Date: 2022-03-31T15:29:31+00:00

Actual source code: nepdefault.c
slepc-3.17.0 2022-03-31
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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:    Simple default routines for common NEP operations
     12: */

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

     16: /*@
     17:    NEPSetWorkVecs - Sets a number of work vectors into a NEP object

     19:    Collective on nep

     21:    Input Parameters:
     22: +  nep - nonlinear eigensolver context
     23: -  nw  - number of work vectors to allocate

     25:    Developer Notes:
     26:    This is SLEPC_EXTERN because it may be required by user plugin NEP
     27:    implementations.

     29:    Level: developer

     31: .seealso: NEPSetUp()
     32: @*/
     33: PetscErrorCode NEPSetWorkVecs(NEP nep,PetscInt nw)
     34: {
     35:   Vec            t;

     37:   if (nep->nwork < nw) {
     38:     VecDestroyVecs(nep->nwork,&nep->work);
     39:     nep->nwork = nw;
     40:     BVGetColumn(nep->V,0,&t);
     41:     VecDuplicateVecs(t,nw,&nep->work);
     42:     BVRestoreColumn(nep->V,0,&t);
     43:     PetscLogObjectParents(nep,nw,nep->work);
     44:   }
     45:   PetscFunctionReturn(0);
     46: }

     48: /*
     49:   NEPGetDefaultShift - Return the value of sigma to start the nonlinear iteration.
     50:  */
     51: PetscErrorCode NEPGetDefaultShift(NEP nep,PetscScalar *sigma)
     52: {
     54:   switch (nep->which) {
     55:     case NEP_LARGEST_MAGNITUDE:
     56:     case NEP_LARGEST_IMAGINARY:
     57:     case NEP_ALL:
     58:     case NEP_WHICH_USER:
     59:       *sigma = 1.0;   /* arbitrary value */
     60:       break;
     61:     case NEP_SMALLEST_MAGNITUDE:
     62:     case NEP_SMALLEST_IMAGINARY:
     63:       *sigma = 0.0;
     64:       break;
     65:     case NEP_LARGEST_REAL:
     66:       *sigma = PETSC_MAX_REAL;
     67:       break;
     68:     case NEP_SMALLEST_REAL:
     69:       *sigma = PETSC_MIN_REAL;
     70:       break;
     71:     case NEP_TARGET_MAGNITUDE:
     72:     case NEP_TARGET_REAL:
     73:     case NEP_TARGET_IMAGINARY:
     74:       *sigma = nep->target;
     75:       break;
     76:   }
     77:   PetscFunctionReturn(0);
     78: }

     80: /*
     81:   NEPConvergedRelative - Checks convergence relative to the eigenvalue.
     82: */
     83: PetscErrorCode NEPConvergedRelative(NEP nep,PetscScalar eigr,PetscScalar eigi,PetscReal res,PetscReal *errest,void *ctx)
     84: {
     85:   PetscReal w;

     87:   w = SlepcAbsEigenvalue(eigr,eigi);
     88:   *errest = res/w;
     89:   PetscFunctionReturn(0);
     90: }

     92: /*
     93:   NEPConvergedAbsolute - Checks convergence absolutely.
     94: */
     95: PetscErrorCode NEPConvergedAbsolute(NEP nep,PetscScalar eigr,PetscScalar eigi,PetscReal res,PetscReal *errest,void *ctx)
     96: {
     97:   *errest = res;
     98:   PetscFunctionReturn(0);
     99: }

    101: /*
    102:   NEPConvergedNorm - Checks convergence relative to the matrix norms.
    103: */
    104: PetscErrorCode NEPConvergedNorm(NEP nep,PetscScalar eigr,PetscScalar eigi,PetscReal res,PetscReal *errest,void *ctx)
    105: {
    106:   PetscScalar    s;
    107:   PetscReal      w=0.0;
    108:   PetscInt       j;
    109:   PetscBool      flg;

    111:   if (nep->fui!=NEP_USER_INTERFACE_SPLIT) {
    112:     NEPComputeFunction(nep,eigr,nep->function,nep->function);
    113:     MatHasOperation(nep->function,MATOP_NORM,&flg);
    115:     MatNorm(nep->function,NORM_INFINITY,&w);
    116:   } else {
    117:     /* initialization of matrix norms */
    118:     if (!nep->nrma[0]) {
    119:       for (j=0;j<nep->nt;j++) {
    120:         MatHasOperation(nep->A[j],MATOP_NORM,&flg);
    122:         MatNorm(nep->A[j],NORM_INFINITY,&nep->nrma[j]);
    123:       }
    124:     }
    125:     for (j=0;j<nep->nt;j++) {
    126:       FNEvaluateFunction(nep->f[j],eigr,&s);
    127:       w = w + nep->nrma[j]*PetscAbsScalar(s);
    128:     }
    129:   }
    130:   *errest = res/w;
    131:   PetscFunctionReturn(0);
    132: }

    134: /*@C
    135:    NEPStoppingBasic - Default routine to determine whether the outer eigensolver
    136:    iteration must be stopped.

    138:    Collective on nep

    140:    Input Parameters:
    141: +  nep    - nonlinear eigensolver context obtained from NEPCreate()
    142: .  its    - current number of iterations
    143: .  max_it - maximum number of iterations
    144: .  nconv  - number of currently converged eigenpairs
    145: .  nev    - number of requested eigenpairs
    146: -  ctx    - context (not used here)

    148:    Output Parameter:
    149: .  reason - result of the stopping test

    151:    Notes:
    152:    A positive value of reason indicates that the iteration has finished successfully
    153:    (converged), and a negative value indicates an error condition (diverged). If
    154:    the iteration needs to be continued, reason must be set to NEP_CONVERGED_ITERATING
    155:    (zero).

    157:    NEPStoppingBasic() will stop if all requested eigenvalues are converged, or if
    158:    the maximum number of iterations has been reached.

    160:    Use NEPSetStoppingTest() to provide your own test instead of using this one.

    162:    Level: advanced

    164: .seealso: NEPSetStoppingTest(), NEPConvergedReason, NEPGetConvergedReason()
    165: @*/
    166: PetscErrorCode NEPStoppingBasic(NEP nep,PetscInt its,PetscInt max_it,PetscInt nconv,PetscInt nev,NEPConvergedReason *reason,void *ctx)
    167: {
    168:   *reason = NEP_CONVERGED_ITERATING;
    169:   if (nconv >= nev) {
    170:     PetscInfo(nep,"Nonlinear eigensolver finished successfully: %" PetscInt_FMT " eigenpairs converged at iteration %" PetscInt_FMT "\n",nconv,its);
    171:     *reason = NEP_CONVERGED_TOL;
    172:   } else if (its >= max_it) {
    173:     *reason = NEP_DIVERGED_ITS;
    174:     PetscInfo(nep,"Nonlinear eigensolver iteration reached maximum number of iterations (%" PetscInt_FMT ")\n",its);
    175:   }
    176:   PetscFunctionReturn(0);
    177: }

    179: PetscErrorCode NEPComputeVectors_Schur(NEP nep)
    180: {
    181:   Mat            Z;

    183:   DSVectors(nep->ds,DS_MAT_X,NULL,NULL);
    184:   DSGetMat(nep->ds,DS_MAT_X,&Z);
    185:   BVMultInPlace(nep->V,Z,0,nep->nconv);
    186:   MatDestroy(&Z);
    187:   BVNormalize(nep->V,nep->eigi);
    188:   PetscFunctionReturn(0);
    189: }