Date: 2016-03-29T14:59:15+00:00

Actual source code: nepdefault.c
slepc-3.6.3 2016-03-29
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      1: /*
      2:      This file contains some simple default routines for common NEP operations.

      4:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      5:    SLEPc - Scalable Library for Eigenvalue Problem Computations
      6:    Copyright (c) 2002-2015, Universitat Politecnica de Valencia, Spain

      8:    This file is part of SLEPc.

     10:    SLEPc is free software: you can redistribute it and/or modify it under  the
     11:    terms of version 3 of the GNU Lesser General Public License as published by
     12:    the Free Software Foundation.

     14:    SLEPc  is  distributed in the hope that it will be useful, but WITHOUT  ANY
     15:    WARRANTY;  without even the implied warranty of MERCHANTABILITY or  FITNESS
     16:    FOR  A  PARTICULAR PURPOSE. See the GNU Lesser General Public  License  for
     17:    more details.

     19:    You  should have received a copy of the GNU Lesser General  Public  License
     20:    along with SLEPc. If not, see <http://www.gnu.org/licenses/>.
     21:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     22: */

     24: #include <slepc/private/nepimpl.h>     /*I "slepcnep.h" I*/

     28: /*@
     29:    NEPSetWorkVecs - Sets a number of work vectors into a NEP object

     31:    Collective on NEP

     33:    Input Parameters:
     34: +  nep - nonlinear eigensolver context
     35: -  nw  - number of work vectors to allocate

     37:    Developers Note:
     38:    This is PETSC_EXTERN because it may be required by user plugin NEP
     39:    implementations.

     41:    Level: developer
     42: @*/
     43: PetscErrorCode NEPSetWorkVecs(NEP nep,PetscInt nw)
     44: {
     46:   Vec            t;

     49:   if (nep->nwork < nw) {
     50:     VecDestroyVecs(nep->nwork,&nep->work);
     51:     nep->nwork = nw;
     52:     BVGetColumn(nep->V,0,&t);
     53:     VecDuplicateVecs(t,nw,&nep->work);
     54:     BVRestoreColumn(nep->V,0,&t);
     55:     PetscLogObjectParents(nep,nw,nep->work);
     56:   }
     57:   return(0);
     58: }

     62: /*
     63:   NEPGetDefaultShift - Return the value of sigma to start the nonlinear iteration.
     64:  */
     65: PetscErrorCode NEPGetDefaultShift(NEP nep,PetscScalar *sigma)
     66: {
     69:   switch (nep->which) {
     70:     case NEP_LARGEST_MAGNITUDE:
     71:     case NEP_LARGEST_IMAGINARY:
     72:       *sigma = 1.0;   /* arbitrary value */
     73:       break;
     74:     case NEP_SMALLEST_MAGNITUDE:
     75:     case NEP_SMALLEST_IMAGINARY:
     76:       *sigma = 0.0;
     77:       break;
     78:     case NEP_LARGEST_REAL:
     79:       *sigma = PETSC_MAX_REAL;
     80:       break;
     81:     case NEP_SMALLEST_REAL:
     82:       *sigma = PETSC_MIN_REAL;
     83:       break;
     84:     case NEP_TARGET_MAGNITUDE:
     85:     case NEP_TARGET_REAL:
     86:     case NEP_TARGET_IMAGINARY:
     87:       *sigma = nep->target;
     88:       break;
     89:   }
     90:   return(0);
     91: }

     95: /*
     96:   NEPConvergedDefault - Checks convergence of the nonlinear eigensolver.
     97: */
     98: PetscErrorCode NEPConvergedDefault(NEP nep,PetscInt it,PetscReal xnorm,PetscReal snorm,PetscReal fnorm,NEPConvergedReason *reason,void *ctx)
     99: {

    106:   *reason = NEP_CONVERGED_ITERATING;

    108:   if (!it) {
    109:     /* set parameter for default relative tolerance convergence test */
    110:     nep->ttol = fnorm*nep->rtol;
    111:   }
    112:   if (PetscIsInfOrNanReal(fnorm)) {
    113:     PetscInfo(nep,"Failed to converged, function norm is NaN\n");
    114:     *reason = NEP_DIVERGED_FNORM_NAN;
    115:   } else if (fnorm < nep->abstol) {
    116:     PetscInfo2(nep,"Converged due to function norm %14.12e < %14.12e\n",(double)fnorm,(double)nep->abstol);
    117:     *reason = NEP_CONVERGED_FNORM_ABS;
    118:   } else if (nep->nfuncs >= nep->max_funcs) {
    119:     PetscInfo2(nep,"Exceeded maximum number of function evaluations: %D > %D\n",nep->nfuncs,nep->max_funcs);
    120:     *reason = NEP_DIVERGED_FUNCTION_COUNT;
    121:   }

    123:   if (it && !*reason) {
    124:     if (fnorm <= nep->ttol) {
    125:       PetscInfo2(nep,"Converged due to function norm %14.12e < %14.12e (relative tolerance)\n",(double)fnorm,(double)nep->ttol);
    126:       *reason = NEP_CONVERGED_FNORM_RELATIVE;
    127:     } else if (snorm < nep->stol*xnorm) {
    128:       PetscInfo3(nep,"Converged due to small update length: %14.12e < %14.12e * %14.12e\n",(double)snorm,(double)nep->stol,(double)xnorm);
    129:       *reason = NEP_CONVERGED_SNORM_RELATIVE;
    130:     }
    131:   }
    132:   return(0);
    133: }