Actual source code: test22.c

slepc-3.11.2 2019-07-30
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  1: /*
  2:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  3:    SLEPc - Scalable Library for Eigenvalue Problem Computations
  4:    Copyright (c) 2002-2019, 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: */

 11: static char help[] = "Illustrates how to obtain invariant subspaces. "
 12:   "Based on ex9.\n"
 13:   "The command line options are:\n"
 14:   "  -n <n>, where <n> = block dimension of the 2x2 block matrix.\n"
 15:   "  -L <L>, where <L> = bifurcation parameter.\n"
 16:   "  -alpha <alpha>, -beta <beta>, -delta1 <delta1>,  -delta2 <delta2>,\n"
 17:   "       where <alpha> <beta> <delta1> <delta2> = model parameters.\n\n";

 19: #include <slepceps.h>

 21: /*
 22:    This example computes the eigenvalues with largest real part of the
 23:    following matrix

 25:         A = [ tau1*T+(beta-1)*I     alpha^2*I
 26:                   -beta*I        tau2*T-alpha^2*I ],

 28:    where

 30:         T = tridiag{1,-2,1}
 31:         h = 1/(n+1)
 32:         tau1 = delta1/(h*L)^2
 33:         tau2 = delta2/(h*L)^2
 34:  */

 36: /* Matrix operations */
 37: PetscErrorCode MatMult_Brussel(Mat,Vec,Vec);
 38: PetscErrorCode MatGetDiagonal_Brussel(Mat,Vec);

 40: typedef struct {
 41:   Mat         T;
 42:   Vec         x1,x2,y1,y2;
 43:   PetscScalar alpha,beta,tau1,tau2,sigma;
 44: } CTX_BRUSSEL;

 46: int main(int argc,char **argv)
 47: {
 48:   EPS            eps;
 49:   Mat            A;
 50:   Vec            *Q,v;
 51:   PetscScalar    delta1,delta2,L,h,kr,ki;
 52:   PetscReal      errest,tol,re,im,lev;
 53:   PetscInt       N=30,n,i,j,Istart,Iend,nev,nconv;
 54:   CTX_BRUSSEL    *ctx;
 55:   PetscBool      errok,trueres;

 58:   SlepcInitialize(&argc,&argv,(char*)0,help);if (ierr) return ierr;
 59:   PetscOptionsGetInt(NULL,NULL,"-n",&N,NULL);
 60:   PetscPrintf(PETSC_COMM_WORLD,"\nBrusselator wave model, n=%D\n\n",N);

 62:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
 63:         Generate the matrix
 64:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

 66:   PetscNew(&ctx);
 67:   ctx->alpha = 2.0;
 68:   ctx->beta  = 5.45;
 69:   delta1     = 0.008;
 70:   delta2     = 0.004;
 71:   L          = 0.51302;

 73:   PetscOptionsGetScalar(NULL,NULL,"-L",&L,NULL);
 74:   PetscOptionsGetScalar(NULL,NULL,"-alpha",&ctx->alpha,NULL);
 75:   PetscOptionsGetScalar(NULL,NULL,"-beta",&ctx->beta,NULL);
 76:   PetscOptionsGetScalar(NULL,NULL,"-delta1",&delta1,NULL);
 77:   PetscOptionsGetScalar(NULL,NULL,"-delta2",&delta2,NULL);

 79:   /* Create matrix T */
 80:   MatCreate(PETSC_COMM_WORLD,&ctx->T);
 81:   MatSetSizes(ctx->T,PETSC_DECIDE,PETSC_DECIDE,N,N);
 82:   MatSetFromOptions(ctx->T);
 83:   MatSetUp(ctx->T);
 84:   MatGetOwnershipRange(ctx->T,&Istart,&Iend);
 85:   for (i=Istart;i<Iend;i++) {
 86:     if (i>0) { MatSetValue(ctx->T,i,i-1,1.0,INSERT_VALUES); }
 87:     if (i<N-1) { MatSetValue(ctx->T,i,i+1,1.0,INSERT_VALUES); }
 88:     MatSetValue(ctx->T,i,i,-2.0,INSERT_VALUES);
 89:   }
 90:   MatAssemblyBegin(ctx->T,MAT_FINAL_ASSEMBLY);
 91:   MatAssemblyEnd(ctx->T,MAT_FINAL_ASSEMBLY);
 92:   MatGetLocalSize(ctx->T,&n,NULL);

