Date: 2022-11-02T11:47:03+00:00

Actual source code: ex24.c
slepc-3.18.1 2022-11-02
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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: */

     11: static char help[] = "Spectrum folding for a standard symmetric eigenproblem.\n\n"
     12:   "The problem matrix is the 2-D Laplacian.\n\n"
     13:   "The command line options are:\n"
     14:   "  -n <n>, where <n> = number of grid subdivisions in x dimension.\n"
     15:   "  -m <m>, where <m> = number of grid subdivisions in y dimension.\n";

     17: #include <slepceps.h>

     19: /*
     20:    User context for spectrum folding
     21: */
     22: typedef struct {
     23:   Mat       A;
     24:   Vec       w;
     25:   PetscReal target;
     26: } CTX_FOLD;

     28: /*
     29:    Auxiliary routines
     30: */
     31: PetscErrorCode MatMult_Fold(Mat,Vec,Vec);
     32: PetscErrorCode RayleighQuotient(Mat,Vec,PetscScalar*);
     33: PetscErrorCode ComputeResidualNorm(Mat,PetscScalar,Vec,PetscReal*);

     35: int main(int argc,char **argv)
     36: {
     37:   Mat            A,M,P;       /* problem matrix, shell matrix and preconditioner */
     38:   Vec            x;           /* eigenvector */
     39:   EPS            eps;         /* eigenproblem solver context */
     40:   ST             st;          /* spectral transformation */
     41:   KSP            ksp;
     42:   PC             pc;
     43:   EPSType        type;
     44:   CTX_FOLD       *ctx;
     45:   PetscInt       nconv,N,n=10,m,nloc,mloc,Istart,Iend,II,i,j;
     46:   PetscReal      *error,*evals,target=0.0,tol;
     47:   PetscScalar    lambda;
     48:   PetscBool      flag,terse,errok,hasmat;

     51:   SlepcInitialize(&argc,&argv,(char*)0,help);

     53:   PetscOptionsGetInt(NULL,NULL,"-n",&n,NULL);
     54:   PetscOptionsGetInt(NULL,NULL,"-m",&m,&flag);
     55:   if (!flag) m=n;
     56:   PetscOptionsGetReal(NULL,NULL,"-target",&target,NULL);
     57:   N = n*m;
     58:   PetscPrintf(PETSC_COMM_WORLD,"\nSpectrum Folding, N=%" PetscInt_FMT " (%" PetscInt_FMT "x%" PetscInt_FMT " grid) target=%f\n\n",N,n,m,(double)target);

     60:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     61:      Compute the 5-point stencil Laplacian
     62:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

     64:   MatCreate(PETSC_COMM_WORLD,&A);
     65:   MatSetSizes(A,PETSC_DECIDE,PETSC_DECIDE,N,N);
     66:   MatSetFromOptions(A);
     67:   MatSetUp(A);

     69:   MatGetOwnershipRange(A,&Istart,&Iend);
     70:   for (II=Istart;II<Iend;II++) {
     71:     i = II/n; j = II-i*n;
     72:     if (i>0) MatSetValue(A,II,II-n,-1.0,INSERT_VALUES);
     73:     if (i<m-1) MatSetValue(A,II,II+n,-1.0,INSERT_VALUES);
     74:     if (j>0) MatSetValue(A,II,II-1,-1.0,INSERT_VALUES);
     75:     if (j<n-1) MatSetValue(A,II,II+1,-1.0,INSERT_VALUES);
     76:     MatSetValue(A,II,II,4.0,INSERT_VALUES);
     77:   }

     79:   MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
     80:   MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
     81:   MatCreateVecs(A,&x,NULL);
     82:   MatGetLocalSize(A,&nloc,&mloc);

     84:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     85:                 Create shell matrix to perform spectrum folding
     86:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
     87:   PetscNew(&ctx);
     88:   ctx->A = A;
     89:   ctx->target = target;
     90:   VecDuplicate(x,&ctx->w);

     92:   MatCreateShell(PETSC_COMM_WORLD,nloc,mloc,N,N,ctx,&M);
     93:   MatShellSetOperation(M,MATOP_MULT,(void(*)(void))MatMult_Fold);

     95:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     96:                 Create the eigensolver and set various options
     97:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

     99:   EPSCreate(PETSC_COMM_WORLD,&eps);
    100:   EPSSetOperators(eps,M,NULL);
    101:   EPSSetProblemType(eps,EPS_HEP);
    102:   EPSSetWhichEigenpairs(eps,EPS_SMALLEST_REAL);
    103:   EPSSetFromOptions(eps);

    105:   PetscObjectTypeCompareAny((PetscObject)eps,&flag,EPSGD,EPSJD,EPSBLOPEX,EPSLOBPCG,EPSRQCG,"");
    106:   if (flag) {
    107:     /*
    108:        Build preconditioner specific for this application (diagonal of A^2)
    109:     */
    110:     MatGetRowSum(A,x);
    111:     VecScale(x,-1.0);
    112:     VecShift(x,20.0);
    113:     MatCreate(PETSC_COMM_WORLD,&P);
    114:     MatSetSizes(P,PETSC_DECIDE,PETSC_DECIDE,N,N);
    115:     MatSetFromOptions(P);
    116:     MatSetUp(P);
    117:     MatDiagonalSet(P,x,INSERT_VALUES);
    118:     /*
    119:        Set diagonal preconditioner
    120:     */
    121:     EPSGetST(eps,&st);
    122:     STSetType(st,STPRECOND);
    123:     STSetPreconditionerMat(st,P);
    124:     MatDestroy(&P);
    125:     STGetKSP(st,&ksp);
    126:     KSPGetPC(ksp,&pc);
    127:     PCSetType(pc,PCJACOBI);
    128:     STPrecondGetKSPHasMat(st,&hasmat);
    129:     PetscPrintf(PETSC_COMM_WORLD," Preconditioned solver, hasmat=%s\n",hasmat?"true":"false");
    130:   }

