Actual source code: acoustic_wave_1d.c

slepc-3.16.1 2021-11-17
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  1: /*
  2:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  3:    SLEPc - Scalable Library for Eigenvalue Problem Computations
  4:    Copyright (c) 2002-2021, 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;

 41:   SlepcInitialize(&argc,&argv,(char*)0,help);if (ierr) return ierr;

 43:   PetscOptionsGetInt(NULL,NULL,"-n",&n,NULL);
 44:   PetscOptionsGetScalar(NULL,NULL,"-z",&z,NULL);
 45:   SlepcSNPrintfScalar(str,sizeof(str),z,PETSC_FALSE);
 46:   PetscPrintf(PETSC_COMM_WORLD,"\nAcoustic wave 1-D, n=%D 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:   MatCreate(PETSC_COMM_WORLD,&K);
 54:   MatSetSizes(K,PETSC_DECIDE,PETSC_DECIDE,n,n);
 55:   MatSetFromOptions(K);
 56:   MatSetUp(K);

 58:   MatGetOwnershipRange(K,&Istart,&Iend);
 59:   for (i=Istart;i<Iend;i++) {
 60:     if (i>0) {
 61:       MatSetValue(K,i,i-1,-1.0*n,INSERT_VALUES);
 62:     }
 63:     if (i<n-1) {
 64:       MatSetValue(K,i,i,2.0*n,INSERT_VALUES);
 65:       MatSetValue(K,i,i+1,-1.0*n,INSERT_VALUES);
 66:     } else {
 67:       MatSetValue(K,i,i,1.0*n,INSERT_VALUES);
 68:     }
 69:   }

 71:   MatAssemblyBegin(K,MAT_FINAL_ASSEMBLY);
 72:   MatAssemblyEnd(K,MAT_FINAL_ASSEMBLY);

 74:   /* C is the zero matrix but one element*/
 75:   MatCreate(PETSC_COMM_WORLD,&C);
 76:   MatSetSizes(C,PETSC_DECIDE,PETSC_DECIDE,n,n);
 77:   MatSetFromOptions(C);
 78:   MatSetUp(C);

 80:   MatGetOwnershipRange(C,&Istart,&Iend);
 81:   if (n-1>=Istart && n-1<Iend) {
 82:     MatSetValue(C,n-1,n-1,-2*PETSC_PI/z,INSERT_VALUES);
 83:   }
 84:   MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);
 85:   MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);

 87:   /* M is a diagonal matrix */
 88:   MatCreate(PETSC_COMM_WORLD,&M);
 89:   MatSetSizes(M,PETSC_DECIDE,PETSC_DECIDE,n,n);
 90:   MatSetFromOptions(M);
 91:   MatSetUp(M);

 93:   MatGetOwnershipRange(M,&Istart,&Iend);
 94:   for (i=Istart;i<Iend;i++) {
 95:     if (i<n-1) {
 96:       MatSetValue(M,i,i,4*PETSC_PI*PETSC_PI/n,INSERT_VALUES);
 97:     } else {
 98:       MatSetValue(M,i,i,2*PETSC_PI*PETSC_PI/n,INSERT_VALUES);
 99:     }
100:   }
101:   MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);
102:   MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);

104:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
105:                 Create the eigensolver and solve the problem
106:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

108:   PEPCreate(PETSC_COMM_WORLD,&pep);
109:   A[0] = K; A[1] = C; A[2] = M;
110:   PEPSetOperators(pep,3,A);
111:   PEPSetFromOptions(pep);
112:   PEPSolve(pep);

114:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
115:                     Display solution and clean up
116:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

118:   /* show detailed info unless -terse option is given by user */
119:   PetscOptionsHasName(NULL,NULL,"-terse",&terse);
120:   if (terse) {
121:     PEPErrorView(pep,PEP_ERROR_BACKWARD,NULL);
122:   } else {
123:     PetscViewerPushFormat(PETSC_VIEWER_STDOUT_WORLD,PETSC_VIEWER_ASCII_INFO_DETAIL);
124:     PEPConvergedReasonView(pep,PETSC_VIEWER_STDOUT_WORLD);
125:     PEPErrorView(pep,PEP_ERROR_BACKWARD,PETSC_VIEWER_STDOUT_WORLD);
126:     PetscViewerPopFormat(PETSC_VIEWER_STDOUT_WORLD);
127:   }
128:   PEPDestroy(&pep);
129:   MatDestroy(&M);
130:   MatDestroy(&C);
131:   MatDestroy(&K);
132:   SlepcFinalize();
133:   return ierr;
134: }

136: /*TEST

138:    testset:
139:       args: -pep_nev 4 -pep_tol 1e-7 -n 24 -terse
140:       output_file: output/acoustic_wave_1d_1.out
141:       requires: !single
142:       test:
143:          suffix: 1
144:          args: -st_type sinvert -st_transform -pep_type {{toar qarnoldi linear}}
145:       test:
146:          suffix: 1_stoar
147:          args: -st_type sinvert -st_transform -pep_type stoar -pep_hermitian -pep_stoar_locking 0 -pep_stoar_nev 11 -pep_ncv 10
148:       test:
149:          suffix: 2
150:          args: -st_type sinvert -st_transform -pep_type toar -pep_extract {{none norm residual}}
151:       test:
152:          suffix: 3
153:          args: -st_type sinvert -pep_type linear -pep_extract {{none norm residual}}
154:       test:
155:          suffix: 4
156:          args: -pep_type jd

158: TEST*/