Actual source code: nepsetup.c
slepc-3.21.1 2024-04-26
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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:    NEP routines related to problem setup
     12: */

     14: #include <slepc/private/nepimpl.h>

     16: /*@
     17:    NEPSetDSType - Sets the type of the internal DS object based on the current
     18:    settings of the nonlinear eigensolver.

     20:    Collective

     22:    Input Parameter:
     23: .  nep - nonlinear eigensolver context

     25:    Note:
     26:    This function need not be called explicitly, since it will be called at
     27:    both NEPSetFromOptions() and NEPSetUp().

     29:    Level: developer

     31: .seealso: NEPSetFromOptions(), NEPSetUp()
     32: @*/
     33: PetscErrorCode NEPSetDSType(NEP nep)
     34: {
     35:   PetscFunctionBegin;
     37:   PetscTryTypeMethod(nep,setdstype);
     38:   PetscFunctionReturn(PETSC_SUCCESS);
     39: }

     41: /*@
     42:    NEPSetUp - Sets up all the internal data structures necessary for the
     43:    execution of the NEP solver.

     45:    Collective

     47:    Input Parameter:
     48: .  nep   - solver context

     50:    Notes:
     51:    This function need not be called explicitly in most cases, since NEPSolve()
     52:    calls it. It can be useful when one wants to measure the set-up time
     53:    separately from the solve time.

     55:    Level: developer

     57: .seealso: NEPCreate(), NEPSolve(), NEPDestroy()
     58: @*/
     59: PetscErrorCode NEPSetUp(NEP nep)
     60: {
     61:   PetscInt       k;
     62:   SlepcSC        sc;
     63:   Mat            T;
     64:   PetscBool      flg;
     65:   KSP            ksp;
     66:   PC             pc;
     67:   PetscMPIInt    size;
     68:   MatSolverType  stype;

     70:   PetscFunctionBegin;
     72:   NEPCheckProblem(nep,1);
     73:   if (nep->state) PetscFunctionReturn(PETSC_SUCCESS);
     74:   PetscCall(PetscLogEventBegin(NEP_SetUp,nep,0,0,0));

     76:   /* reset the convergence flag from the previous solves */
     77:   nep->reason = NEP_CONVERGED_ITERATING;

     79:   /* set default solver type (NEPSetFromOptions was not called) */
     80:   if (!((PetscObject)nep)->type_name) PetscCall(NEPSetType(nep,NEPRII));
     81:   if (nep->useds && !nep->ds) PetscCall(NEPGetDS(nep,&nep->ds));
     82:   if (nep->useds) PetscCall(NEPSetDSType(nep));
     83:   if (!nep->rg) PetscCall(NEPGetRG(nep,&nep->rg));
     84:   if (!((PetscObject)nep->rg)->type_name) PetscCall(RGSetType(nep->rg,RGINTERVAL));

     86:   /* set problem dimensions */
     87:   switch (nep->fui) {
     88:   case NEP_USER_INTERFACE_CALLBACK:
     89:     PetscCall(NEPGetFunction(nep,&T,NULL,NULL,NULL));
     90:     PetscCall(MatGetSize(T,&nep->n,NULL));
     91:     PetscCall(MatGetLocalSize(T,&nep->nloc,NULL));
     92:     break;
     93:   case NEP_USER_INTERFACE_SPLIT:
     94:     PetscCall(MatDuplicate(nep->A[0],MAT_DO_NOT_COPY_VALUES,&nep->function));
     95:     if (nep->P) PetscCall(MatDuplicate(nep->P[0],MAT_DO_NOT_COPY_VALUES,&nep->function_pre));
     96:     PetscCall(MatDuplicate(nep->A[0],MAT_DO_NOT_COPY_VALUES,&nep->jacobian));
     97:     PetscCall(MatGetSize(nep->A[0],&nep->n,NULL));
     98:     PetscCall(MatGetLocalSize(nep->A[0],&nep->nloc,NULL));
     99:     break;
    100:   }

    102:   /* set default problem type */
    103:   if (!nep->problem_type) PetscCall(NEPSetProblemType(nep,NEP_GENERAL));