    132:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    133:                       Solve the eigensystem
    134:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

    136:   EPSSolve(eps);
    137:   EPSGetType(eps,&type);
    138:   PetscPrintf(PETSC_COMM_WORLD," Solution method: %s\n\n",type);
    139:   EPSGetTolerances(eps,&tol,NULL);

    141:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    142:                     Display solution and clean up
    143:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

    145:   EPSGetConverged(eps,&nconv);
    146:   PetscPrintf(PETSC_COMM_WORLD," Number of converged eigenpairs: %" PetscInt_FMT "\n\n",nconv);
    147:   if (nconv>0) {
    148:     PetscMalloc2(nconv,&evals,nconv,&error);
    149:     for (i=0;i<nconv;i++) {
    150:       /*  Get i-th eigenvector, compute eigenvalue approximation from
    151:           Rayleigh quotient and compute residual norm */
    152:       EPSGetEigenpair(eps,i,NULL,NULL,x,NULL);
    153:       RayleighQuotient(A,x,&lambda);
    154:       ComputeResidualNorm(A,lambda,x,&error[i]);
    155: #if defined(PETSC_USE_COMPLEX)
    156:       evals[i] = PetscRealPart(lambda);
    157: #else
    158:       evals[i] = lambda;
    159: #endif
    160:     }
    161:     PetscOptionsHasName(NULL,NULL,"-terse",&terse);
    162:     if (!terse) {
    163:       PetscCall(PetscPrintf(PETSC_COMM_WORLD,
    164:            "           k              ||Ax-kx||\n"
    165:            "   ----------------- ------------------\n"));
    166:       for (i=0;i<nconv;i++) PetscPrintf(PETSC_COMM_WORLD,"   %12f       %12.2g\n",(double)evals[i],(double)error[i]);
    167:     } else {
    168:       errok = PETSC_TRUE;
    169:       for (i=0;i<nconv;i++) errok = (errok && error[i]<5.0*tol)? PETSC_TRUE: PETSC_FALSE;
    170:       if (!errok) PetscPrintf(PETSC_COMM_WORLD," Problem: some of the first %" PetscInt_FMT " relative errors are higher than the tolerance\n\n",nconv);
    171:       else {
    172:         PetscPrintf(PETSC_COMM_WORLD," nconv=%" PetscInt_FMT " eigenvalues computed up to the required tolerance:",nconv);
    173:         for (i=0;i<nconv;i++) PetscPrintf(PETSC_COMM_WORLD," %.5f",(double)evals[i]);
    174:       }
    175:     }
    176:     PetscPrintf(PETSC_COMM_WORLD,"\n");
    177:     PetscFree2(evals,error);
    178:   }

    180:   EPSDestroy(&eps);
    181:   MatDestroy(&A);
    182:   MatDestroy(&M);
    183:   VecDestroy(&ctx->w);
    184:   VecDestroy(&x);
    185:   PetscFree(ctx);
    186:   SlepcFinalize();
    187:   return 0;
    188: }

    190: /*
    191:     Matrix-vector product subroutine for the spectrum folding.
    192:        y <-- (A-t*I)^2*x
    193:  */
    194: PetscErrorCode MatMult_Fold(Mat M,Vec x,Vec y)
    195: {
    196:   CTX_FOLD       *ctx;
    197:   PetscScalar    sigma;

    200:   MatShellGetContext(M,&ctx);
    201:   sigma = -ctx->target;
    202:   MatMult(ctx->A,x,ctx->w);
    203:   VecAXPY(ctx->w,sigma,x);
    204:   MatMult(ctx->A,ctx->w,y);
    205:   VecAXPY(y,sigma,ctx->w);
    206:   return 0;
    207: }

    209: /*
    210:     Computes the Rayleigh quotient of a vector x
    211:        r <-- x^T*A*x       (assumes x has unit norm)
    212:  */
    213: PetscErrorCode RayleighQuotient(Mat A,Vec x,PetscScalar *r)
    214: {
    215:   Vec            Ax;

    218:   VecDuplicate(x,&Ax);
    219:   MatMult(A,x,Ax);
    220:   VecDot(Ax,x,r);
    221:   VecDestroy(&Ax);
    222:   return 0;
    223: }

    225: /*
    226:     Computes the residual norm of an approximate eigenvector x, |A*x-lambda*x|
    227:  */
    228: PetscErrorCode ComputeResidualNorm(Mat A,PetscScalar lambda,Vec x,PetscReal *r)
    229: {
    230:   Vec            Ax;

    233:   VecDuplicate(x,&Ax);
    234:   MatMult(A,x,Ax);
    235:   VecAXPY(Ax,-lambda,x);
    236:   VecNorm(Ax,NORM_2,r);
    237:   VecDestroy(&Ax);
    238:   return 0;
    239: }

    241: /*TEST

    243:    testset:
    244:       args: -n 15 -eps_nev 1 -eps_ncv 12 -eps_max_it 1000 -eps_tol 1e-5 -terse
    245:       filter: grep -v Solution
    246:       test:
    247:          suffix: 1
    248:       test:
    249:          suffix: 1_lobpcg
    250:          args: -eps_type lobpcg
    251:          requires: !single
    252:       test:
    253:          suffix: 1_gd
    254:          args: -eps_type gd
    255:          requires: !single

    257: TEST*/