 94:   /* Fill the remaining information in the shell matrix context
 95:      and create auxiliary vectors */
 96:   h = 1.0 / (PetscReal)(N+1);
 97:   ctx->tau1 = delta1 / ((h*L)*(h*L));
 98:   ctx->tau2 = delta2 / ((h*L)*(h*L));
 99:   ctx->sigma = 0.0;
100:   VecCreateMPIWithArray(PETSC_COMM_WORLD,1,n,PETSC_DECIDE,NULL,&ctx->x1);
101:   VecCreateMPIWithArray(PETSC_COMM_WORLD,1,n,PETSC_DECIDE,NULL,&ctx->x2);
102:   VecCreateMPIWithArray(PETSC_COMM_WORLD,1,n,PETSC_DECIDE,NULL,&ctx->y1);
103:   VecCreateMPIWithArray(PETSC_COMM_WORLD,1,n,PETSC_DECIDE,NULL,&ctx->y2);

105:   /* Create the shell matrix */
106:   MatCreateShell(PETSC_COMM_WORLD,2*n,2*n,2*N,2*N,(void*)ctx,&A);
107:   MatShellSetOperation(A,MATOP_MULT,(void(*)(void))MatMult_Brussel);
108:   MatShellSetOperation(A,MATOP_GET_DIAGONAL,(void(*)(void))MatGetDiagonal_Brussel);

110:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
111:                 Create the eigensolver and solve the problem
112:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

114:   EPSCreate(PETSC_COMM_WORLD,&eps);
115:   EPSSetOperators(eps,A,NULL);
116:   EPSSetProblemType(eps,EPS_NHEP);
117:   EPSSetWhichEigenpairs(eps,EPS_LARGEST_REAL);
118:   EPSSetTrueResidual(eps,PETSC_FALSE);
119:   EPSSetFromOptions(eps);
120:   EPSSolve(eps);

122:   EPSGetTrueResidual(eps,&trueres);
123:   /*if (trueres) { PetscPrintf(PETSC_COMM_WORLD," Computing true residuals explicitly\n\n"); }*/

125:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
126:                     Display solution and clean up
127:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

129:   EPSGetDimensions(eps,&nev,NULL,NULL);
130:   EPSGetTolerances(eps,&tol,NULL);
131:   EPSGetConverged(eps,&nconv);
132:   if (nconv<nev) {
133:     PetscPrintf(PETSC_COMM_WORLD," Problem: less than %D eigenvalues converged\n\n",nev);
134:   } else {
135:     /* Check that all converged eigenpairs satisfy the requested tolerance
136:        (in this example we use the solver's error estimate instead of computing
137:        the residual norm explicitly) */
138:     errok = PETSC_TRUE;
139:     for (i=0;i<nev;i++) {
140:       EPSGetErrorEstimate(eps,i,&errest);
141:       errok = (errok && errest<5.0*tol)? PETSC_TRUE: PETSC_FALSE;
142:     }
143:     if (!errok) {
144:       PetscPrintf(PETSC_COMM_WORLD," Problem: some of the first %D relative errors are higher than the tolerance\n\n",nev);
145:     } else {
146:       PetscPrintf(PETSC_COMM_WORLD," All requested eigenvalues computed up to the required tolerance:");
147:       for (i=0;i<=(nev-1)/8;i++) {
148:         PetscPrintf(PETSC_COMM_WORLD,"\n     ");
149:         for (j=0;j<PetscMin(8,nev-8*i);j++) {
150:           EPSGetEigenpair(eps,8*i+j,&kr,&ki,NULL,NULL);
151: #if defined(PETSC_USE_COMPLEX)
152:           re = PetscRealPart(kr);
153:           im = PetscImaginaryPart(kr);
154: #else
155:           re = kr;
156:           im = ki;
157: #endif
158:           if (PetscAbs(re)/PetscAbs(im)<PETSC_SMALL) re = 0.0;
159:           if (PetscAbs(im)/PetscAbs(re)<PETSC_SMALL) im = 0.0;
160:           if (im!=0.0) {
161:             PetscPrintf(PETSC_COMM_WORLD,"%.5f%+.5fi",(double)re,(double)im);
162:           } else {
163:             PetscPrintf(PETSC_COMM_WORLD,"%.5f",(double)re);
164:           }
165:           if (8*i+j+1<nev) { PetscPrintf(PETSC_COMM_WORLD,", "); }
166:         }
167:       }
168:       PetscPrintf(PETSC_COMM_WORLD,"\n\n");
169:     }
170:   }