    105:   /* check consistency of refinement options */
    106:   if (nep->refine) {
    107:     PetscCheck(nep->fui==NEP_USER_INTERFACE_SPLIT,PetscObjectComm((PetscObject)nep),PETSC_ERR_SUP,"Iterative refinement only implemented in split form");
    108:     if (!nep->scheme) {  /* set default scheme */
    109:       PetscCall(NEPRefineGetKSP(nep,&ksp));
    110:       PetscCall(KSPGetPC(ksp,&pc));
    111:       PetscCall(PetscObjectTypeCompare((PetscObject)ksp,KSPPREONLY,&flg));
    112:       if (flg) PetscCall(PetscObjectTypeCompareAny((PetscObject)pc,&flg,PCLU,PCCHOLESKY,""));
    113:       nep->scheme = flg? NEP_REFINE_SCHEME_MBE: NEP_REFINE_SCHEME_SCHUR;
    114:     }
    115:     if (nep->scheme==NEP_REFINE_SCHEME_MBE) {
    116:       PetscCall(NEPRefineGetKSP(nep,&ksp));
    117:       PetscCall(KSPGetPC(ksp,&pc));
    118:       PetscCall(PetscObjectTypeCompare((PetscObject)ksp,KSPPREONLY,&flg));
    119:       if (flg) PetscCall(PetscObjectTypeCompareAny((PetscObject)pc,&flg,PCLU,PCCHOLESKY,""));
    120:       PetscCheck(flg,PetscObjectComm((PetscObject)nep),PETSC_ERR_SUP,"The MBE scheme for refinement requires a direct solver in KSP");
    121:       PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)pc),&size));
    122:       if (size>1) {   /* currently selected PC is a factorization */
    123:         PetscCall(PCFactorGetMatSolverType(pc,&stype));
    124:         PetscCall(PetscStrcmp(stype,MATSOLVERPETSC,&flg));
    125:         PetscCheck(!flg,PetscObjectComm((PetscObject)nep),PETSC_ERR_SUP,"For Newton refinement, you chose to solve linear systems with a factorization, but in parallel runs you need to select an external package");
    126:       }
    127:     }
    128:     if (nep->scheme==NEP_REFINE_SCHEME_SCHUR) {
    129:       PetscCheck(nep->npart==1,PetscObjectComm((PetscObject)nep),PETSC_ERR_SUP,"The Schur scheme for refinement does not support subcommunicators");
    130:     }
    131:   }
    132:   /* call specific solver setup */
    133:   PetscUseTypeMethod(nep,setup);

    135:   /* set tolerance if not yet set */
    136:   if (nep->tol==(PetscReal)PETSC_DEFAULT) nep->tol = SLEPC_DEFAULT_TOL;
    137:   if (nep->refine) {
    138:     if (nep->rtol==(PetscReal)PETSC_DEFAULT) nep->rtol = PetscMax(nep->tol/1000,PETSC_MACHINE_EPSILON);
    139:     if (nep->rits==(PetscReal)PETSC_DEFAULT) nep->rits = (nep->refine==NEP_REFINE_SIMPLE)? 10: 1;
    140:   }

