Date: 2026-01-20T11:35:13+00:00

Actual source code: acoustic_wave_1d.c

      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: */
     10: /*
     11:    This example implements one of the problems found at
     12:        NLEVP: A Collection of Nonlinear Eigenvalue Problems,
     13:        The University of Manchester.
     14:    The details of the collection can be found at:
     15:        [1] T. Betcke et al., "NLEVP: A Collection of Nonlinear Eigenvalue
     16:            Problems", ACM Trans. Math. Software 39(2), Article 7, 2013.

     18:    The acoustic_wave_1d problem is a QEP from an acoustics application.
     19:    Here we solve it with the eigenvalue scaled by the imaginary unit, to be
     20:    able to use real arithmetic, so the computed eigenvalues should be scaled
     21:    back.
     22: */

     24: static char help[] = "Quadratic eigenproblem from an acoustics application (1-D).\n\n"
     25:   "The command line options are:\n"
     26:   "  -n <n>, where <n> = dimension of the matrices.\n"
     27:   "  -z <z>, where <z> = impedance (default 1.0).\n\n";

     29: #include <slepcpep.h>

     31: int main(int argc,char **argv)
     32: {
     33:   Mat            M,C,K,A[3];      /* problem matrices */
     34:   PEP            pep;             /* polynomial eigenproblem solver context */
     35:   PetscInt       n=10,Istart,Iend,i;
     36:   PetscScalar    z=1.0;
     37:   char           str[50];
     38:   PetscBool      terse;

     40:   PetscFunctionBeginUser;
     41:   PetscCall(SlepcInitialize(&argc,&argv,NULL,help));

     43:   PetscCall(PetscOptionsGetInt(NULL,NULL,"-n",&n,NULL));
     44:   PetscCall(PetscOptionsGetScalar(NULL,NULL,"-z",&z,NULL));
     45:   PetscCall(SlepcSNPrintfScalar(str,sizeof(str),z,PETSC_FALSE));
     46:   PetscCall(PetscPrintf(PETSC_COMM_WORLD,"\nAcoustic wave 1-D, n=%" PetscInt_FMT " z=%s\n\n",n,str));

     48:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     49:      Compute the matrices that define the eigensystem, (k^2*M+k*C+K)x=0
     50:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

     52:   /* K is a tridiagonal */
     53:   PetscCall(MatCreate(PETSC_COMM_WORLD,&K));
     54:   PetscCall(MatSetSizes(K,PETSC_DECIDE,PETSC_DECIDE,n,n));
     55:   PetscCall(MatSetFromOptions(K));

     57:   PetscCall(MatGetOwnershipRange(K,&Istart,&Iend));
     58:   for (i=Istart;i<Iend;i++) {
     59:     if (i>0) PetscCall(MatSetValue(K,i,i-1,-1.0*n,INSERT_VALUES));
     60:     if (i<n-1) {
     61:       PetscCall(MatSetValue(K,i,i,2.0*n,INSERT_VALUES));
     62:       PetscCall(MatSetValue(K,i,i+1,-1.0*n,INSERT_VALUES));
     63:     } else PetscCall(MatSetValue(K,i,i,1.0*n,INSERT_VALUES));
     64:   }

     66:   PetscCall(MatAssemblyBegin(K,MAT_FINAL_ASSEMBLY));
     67:   PetscCall(MatAssemblyEnd(K,MAT_FINAL_ASSEMBLY));

     69:   /* C is the zero matrix but one element*/
     70:   PetscCall(MatCreate(PETSC_COMM_WORLD,&C));
     71:   PetscCall(MatSetSizes(C,PETSC_DECIDE,PETSC_DECIDE,n,n));
     72:   PetscCall(MatSetFromOptions(C));

     74:   PetscCall(MatGetOwnershipRange(C,&Istart,&Iend));
     75:   if (n-1>=Istart && n-1<Iend) PetscCall(MatSetValue(C,n-1,n-1,-2*PETSC_PI/z,INSERT_VALUES));
     76:   PetscCall(MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY));
     77:   PetscCall(MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY));

     79:   /* M is a diagonal matrix */
     80:   PetscCall(MatCreate(PETSC_COMM_WORLD,&M));
     81:   PetscCall(MatSetSizes(M,PETSC_DECIDE,PETSC_DECIDE,n,n));
     82:   PetscCall(MatSetFromOptions(M));

     84:   PetscCall(MatGetOwnershipRange(M,&Istart,&Iend));
     85:   for (i=Istart;i<Iend;i++) {
     86:     if (i<n-1) PetscCall(MatSetValue(M,i,i,4*PETSC_PI*PETSC_PI/n,INSERT_VALUES));
     87:     else PetscCall(MatSetValue(M,i,i,2*PETSC_PI*PETSC_PI/n,INSERT_VALUES));
     88:   }
     89:   PetscCall(MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY));
     90:   PetscCall(MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY));

     92:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     93:                 Create the eigensolver and solve the problem
     94:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

     96:   PetscCall(PEPCreate(PETSC_COMM_WORLD,&pep));
     97:   A[0] = K; A[1] = C; A[2] = M;
     98:   PetscCall(PEPSetOperators(pep,3,A));
     99:   PetscCall(PEPSetFromOptions(pep));
    100:   PetscCall(PEPSolve(pep));

    102:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    103:                     Display solution and clean up
    104:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

    106:   /* show detailed info unless -terse option is given by user */
    107:   PetscCall(PetscOptionsHasName(NULL,NULL,"-terse",&terse));
    108:   if (terse) PetscCall(PEPErrorView(pep,PEP_ERROR_BACKWARD,NULL));
    109:   else {
    110:     PetscCall(PetscViewerPushFormat(PETSC_VIEWER_STDOUT_WORLD,PETSC_VIEWER_ASCII_INFO_DETAIL));
    111:     PetscCall(PEPConvergedReasonView(pep,PETSC_VIEWER_STDOUT_WORLD));
    112:     PetscCall(PEPErrorView(pep,PEP_ERROR_BACKWARD,PETSC_VIEWER_STDOUT_WORLD));
    113:     PetscCall(PetscViewerPopFormat(PETSC_VIEWER_STDOUT_WORLD));
    114:   }
    115:   PetscCall(PEPDestroy(&pep));
    116:   PetscCall(MatDestroy(&M));
    117:   PetscCall(MatDestroy(&C));
    118:   PetscCall(MatDestroy(&K));
    119:   PetscCall(SlepcFinalize());
    120:   return 0;
    121: }

    123: /*TEST

    125:    testset:
    126:       args: -pep_nev 4 -pep_tol 1e-7 -n 24 -terse
    127:       output_file: output/acoustic_wave_1d_1.out
    128:       requires: !single
    129:       test:
    130:          suffix: 1
    131:          args: -st_type sinvert -st_transform -pep_type {{toar qarnoldi linear}}
    132:       test:
    133:          suffix: 1_stoar
    134:          args: -st_type sinvert -st_transform -pep_type stoar -pep_hermitian -pep_stoar_locking 0 -pep_stoar_nev 11 -pep_ncv 10
    135:       test:
    136:          suffix: 2
    137:          args: -st_type sinvert -st_transform -pep_type toar -pep_extract {{none norm residual}}
    138:       test:
    139:          suffix: 3
    140:          args: -st_type sinvert -pep_type linear -pep_extract {{none norm residual}}
    141:       test:
    142:          suffix: 4
    143:          args: -pep_type jd

    145: TEST*/