172:   /* Get an orthogonal basis of the invariant subspace and check it is indeed
173:      orthogonal (note that eigenvectors are not orthogonal in this case) */
174:   if (nconv>1) {
175:     MatCreateVecs(A,&v,NULL);
176:     VecDuplicateVecs(v,nconv,&Q);
177:     EPSGetInvariantSubspace(eps,Q);
178:     VecCheckOrthogonality(Q,nconv,NULL,nconv,NULL,NULL,&lev);
179:     if (lev<10*tol) {
180:       PetscPrintf(PETSC_COMM_WORLD,"Level of orthogonality below the tolerance\n");
181:     } else {
182:       PetscPrintf(PETSC_COMM_WORLD,"Level of orthogonality: %g\n",(double)lev);
183:     }
184:     VecDestroyVecs(nconv,&Q);
185:     VecDestroy(&v);
186:   }

188:   EPSDestroy(&eps);
189:   MatDestroy(&A);
190:   MatDestroy(&ctx->T);
191:   VecDestroy(&ctx->x1);
192:   VecDestroy(&ctx->x2);
193:   VecDestroy(&ctx->y1);
194:   VecDestroy(&ctx->y2);
195:   PetscFree(ctx);
196:   SlepcFinalize();
197:   return ierr;
198: }

200: PetscErrorCode MatMult_Brussel(Mat A,Vec x,Vec y)
201: {
202:   PetscInt          n;
203:   const PetscScalar *px;
204:   PetscScalar       *py;
205:   CTX_BRUSSEL       *ctx;
206:   PetscErrorCode    ierr;

209:   MatShellGetContext(A,(void**)&ctx);
210:   MatGetLocalSize(ctx->T,&n,NULL);
211:   VecGetArrayRead(x,&px);
212:   VecGetArray(y,&py);
213:   VecPlaceArray(ctx->x1,px);
214:   VecPlaceArray(ctx->x2,px+n);
215:   VecPlaceArray(ctx->y1,py);
216:   VecPlaceArray(ctx->y2,py+n);

218:   MatMult(ctx->T,ctx->x1,ctx->y1);
219:   VecScale(ctx->y1,ctx->tau1);
220:   VecAXPY(ctx->y1,ctx->beta - 1.0 + ctx->sigma,ctx->x1);
221:   VecAXPY(ctx->y1,ctx->alpha * ctx->alpha,ctx->x2);

223:   MatMult(ctx->T,ctx->x2,ctx->y2);
224:   VecScale(ctx->y2,ctx->tau2);
225:   VecAXPY(ctx->y2,-ctx->beta,ctx->x1);
226:   VecAXPY(ctx->y2,-ctx->alpha * ctx->alpha + ctx->sigma,ctx->x2);

228:   VecRestoreArrayRead(x,&px);
229:   VecRestoreArray(y,&py);
230:   VecResetArray(ctx->x1);
231:   VecResetArray(ctx->x2);
232:   VecResetArray(ctx->y1);
233:   VecResetArray(ctx->y2);
234:   return(0);
235: }

237: PetscErrorCode MatGetDiagonal_Brussel(Mat A,Vec diag)
238: {
239:   Vec            d1,d2;
240:   PetscInt       n;
241:   PetscScalar    *pd;
242:   MPI_Comm       comm;
243:   CTX_BRUSSEL    *ctx;

247:   MatShellGetContext(A,(void**)&ctx);
248:   PetscObjectGetComm((PetscObject)A,&comm);
249:   MatGetLocalSize(ctx->T,&n,NULL);
250:   VecGetArray(diag,&pd);
251:   VecCreateMPIWithArray(comm,1,n,PETSC_DECIDE,pd,&d1);
252:   VecCreateMPIWithArray(comm,1,n,PETSC_DECIDE,pd+n,&d2);

254:   VecSet(d1,-2.0*ctx->tau1 + ctx->beta - 1.0 + ctx->sigma);
255:   VecSet(d2,-2.0*ctx->tau2 - ctx->alpha*ctx->alpha + ctx->sigma);

257:   VecDestroy(&d1);
258:   VecDestroy(&d2);
259:   VecRestoreArray(diag,&pd);
260:   return(0);
261: }

263: /*TEST

265:    test:
266:       suffix: 1
267:       args: -eps_nev 4 -eps_true_residual {{0 1}}
268:       requires: !complex !single
269:       output_file: output/test22_1.out

271:    test:
272:       suffix: 2
273:       args: -eps_nev 4 -eps_true_residual -eps_balance oneside -eps_tol 1e-7
274:       requires: !complex !single

276: TEST*/