    142:   /* fill sorting criterion context */
    143:   switch (nep->which) {
    144:     case NEP_LARGEST_MAGNITUDE:
    145:       nep->sc->comparison    = SlepcCompareLargestMagnitude;
    146:       nep->sc->comparisonctx = NULL;
    147:       break;
    148:     case NEP_SMALLEST_MAGNITUDE:
    149:       nep->sc->comparison    = SlepcCompareSmallestMagnitude;
    150:       nep->sc->comparisonctx = NULL;
    151:       break;
    152:     case NEP_LARGEST_REAL:
    153:       nep->sc->comparison    = SlepcCompareLargestReal;
    154:       nep->sc->comparisonctx = NULL;
    155:       break;
    156:     case NEP_SMALLEST_REAL:
    157:       nep->sc->comparison    = SlepcCompareSmallestReal;
    158:       nep->sc->comparisonctx = NULL;
    159:       break;
    160:     case NEP_LARGEST_IMAGINARY:
    161:       nep->sc->comparison    = SlepcCompareLargestImaginary;
    162:       nep->sc->comparisonctx = NULL;
    163:       break;
    164:     case NEP_SMALLEST_IMAGINARY:
    165:       nep->sc->comparison    = SlepcCompareSmallestImaginary;
    166:       nep->sc->comparisonctx = NULL;
    167:       break;
    168:     case NEP_TARGET_MAGNITUDE:
    169:       nep->sc->comparison    = SlepcCompareTargetMagnitude;
    170:       nep->sc->comparisonctx = &nep->target;
    171:       break;
    172:     case NEP_TARGET_REAL:
    173:       nep->sc->comparison    = SlepcCompareTargetReal;
    174:       nep->sc->comparisonctx = &nep->target;
    175:       break;
    176:     case NEP_TARGET_IMAGINARY:
    177: #if defined(PETSC_USE_COMPLEX)
    178:       nep->sc->comparison    = SlepcCompareTargetImaginary;
    179:       nep->sc->comparisonctx = &nep->target;
    180: #endif
    181:       break;
    182:     case NEP_ALL:
    183:       nep->sc->comparison    = SlepcCompareSmallestReal;
    184:       nep->sc->comparisonctx = NULL;
    185:       break;
    186:     case NEP_WHICH_USER:
    187:       break;
    188:   }

    190:   nep->sc->map    = NULL;
    191:   nep->sc->mapobj = NULL;

    193:   /* fill sorting criterion for DS */
    194:   if (nep->useds) {
    195:     PetscCall(DSGetSlepcSC(nep->ds,&sc));
    196:     sc->comparison    = nep->sc->comparison;
    197:     sc->comparisonctx = nep->sc->comparisonctx;
    198:     PetscCall(PetscObjectTypeCompare((PetscObject)nep,NEPNLEIGS,&flg));
    199:     if (!flg) {
    200:       sc->map    = NULL;
    201:       sc->mapobj = NULL;
    202:     }
    203:   }
    204:   PetscCheck(nep->nev<=nep->ncv,PetscObjectComm((PetscObject)nep),PETSC_ERR_ARG_OUTOFRANGE,"nev bigger than ncv");

    206:   /* process initial vectors */
    207:   if (nep->nini<0) {
    208:     k = -nep->nini;
    209:     PetscCheck(k<=nep->ncv,PetscObjectComm((PetscObject)nep),PETSC_ERR_USER_INPUT,"The number of initial vectors is larger than ncv");
    210:     PetscCall(BVInsertVecs(nep->V,0,&k,nep->IS,PETSC_TRUE));
    211:     PetscCall(SlepcBasisDestroy_Private(&nep->nini,&nep->IS));
    212:     nep->nini = k;
    213:   }
    214:   PetscCall(PetscLogEventEnd(NEP_SetUp,nep,0,0,0));
    215:   nep->state = NEP_STATE_SETUP;
    216:   PetscFunctionReturn(PETSC_SUCCESS);
    217: }

    219: /*@C
    220:    NEPSetInitialSpace - Specify a basis of vectors that constitute the initial
    221:    space, that is, the subspace from which the solver starts to iterate.

    223:    Collective

    225:    Input Parameters:
    226: +  nep   - the nonlinear eigensolver context
    227: .  n     - number of vectors
    228: -  is    - set of basis vectors of the initial space

    230:    Notes:
    231:    Some solvers start to iterate on a single vector (initial vector). In that case,
    232:    the other vectors are ignored.

    234:    These vectors do not persist from one NEPSolve() call to the other, so the
    235:    initial space should be set every time.

    237:    The vectors do not need to be mutually orthonormal, since they are explicitly
    238:    orthonormalized internally.

    240:    Common usage of this function is when the user can provide a rough approximation
    241:    of the wanted eigenspace. Then, convergence may be faster.

