Actual source code: nepdefault.c

slepc-3.7.4 2017-05-17
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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) 2002-2016, 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:     case NEP_ALL:
 73:     case NEP_WHICH_USER:
 74:       *sigma = 1.0;   /* arbitrary value */
 75:       break;
 76:     case NEP_SMALLEST_MAGNITUDE:
 77:     case NEP_SMALLEST_IMAGINARY:
 78:       *sigma = 0.0;
 79:       break;
 80:     case NEP_LARGEST_REAL:
 81:       *sigma = PETSC_MAX_REAL;
 82:       break;
 83:     case NEP_SMALLEST_REAL:
 84:       *sigma = PETSC_MIN_REAL;
 85:       break;
 86:     case NEP_TARGET_MAGNITUDE:
 87:     case NEP_TARGET_REAL:
 88:     case NEP_TARGET_IMAGINARY:
 89:       *sigma = nep->target;
 90:       break;
 91:   }
 92:   return(0);
 93: }

 97: /*
 98:   NEPConvergedRelative - Checks convergence relative to the eigenvalue.
 99: */
100: PetscErrorCode NEPConvergedRelative(NEP nep,PetscScalar eigr,PetscScalar eigi,PetscReal res,PetscReal *errest,void *ctx)
101: {
102:   PetscReal w;

105:   w = SlepcAbsEigenvalue(eigr,eigi);
106:   *errest = res/w;
107:   return(0);
108: }

112: /*
113:   NEPConvergedAbsolute - Checks convergence absolutely.
114: */
115: PetscErrorCode NEPConvergedAbsolute(NEP nep,PetscScalar eigr,PetscScalar eigi,PetscReal res,PetscReal *errest,void *ctx)
116: {
118:   *errest = res;
119:   return(0);
120: }

124: /*
125:   NEPConvergedNorm - Checks convergence relative to the matrix norms.
126: */
127: PetscErrorCode NEPConvergedNorm(NEP nep,PetscScalar eigr,PetscScalar eigi,PetscReal res,PetscReal *errest,void *ctx)
128: {
129:   PetscScalar    s;
130:   PetscReal      w=0.0;
131:   PetscInt       j;
132:   PetscBool      flg;

136:   if (nep->fui!=NEP_USER_INTERFACE_SPLIT) SETERRQ(PetscObjectComm((PetscObject)nep),PETSC_ERR_SUP,"Backward error only available in split form");
137:   /* initialization of matrix norms */
138:   if (!nep->nrma[0]) {
139:     for (j=0;j<nep->nt;j++) {
140:       MatHasOperation(nep->A[j],MATOP_NORM,&flg);
141:       if (!flg) SETERRQ(PetscObjectComm((PetscObject)nep),PETSC_ERR_ARG_WRONG,"The convergence test related to the matrix norms requires a matrix norm operation");
142:       MatNorm(nep->A[j],NORM_INFINITY,&nep->nrma[j]);
143:     }
144:   }
145:   for (j=0;j<nep->nt;j++) {
146:     FNEvaluateFunction(nep->f[j],eigr,&s);
147:     w = w + nep->nrma[j]*PetscAbsScalar(s);
148:   }
149:   *errest = res/w;
150:   return(0);
151: }

155: /*@C
156:    NEPStoppingBasic - Default routine to determine whether the outer eigensolver
157:    iteration must be stopped.

159:    Collective on NEP

161:    Input Parameters:
162: +  nep    - nonlinear eigensolver context obtained from NEPCreate()
163: .  its    - current number of iterations
164: .  max_it - maximum number of iterations
165: .  nconv  - number of currently converged eigenpairs
166: .  nev    - number of requested eigenpairs
167: -  ctx    - context (not used here)

169:    Output Parameter:
170: .  reason - result of the stopping test

172:    Notes:
173:    A positive value of reason indicates that the iteration has finished successfully
174:    (converged), and a negative value indicates an error condition (diverged). If
175:    the iteration needs to be continued, reason must be set to NEP_CONVERGED_ITERATING
176:    (zero).

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

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

183:    Level: advanced

185: .seealso: NEPSetStoppingTest(), NEPConvergedReason, NEPGetConvergedReason()
186: @*/
187: PetscErrorCode NEPStoppingBasic(NEP nep,PetscInt its,PetscInt max_it,PetscInt nconv,PetscInt nev,NEPConvergedReason *reason,void *ctx)
188: {

192:   *reason = NEP_CONVERGED_ITERATING;
193:   if (nconv >= nev) {
194:     PetscInfo2(nep,"Nonlinear eigensolver finished successfully: %D eigenpairs converged at iteration %D\n",nconv,its);
195:     *reason = NEP_CONVERGED_TOL;
196:   } else if (its >= max_it) {
197:     *reason = NEP_DIVERGED_ITS;
198:     PetscInfo1(nep,"Nonlinear eigensolver iteration reached maximum number of iterations (%D)\n",its);
199:   }
200:   return(0);
201: }

205: PetscErrorCode NEPComputeVectors_Schur(NEP nep)
206: {
208:   PetscInt       n,i;
209:   Mat            Z;
210:   Vec            v;

213:   DSGetDimensions(nep->ds,&n,NULL,NULL,NULL,NULL);
214:   DSVectors(nep->ds,DS_MAT_X,NULL,NULL);
215:   DSGetMat(nep->ds,DS_MAT_X,&Z);
216:   BVSetActiveColumns(nep->V,0,n);
217:   BVMultInPlace(nep->V,Z,0,n);
218:   MatDestroy(&Z);

220:   /* normalization */
221:   for (i=0;i<n;i++) {
222:     BVGetColumn(nep->V,i,&v);
223:     VecNormalize(v,NULL);
224:     BVRestoreColumn(nep->V,i,&v);
225:   }
226:   return(0);
227: }