Date: 2017-05-17T08:26:23+00:00

Actual source code: ex24.c
slepc-3.7.4 2017-05-17
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      1: /*
      2:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      3:    SLEPc - Scalable Library for Eigenvalue Problem Computations
      4:    Copyright (c) 2002-2016, Universitat Politecnica de Valencia, Spain

      6:    This file is part of SLEPc.

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

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

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

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

     28: #include <slepceps.h>

     30: /*
     31:    User context for spectrum folding
     32: */
     33: typedef struct {
     34:   Mat       A;
     35:   Vec       w;
     36:   PetscReal target;
     37: } CTX_FOLD;

     39: /*
     40:    Auxiliary routines
     41: */
     42: PetscErrorCode MatMult_Fold(Mat,Vec,Vec);
     43: PetscErrorCode RayleighQuotient(Mat,Vec,PetscScalar*);
     44: PetscErrorCode ComputeResidualNorm(Mat,PetscScalar,Vec,PetscReal*);

     48: int main(int argc,char **argv)
     49: {
     50:   Mat            A,M,P;       /* problem matrix, shell matrix and preconditioner */
     51:   Vec            x;           /* eigenvector */
     52:   EPS            eps;         /* eigenproblem solver context */
     53:   ST             st;          /* spectral transformation */
     54:   KSP            ksp;
     55:   PC             pc;
     56:   EPSType        type;
     57:   CTX_FOLD       *ctx;
     58:   PetscInt       nconv,N,n=10,m,Istart,Iend,II,i,j;
     59:   PetscReal      *error,*evals,target=2.1,tol;
     60:   PetscScalar    lambda;
     61:   PetscBool      flag,terse,errok;

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

     66:   PetscOptionsGetInt(NULL,NULL,"-n",&n,NULL);
     67:   PetscOptionsGetInt(NULL,NULL,"-m",&m,&flag);
     68:   if (!flag) m=n;
     69:   PetscOptionsGetReal(NULL,NULL,"-target",&target,NULL);
     70:   N = n*m;
     71:   PetscPrintf(PETSC_COMM_WORLD,"\nSpectrum Folding, N=%D (%Dx%D grid) target=%f\n\n",N,n,m,(double)target);

     73:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     74:      Compute the 5-point stencil Laplacian
     75:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

     77:   MatCreate(PETSC_COMM_WORLD,&A);
     78:   MatSetSizes(A,PETSC_DECIDE,PETSC_DECIDE,N,N);
     79:   MatSetFromOptions(A);
     80:   MatSetUp(A);

     82:   MatGetOwnershipRange(A,&Istart,&Iend);
     83:   for (II=Istart;II<Iend;II++) {
     84:     i = II/n; j = II-i*n;
     85:     if (i>0) { MatSetValue(A,II,II-n,-1.0,INSERT_VALUES); }
     86:     if (i<m-1) { MatSetValue(A,II,II+n,-1.0,INSERT_VALUES); }
     87:     if (j>0) { MatSetValue(A,II,II-1,-1.0,INSERT_VALUES); }
     88:     if (j<n-1) { MatSetValue(A,II,II+1,-1.0,INSERT_VALUES); }
     89:     MatSetValue(A,II,II,4.0,INSERT_VALUES);
     90:   }

     92:   MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
     93:   MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
     94:   MatCreateVecs(A,&x,NULL);

     96:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     97:                 Create shell matrix to perform spectrum folding
     98:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
     99:   PetscNew(&ctx);
    100:   ctx->A = A;
    101:   ctx->target = target;
    102:   VecDuplicate(x,&ctx->w);

    104:   MatCreateShell(PETSC_COMM_WORLD,N,N,N,N,ctx,&M);
    105:   MatSetFromOptions(M);
    106:   MatShellSetOperation(M,MATOP_MULT,(void(*)())MatMult_Fold);

    108:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    109:                 Create the eigensolver and set various options
    110:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

    112:   EPSCreate(PETSC_COMM_WORLD,&eps);
    113:   EPSSetOperators(eps,M,NULL);
    114:   EPSSetProblemType(eps,EPS_HEP);
    115:   EPSSetWhichEigenpairs(eps,EPS_SMALLEST_REAL);
    116:   EPSSetFromOptions(eps);

    118:   PetscObjectTypeCompareAny((PetscObject)eps,&flag,EPSBLOPEX,EPSRQCG,"");
    119:   if (flag) {
    120:     /*
    121:        Build preconditioner specific for this application (diagonal of A^2)
    122:     */
    123:     MatGetRowSum(A,x);
    124:     VecScale(x,-1.0);
    125:     VecShift(x,20.0);
    126:     MatCreate(PETSC_COMM_WORLD,&P);
    127:     MatSetSizes(P,PETSC_DECIDE,PETSC_DECIDE,N,N);
    128:     MatSetFromOptions(P);
    129:     MatSetUp(P);
    130:     MatDiagonalSet(P,x,INSERT_VALUES);
    131:     /*
    132:        Set diagonal preconditioner
    133:     */
    134:     EPSGetST(eps,&st);
    135:     STSetType(st,STPRECOND);
    136:     STPrecondSetMatForPC(st,P);
    137:     MatDestroy(&P);
    138:     STGetKSP(st,&ksp);
    139:     KSPGetPC(ksp,&pc);
    140:     PCSetType(pc,PCJACOBI);
    141:   }

