Actual source code: acoustic_wave_1d.c
slepc-3.18.1 2022-11-02
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;
41: SlepcInitialize(&argc,&argv,(char*)0,help);
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=%" 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: 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) MatSetValue(K,i,i-1,-1.0*n,INSERT_VALUES);
61: if (i<n-1) {
62: MatSetValue(K,i,i,2.0*n,INSERT_VALUES);
63: MatSetValue(K,i,i+1,-1.0*n,INSERT_VALUES);
64: } else MatSetValue(K,i,i,1.0*n,INSERT_VALUES);
65: }
67: MatAssemblyBegin(K,MAT_FINAL_ASSEMBLY);
68: MatAssemblyEnd(K,MAT_FINAL_ASSEMBLY);
70: /* C is the zero matrix but one element*/
71: MatCreate(PETSC_COMM_WORLD,&C);
72: MatSetSizes(C,PETSC_DECIDE,PETSC_DECIDE,n,n);
73: MatSetFromOptions(C);
74: MatSetUp(C);
76: MatGetOwnershipRange(C,&Istart,&Iend);
77: if (n-1>=Istart && n-1<Iend) MatSetValue(C,n-1,n-1,-2*PETSC_PI/z,INSERT_VALUES);
78: MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);
79: MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);
81: /* M is a diagonal matrix */
82: MatCreate(PETSC_COMM_WORLD,&M);
83: MatSetSizes(M,PETSC_DECIDE,PETSC_DECIDE,n,n);
84: MatSetFromOptions(M);
85: MatSetUp(M);
87: MatGetOwnershipRange(M,&Istart,&Iend);
88: for (i=Istart;i<Iend;i++) {
89: if (i<n-1) MatSetValue(M,i,i,4*PETSC_PI*PETSC_PI/n,INSERT_VALUES);
90: else MatSetValue(M,i,i,2*PETSC_PI*PETSC_PI/n,INSERT_VALUES);
91: }
92: MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);
93: MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);
95: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
96: Create the eigensolver and solve the problem
97: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
99: PEPCreate(PETSC_COMM_WORLD,&pep);
100: A[0] = K; A[1] = C; A[2] = M;
101: PEPSetOperators(pep,3,A);
102: PEPSetFromOptions(pep);
103: PEPSolve(pep);
105: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
106: Display solution and clean up
107: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
109: /* show detailed info unless -terse option is given by user */
110: PetscOptionsHasName(NULL,NULL,"-terse",&terse);
111: if (terse) PEPErrorView(pep,PEP_ERROR_BACKWARD,NULL);
112: else {
113: PetscViewerPushFormat(PETSC_VIEWER_STDOUT_WORLD,PETSC_VIEWER_ASCII_INFO_DETAIL);
114: PEPConvergedReasonView(pep,PETSC_VIEWER_STDOUT_WORLD);
115: PEPErrorView(pep,PEP_ERROR_BACKWARD,PETSC_VIEWER_STDOUT_WORLD);
116: PetscViewerPopFormat(PETSC_VIEWER_STDOUT_WORLD);
117: }
118: PEPDestroy(&pep);
119: MatDestroy(&M);
120: MatDestroy(&C);
121: MatDestroy(&K);
122: SlepcFinalize();
123: return 0;
124: }
126: /*TEST
128: testset:
129: args: -pep_nev 4 -pep_tol 1e-7 -n 24 -terse
130: output_file: output/acoustic_wave_1d_1.out
131: requires: !single
132: test:
133: suffix: 1
134: args: -st_type sinvert -st_transform -pep_type {{toar qarnoldi linear}}
135: test:
136: suffix: 1_stoar
137: args: -st_type sinvert -st_transform -pep_type stoar -pep_hermitian -pep_stoar_locking 0 -pep_stoar_nev 11 -pep_ncv 10
138: test:
139: suffix: 2
140: args: -st_type sinvert -st_transform -pep_type toar -pep_extract {{none norm residual}}
141: test:
142: suffix: 3
143: args: -st_type sinvert -pep_type linear -pep_extract {{none norm residual}}
144: test:
145: suffix: 4
146: args: -pep_type jd
148: TEST*/