Date: 2023-01-26T12:18:49+00:00

Actual source code: test22.c
slepc-3.18.2 2023-01-26
Report Typos and Errors

      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: */

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

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

    181:   EPSDestroy(&eps);
    182:   MatDestroy(&A);
    183:   MatDestroy(&ctx->T);
    184:   VecDestroy(&ctx->x1);
    185:   VecDestroy(&ctx->x2);
    186:   VecDestroy(&ctx->y1);
    187:   VecDestroy(&ctx->y2);
    188:   PetscFree(ctx);
    189:   SlepcFinalize();
    190:   return 0;
    191: }

    193: PetscErrorCode MatMult_Brussel(Mat A,Vec x,Vec y)
    194: {
    195:   PetscInt          n;
    196:   const PetscScalar *px;
    197:   PetscScalar       *py;
    198:   CTX_BRUSSEL       *ctx;

    201:   MatShellGetContext(A,&ctx);
    202:   MatGetLocalSize(ctx->T,&n,NULL);
    203:   VecGetArrayRead(x,&px);
    204:   VecGetArray(y,&py);
    205:   VecPlaceArray(ctx->x1,px);
    206:   VecPlaceArray(ctx->x2,px+n);
    207:   VecPlaceArray(ctx->y1,py);
    208:   VecPlaceArray(ctx->y2,py+n);

    210:   MatMult(ctx->T,ctx->x1,ctx->y1);
    211:   VecScale(ctx->y1,ctx->tau1);
    212:   VecAXPY(ctx->y1,ctx->beta - 1.0 + ctx->sigma,ctx->x1);
    213:   VecAXPY(ctx->y1,ctx->alpha * ctx->alpha,ctx->x2);

    215:   MatMult(ctx->T,ctx->x2,ctx->y2);
    216:   VecScale(ctx->y2,ctx->tau2);
    217:   VecAXPY(ctx->y2,-ctx->beta,ctx->x1);
    218:   VecAXPY(ctx->y2,-ctx->alpha * ctx->alpha + ctx->sigma,ctx->x2);

    220:   VecRestoreArrayRead(x,&px);
    221:   VecRestoreArray(y,&py);
    222:   VecResetArray(ctx->x1);
    223:   VecResetArray(ctx->x2);
    224:   VecResetArray(ctx->y1);
    225:   VecResetArray(ctx->y2);
    226:   return 0;
    227: }

    229: PetscErrorCode MatGetDiagonal_Brussel(Mat A,Vec diag)
    230: {
    231:   Vec            d1,d2;
    232:   PetscInt       n;
    233:   PetscScalar    *pd;
    234:   MPI_Comm       comm;
    235:   CTX_BRUSSEL    *ctx;

    238:   MatShellGetContext(A,&ctx);
    239:   PetscObjectGetComm((PetscObject)A,&comm);
    240:   MatGetLocalSize(ctx->T,&n,NULL);
    241:   VecGetArray(diag,&pd);
    242:   VecCreateMPIWithArray(comm,1,n,PETSC_DECIDE,pd,&d1);
    243:   VecCreateMPIWithArray(comm,1,n,PETSC_DECIDE,pd+n,&d2);

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

    248:   VecDestroy(&d1);
    249:   VecDestroy(&d2);
    250:   VecRestoreArray(diag,&pd);
    251:   return 0;
    252: }

    254: /*TEST

    256:    test:
    257:       suffix: 1
    258:       args: -eps_nev 4 -eps_true_residual {{0 1}}
    259:       requires: !single

    261:    test:
    262:       suffix: 2
    263:       args: -eps_nev 4 -eps_true_residual -eps_balance oneside -eps_tol 1e-7
    264:       requires: !single

    266:    test:
    267:       suffix: 3
    268:       args: -n 50 -eps_nev 4 -eps_ncv 16 -eps_type subspace -eps_largest_magnitude -bv_orthog_block {{gs tsqr chol tsqrchol svqb}}
    269:       requires: !single

    271: TEST*/