    143:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    144:                       Solve the eigensystem
    145:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

    147:   EPSSolve(eps);
    148:   EPSGetType(eps,&type);
    149:   PetscPrintf(PETSC_COMM_WORLD," Solution method: %s\n\n",type);
    150:   EPSGetTolerances(eps,&tol,NULL);

    152:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    153:                     Display solution and clean up
    154:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

    156:   EPSGetConverged(eps,&nconv);
    157:   PetscPrintf(PETSC_COMM_WORLD," Number of converged eigenpairs: %D\n\n",nconv);
    158:   if (nconv>0) {
    159:     PetscMalloc2(nconv,&evals,nconv,&error);
    160:     for (i=0;i<nconv;i++) {
    161:       /*  Get i-th eigenvector, compute eigenvalue approximation from
    162:           Rayleigh quotient and compute residual norm */
    163:       EPSGetEigenpair(eps,i,NULL,NULL,x,NULL);
    164:       RayleighQuotient(A,x,&lambda);
    165:       ComputeResidualNorm(A,lambda,x,&error[i]);
    166: #if defined(PETSC_USE_COMPLEX)
    167:       evals[i] = PetscRealPart(lambda);
    168: #else
    169:       evals[i] = lambda;
    170: #endif
    171:     }
    172:     PetscOptionsHasName(NULL,NULL,"-terse",&terse);
    173:     if (!terse) {
    174:       PetscPrintf(PETSC_COMM_WORLD,
    175:            "           k              ||Ax-kx||\n"
    176:            "   ----------------- ------------------\n");
    177:       for (i=0;i<nconv;i++) {
    178:         PetscPrintf(PETSC_COMM_WORLD,"   %12f       %12.2g\n",(double)evals[i],(double)error[i]);
    179:       }
    180:     } else {
    181:       errok = PETSC_TRUE;
    182:       for (i=0;i<nconv;i++) errok = (errok && error[i]<5.0*tol)? PETSC_TRUE: PETSC_FALSE;
    183:       if (!errok) {
    184:         PetscPrintf(PETSC_COMM_WORLD," Problem: some of the first %D relative errors are higher than the tolerance\n\n",nconv);
    185:       } else {
    186:         PetscPrintf(PETSC_COMM_WORLD," nconv=%D eigenvalues computed up to the required tolerance:",nconv);
    187:         for (i=0;i<nconv;i++) {
    188:           PetscPrintf(PETSC_COMM_WORLD," %.5f",(double)evals[i]);
    189:         }
    190:       }
    191:     }
    192:     PetscPrintf(PETSC_COMM_WORLD,"\n");
    193:     PetscFree2(evals,error);
    194:   }

    196:   EPSDestroy(&eps);
    197:   MatDestroy(&A);
    198:   MatDestroy(&M);
    199:   VecDestroy(&ctx->w);
    200:   VecDestroy(&x);
    201:   PetscFree(ctx);
    202:   SlepcFinalize();
    203:   return ierr;
    204: }

    208: /*
    209:     Matrix-vector product subroutine for the spectrum folding.
    210:        y <-- (A-t*I)^2*x
    211:  */
    212: PetscErrorCode MatMult_Fold(Mat M,Vec x,Vec y)
    213: {
    214:   CTX_FOLD       *ctx;
    215:   PetscScalar    sigma;

    219:   MatShellGetContext(M,&ctx);
    220:   sigma = -ctx->target;
    221:   MatMult(ctx->A,x,ctx->w);
    222:   VecAXPY(ctx->w,sigma,x);
    223:   MatMult(ctx->A,ctx->w,y);
    224:   VecAXPY(y,sigma,ctx->w);
    225:   return(0);
    226: }

    230: /*
    231:     Computes the Rayleigh quotient of a vector x
    232:        r <-- x^T*A*x       (assumes x has unit norm)
    233:  */
    234: PetscErrorCode RayleighQuotient(Mat A,Vec x,PetscScalar *r)
    235: {
    236:   Vec            Ax;

    240:   VecDuplicate(x,&Ax);
    241:   MatMult(A,x,Ax);
    242:   VecDot(Ax,x,r);
    243:   VecDestroy(&Ax);
    244:   return(0);
    245: }

    249: /*
    250:     Computes the residual norm of an approximate eigenvector x, |A*x-lambda*x|
    251:  */
    252: PetscErrorCode ComputeResidualNorm(Mat A,PetscScalar lambda,Vec x,PetscReal *r)
    253: {
    254:   Vec            Ax;

    258:   VecDuplicate(x,&Ax);
    259:   MatMult(A,x,Ax);
    260:   VecAXPY(Ax,-lambda,x);
    261:   VecNorm(Ax,NORM_2,r);
    262:   VecDestroy(&Ax);
    263:   return(0);
    264: }