Actual source code: test6.c
slepc-3.11.2 2019-07-30
1: /*
2: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
3: SLEPc - Scalable Library for Eigenvalue Problem Computations
4: Copyright (c) 2002-2019, 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: Example based on spring problem in NLEVP collection [1]. See the parameters
12: meaning at Example 2 in [2].
14: [1] T. Betcke, N. J. Higham, V. Mehrmann, C. Schroder, and F. Tisseur,
15: NLEVP: A Collection of Nonlinear Eigenvalue Problems, MIMS EPrint
16: 2010.98, November 2010.
17: [2] F. Tisseur, Backward error and condition of polynomial eigenvalue
18: problems, Linear Algebra and its Applications, 309 (2000), pp. 339--361,
19: April 2000.
20: */
22: static char help[] = "Tests multiple calls to PEPSolve with different matrix of different size.\n\n"
23: "This is based on the spring problem from NLEVP collection.\n\n"
24: "The command line options are:\n"
25: " -n <n> ... number of grid subdivisions.\n"
26: " -mu <value> ... mass (default 1).\n"
27: " -tau <value> ... damping constant of the dampers (default 10).\n"
28: " -kappa <value> ... damping constant of the springs (default 5).\n"
29: " -initv ... set an initial vector.\n\n";
31: #include <slepcpep.h>
33: int main(int argc,char **argv)
34: {
35: Mat M,C,K,A[3]; /* problem matrices */
36: PEP pep; /* polynomial eigenproblem solver context */
38: PetscInt n=30,Istart,Iend,i,nev;
39: PetscScalar mu=1.0,tau=10.0,kappa=5.0;
40: PetscBool terse=PETSC_FALSE;
42: SlepcInitialize(&argc,&argv,(char*)0,help);if (ierr) return ierr;
44: PetscOptionsGetInt(NULL,NULL,"-n",&n,NULL);
45: PetscOptionsGetScalar(NULL,NULL,"-mu",&mu,NULL);
46: PetscOptionsGetScalar(NULL,NULL,"-tau",&tau,NULL);
47: PetscOptionsGetScalar(NULL,NULL,"-kappa",&kappa,NULL);
49: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
50: Compute the matrices that define the eigensystem, (k^2*M+k*C+K)x=0
51: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
53: /* K is a tridiagonal */
54: MatCreate(PETSC_COMM_WORLD,&K);
55: MatSetSizes(K,PETSC_DECIDE,PETSC_DECIDE,n,n);
56: MatSetFromOptions(K);
57: MatSetUp(K);
59: MatGetOwnershipRange(K,&Istart,&Iend);
60: for (i=Istart;i<Iend;i++) {
61: if (i>0) {
62: MatSetValue(K,i,i-1,-kappa,INSERT_VALUES);
63: }
64: MatSetValue(K,i,i,kappa*3.0,INSERT_VALUES);
65: if (i<n-1) {
66: MatSetValue(K,i,i+1,-kappa,INSERT_VALUES);
67: }
68: }
70: MatAssemblyBegin(K,MAT_FINAL_ASSEMBLY);
71: MatAssemblyEnd(K,MAT_FINAL_ASSEMBLY);
73: /* C is a tridiagonal */
74: MatCreate(PETSC_COMM_WORLD,&C);
75: MatSetSizes(C,PETSC_DECIDE,PETSC_DECIDE,n,n);
76: MatSetFromOptions(C);
77: MatSetUp(C);
79: MatGetOwnershipRange(C,&Istart,&Iend);
80: for (i=Istart;i<Iend;i++) {
81: if (i>0) {
82: MatSetValue(C,i,i-1,-tau,INSERT_VALUES);
83: }
84: MatSetValue(C,i,i,tau*3.0,INSERT_VALUES);
85: if (i<n-1) {
86: MatSetValue(C,i,i+1,-tau,INSERT_VALUES);
87: }
88: }
90: MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);
91: MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);
93: /* M is a diagonal matrix */
94: MatCreate(PETSC_COMM_WORLD,&M);
95: MatSetSizes(M,PETSC_DECIDE,PETSC_DECIDE,n,n);
96: MatSetFromOptions(M);
97: MatSetUp(M);
98: MatGetOwnershipRange(M,&Istart,&Iend);
99: for (i=Istart;i<Iend;i++) {
100: MatSetValue(M,i,i,mu,INSERT_VALUES);
101: }
102: MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);
103: MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);
105: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
106: Create the eigensolver and set various options
107: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
109: PEPCreate(PETSC_COMM_WORLD,&pep);
110: A[0] = K; A[1] = C; A[2] = M;
111: PEPSetOperators(pep,3,A);
112: PEPSetProblemType(pep,PEP_GENERAL);
113: PEPSetTolerances(pep,PETSC_SMALL,PETSC_DEFAULT);
114: PEPSetFromOptions(pep);