    243:    Level: intermediate

    245: .seealso: NEPSetUp()
    246: @*/
    247: PetscErrorCode NEPSetInitialSpace(NEP nep,PetscInt n,Vec is[])
    248: {
    249:   PetscFunctionBegin;
    252:   PetscCheck(n>=0,PetscObjectComm((PetscObject)nep),PETSC_ERR_ARG_OUTOFRANGE,"Argument n cannot be negative");
    253:   if (n>0) {
    254:     PetscAssertPointer(is,3);
    256:   }
    257:   PetscCall(SlepcBasisReference_Private(n,is,&nep->nini,&nep->IS));
    258:   if (n>0) nep->state = NEP_STATE_INITIAL;
    259:   PetscFunctionReturn(PETSC_SUCCESS);
    260: }

    262: /*
    263:   NEPSetDimensions_Default - Set reasonable values for ncv, mpd if not set
    264:   by the user. This is called at setup.
    265:  */
    266: PetscErrorCode NEPSetDimensions_Default(NEP nep,PetscInt nev,PetscInt *ncv,PetscInt *mpd)
    267: {
    268:   PetscFunctionBegin;
    269:   if (*ncv!=PETSC_DEFAULT) { /* ncv set */
    270:     PetscCheck(*ncv>=nev,PetscObjectComm((PetscObject)nep),PETSC_ERR_USER_INPUT,"The value of ncv must be at least nev");
    271:   } else if (*mpd!=PETSC_DEFAULT) { /* mpd set */
    272:     *ncv = PetscMin(nep->n,nev+(*mpd));
    273:   } else { /* neither set: defaults depend on nev being small or large */
    274:     if (nev<500) *ncv = PetscMin(nep->n,PetscMax(2*nev,nev+15));
    275:     else {
    276:       *mpd = 500;
    277:       *ncv = PetscMin(nep->n,nev+(*mpd));
    278:     }
    279:   }
    280:   if (*mpd==PETSC_DEFAULT) *mpd = *ncv;
    281:   PetscFunctionReturn(PETSC_SUCCESS);
    282: }

    284: /*@
    285:    NEPAllocateSolution - Allocate memory storage for common variables such
    286:    as eigenvalues and eigenvectors.

    288:    Collective

    290:    Input Parameters:
    291: +  nep   - eigensolver context
    292: -  extra - number of additional positions, used for methods that require a
    293:            working basis slightly larger than ncv

    295:    Developer Notes:
    296:    This is SLEPC_EXTERN because it may be required by user plugin NEP
    297:    implementations.

    299:    Level: developer

    301: .seealso: PEPSetUp()
    302: @*/
    303: PetscErrorCode NEPAllocateSolution(NEP nep,PetscInt extra)
    304: {
    305:   PetscInt       oldsize,requested;
    306:   PetscRandom    rand;
    307:   Mat            T;
    308:   Vec            t;

    310:   PetscFunctionBegin;
    311:   requested = nep->ncv + extra;

    313:   /* oldsize is zero if this is the first time setup is called */
    314:   PetscCall(BVGetSizes(nep->V,NULL,NULL,&oldsize));

    316:   /* allocate space for eigenvalues and friends */
    317:   if (requested != oldsize || !nep->eigr) {
    318:     PetscCall(PetscFree4(nep->eigr,nep->eigi,nep->errest,nep->perm));
    319:     PetscCall(PetscMalloc4(requested,&nep->eigr,requested,&nep->eigi,requested,&nep->errest,requested,&nep->perm));
    320:   }

    322:   /* allocate V */
    323:   if (!nep->V) PetscCall(NEPGetBV(nep,&nep->V));
    324:   if (!oldsize) {
    325:     if (!((PetscObject)nep->V)->type_name) PetscCall(BVSetType(nep->V,BVMAT));
    326:     if (nep->fui==NEP_USER_INTERFACE_SPLIT) T = nep->A[0];
    327:     else PetscCall(NEPGetFunction(nep,&T,NULL,NULL,NULL));
    328:     PetscCall(MatCreateVecsEmpty(T,&t,NULL));
    329:     PetscCall(BVSetSizesFromVec(nep->V,t,requested));
    330:     PetscCall(VecDestroy(&t));
    331:   } else PetscCall(BVResize(nep->V,requested,PETSC_FALSE));

    333:   /* allocate W */
    334:   if (nep->twosided) {
    335:     PetscCall(BVGetRandomContext(nep->V,&rand));  /* make sure the random context is available when duplicating */
    336:     PetscCall(BVDestroy(&nep->W));
    337:     PetscCall(BVDuplicate(nep->V,&nep->W));
    338:   }
    339:   PetscFunctionReturn(PETSC_SUCCESS);
    340: }