrorCode EPSView_Power(EPS eps,PetscViewer viewer)
    1183: {
    1184:   EPS_POWER      *power = (EPS_POWER*)eps->data;
    1185:   PetscBool      isascii;

    1187:   PetscFunctionBegin;
    1188:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isascii));
    1189:   if (isascii) {
    1190:     if (power->nonlinear) {
    1191:       if (power->sign_normalization) PetscCall(PetscViewerASCIIPrintf(viewer,"  normalizing Bx by the sign of the first nonzero element\n"));
    1192:       else PetscCall(PetscViewerASCIIPrintf(viewer,"  not normalizing Bx by the sign of the first nonzero element\n"));
    1193:       PetscCall(PetscViewerASCIIPrintf(viewer,"  using nonlinear inverse iteration\n"));
    1194:       if (power->update) PetscCall(PetscViewerASCIIPrintf(viewer,"  updating the residual monolithically\n"));
    1195:       if (!power->snes) PetscCall(EPSPowerGetSNES(eps,&power->snes));
    1196:       PetscCall(PetscViewerASCIIPushTab(viewer));
    1197:       PetscCall(SNESView(power->snes,viewer));
    1198:       PetscCall(PetscViewerASCIIPopTab(viewer));
    1199:     } else PetscCall(PetscViewerASCIIPrintf(viewer,"  %s shifts\n",EPSPowerShiftTypes[power->shift_type]));
    1200:   }
    1201:   PetscFunctionReturn(PETSC_SUCCESS);
    1202: }

    1204: static PetscErrorCode EPSComputeVectors_Power(EPS eps)
    1205: {
    1206:   EPS_POWER      *power = (EPS_POWER*)eps->data;

    1208:   PetscFunctionBegin;
    1209:   if (eps->twosided) {
    1210:     PetscCall(EPSComputeVectors_Twosided(eps));
    1211:     PetscCall(BVNormalize(eps->V,NULL));
    1212:     PetscCall(BVNormalize(eps->W,NULL));
    1213:   } else if (!power->nonlinear) PetscCall(EPSComputeVectors_Schur(eps));
    1214:   PetscFunctionReturn(PETSC_SUCCESS);
    1215: }

    1217: static PetscErrorCode EPSSetDefaultST_Power(EPS eps)
    1218: {
    1219:   EPS_POWER      *power = (EPS_POWER*)eps->data;
    1220:   KSP            ksp;
    1221:   PC             pc;

    1223:   PetscFunctionBegin;
    1224:   if (power->nonlinear) {
    1225:     eps->categ=EPS_CATEGORY_PRECOND;
    1226:     PetscCall(STGetKSP(eps->st,&ksp));
    1227:     /* Set ST as STPRECOND so it can carry one preconditioning matrix
    1228:      * It is useful when A and B are shell matrices
    1229:      */
    1230:     PetscCall(STSetType(eps->st,STPRECOND));
    1231:     PetscCall(KSPGetPC(ksp,&pc));
    1232:     PetscCall(PCSetType(pc,PCNONE));
    1233:   }
    1234:   PetscFunctionReturn(PETSC_SUCCESS);
    1235: }

    1237: SLEPC_EXTERN PetscErrorCode EPSCreate_Power(EPS eps)
    1238: {
    1239:   EPS_POWER      *ctx;

    1241:   PetscFunctionBegin;
    1242:   PetscCall(PetscNew(&ctx));
    1243:   eps->data = (void*)ctx;

    1245:   eps->useds = PETSC_TRUE;
    1246:   eps->categ = EPS_CATEGORY_OTHER;

    1248:   eps->ops->setup          = EPSSetUp_Power;
    1249:   eps->ops->setupsort      = EPSSetUpSort_Default;
    1250:   eps->ops->setfromoptions = EPSSetFromOptions_Power;
    1251:   eps->ops->reset          = EPSReset_Power;
    1252:   eps->ops->destroy        = EPSDestroy_Power;
    1253:   eps->ops->view           = EPSView_Power;
    1254:   eps->ops->backtransform  = EPSBackTransform_Power;
    1255:   eps->ops->computevectors = EPSComputeVectors_Power;
    1256:   eps->ops->setdefaultst   = EPSSetDefaultST_Power;
    1257:   eps->stopping            = EPSStopping_Power;
    1258:   ctx->sign_normalization  = PETSC_TRUE;

    1260:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSPowerSetShiftType_C",EPSPowerSetShiftType_Power));
    1261:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSPowerGetShiftType_C",EPSPowerGetShiftType_Power));
    1262:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSPowerSetNonlinear_C",EPSPowerSetNonlinear_Power));
    1263:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSPowerGetNonlinear_C",EPSPowerGetNonlinear_Power));
    1264:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSPowerSetUpdate_C",EPSPowerSetUpdate_Power));
    1265:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSPowerGetUpdate_C",EPSPowerGetUpdate_Power));
    1266:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSPowerSetSignNormalization_C",EPSPowerSetSignNormalization_Power));
    1267:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSPowerGetSignNormalization_C",EPSPowerGetSignNormalization_Power));
    1268:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSPowerSetSNES_C",EPSPowerSetSNES_Power));
    1269:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSPowerGetSNES_C",EPSPowerGetSNES_Power));
    1270:   PetscFunctionReturn(PETSC_SUCCESS);
    1271: }