116: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
117: Solve the eigensystem
118: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
120: PEPSolve(pep);
121: PEPGetDimensions(pep,&nev,NULL,NULL);
122: PetscPrintf(PETSC_COMM_WORLD," Number of requested eigenvalues: %D\n",nev);
124: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
125: Display solution of first solve
126: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
127: PetscOptionsHasName(NULL,NULL,"-terse",&terse);
128: if (terse) {
129: PEPErrorView(pep,PEP_ERROR_BACKWARD,NULL);
130: } else {
131: PetscViewerPushFormat(PETSC_VIEWER_STDOUT_WORLD,PETSC_VIEWER_ASCII_INFO_DETAIL);
132: PEPReasonView(pep,PETSC_VIEWER_STDOUT_WORLD);
133: PEPErrorView(pep,PEP_ERROR_RELATIVE,PETSC_VIEWER_STDOUT_WORLD);
134: PetscViewerPopFormat(PETSC_VIEWER_STDOUT_WORLD);
135: }
136: MatDestroy(&M);
137: MatDestroy(&C);
138: MatDestroy(&K);
140: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
141: Compute the eigensystem, (k^2*M+k*C+K)x=0 for bigger n
142: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
143:
144: n *= 2;
145: /* K is a tridiagonal */
146: MatCreate(PETSC_COMM_WORLD,&K);
147: MatSetSizes(K,PETSC_DECIDE,PETSC_DECIDE,n,n);
148: MatSetFromOptions(K);
149: MatSetUp(K);
151: MatGetOwnershipRange(K,&Istart,&Iend);
152: for (i=Istart;i<Iend;i++) {
153: if (i>0) {
154: MatSetValue(K,i,i-1,-kappa,INSERT_VALUES);
155: }
156: MatSetValue(K,i,i,kappa*3.0,INSERT_VALUES);
157: if (i<n-1) {
158: MatSetValue(K,i,i+1,-kappa,INSERT_VALUES);
159: }
160: }
162: MatAssemblyBegin(K,MAT_FINAL_ASSEMBLY);
163: MatAssemblyEnd(K,MAT_FINAL_ASSEMBLY);
165: /* C is a tridiagonal */
166: MatCreate(PETSC_COMM_WORLD,&C);
167: MatSetSizes(C,PETSC_DECIDE,PETSC_DECIDE,n,n);
168: MatSetFromOptions(C);
169: MatSetUp(C);
171: MatGetOwnershipRange(C,&Istart,&Iend);
172: for (i=Istart;i<Iend;i++) {
173: if (i>0) {
174: MatSetValue(C,i,i-1,-tau,INSERT_VALUES);
175: }
176: MatSetValue(C,i,i,tau*3.0,INSERT_VALUES);
177: if (i<n-1) {
178: MatSetValue(C,i,i+1,-tau,INSERT_VALUES);
179: }
180: }
182: MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);
183: MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);
185: /* M is a diagonal matrix */
186: MatCreate(PETSC_COMM_WORLD,&M);
187: MatSetSizes(M,PETSC_DECIDE,PETSC_DECIDE,n,n);
188: MatSetFromOptions(M);
189: MatSetUp(M);
190: MatGetOwnershipRange(M,&Istart,&Iend);
191: for (i=Istart;i<Iend;i++) {
192: MatSetValue(M,i,i,mu,INSERT_VALUES);
193: }
194: MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);
195: MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);
197: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
198: Solve again, calling PEPReset() since matrix size has changed
199: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
200: PEPReset(pep); /* if this is omitted, it will be called in PEPSetOperators() */
201: A[0] = K; A[1] = C; A[2] = M;
202: PEPSetOperators(pep,3,A);
203: PEPSolve(pep);
205: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
206: Display solution and clean up
207: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
208: if (terse) {
209: PEPErrorView(pep,PEP_ERROR_BACKWARD,NULL);
210: } else {
211: PetscViewerPushFormat(PETSC_VIEWER_STDOUT_WORLD,PETSC_VIEWER_ASCII_INFO_DETAIL);
212: PEPReasonView(pep,PETSC_VIEWER_STDOUT_WORLD);
213: PEPErrorView(pep,PEP_ERROR_RELATIVE,PETSC_VIEWER_STDOUT_WORLD);
214: PetscViewerPopFormat(PETSC_VIEWER_STDOUT_WORLD);
215: }
216: PEPDestroy(&pep);
217: MatDestroy(&M);
218: MatDestroy(&C);
219: MatDestroy(&K);
220: SlepcFinalize();
221: return ierr;
222: }
224: /*TEST
226: test:
227: suffix: 1
228: args: -pep_type {{toar qarnoldi linear}} -pep_nev 4 -terse
229: requires: !single
231: test:
232: suffix: 2
233: args: -pep_type stoar -pep_hermitian -pep_nev 4 -terse
234: requires: !single
236: TEST*/