Actual source code: loaded_string.c
slepc-3.21.0 2024-03-30
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 loaded_string problem is a rational eigenvalue problem for the
19: finite element model of a loaded vibrating string.
20: */
22: static char help[] = "Finite element model of a loaded vibrating string.\n\n"
23: "The command line options are:\n"
24: " -n <n>, dimension of the matrices.\n"
25: " -kappa <kappa>, stiffness of elastic spring.\n"
26: " -mass <m>, mass of the attached load.\n\n";
28: #include <slepcnep.h>
30: #define NMAT 3
32: int main(int argc,char **argv)
33: {
34: Mat A[NMAT]; /* problem matrices */
35: FN f[NMAT]; /* functions to define the nonlinear operator */
36: NEP nep; /* nonlinear eigensolver context */
37: PetscInt n=100,Istart,Iend,i;
38: PetscReal kappa=1.0,m=1.0;
39: PetscScalar sigma,numer[2],denom[2];
40: PetscBool terse;
42: PetscFunctionBeginUser;
43: PetscCall(SlepcInitialize(&argc,&argv,(char*)0,help));
45: PetscCall(PetscOptionsGetInt(NULL,NULL,"-n",&n,NULL));
46: PetscCall(PetscOptionsGetReal(NULL,NULL,"-kappa",&kappa,NULL));
47: PetscCall(PetscOptionsGetReal(NULL,NULL,"-mass",&m,NULL));
48: sigma = kappa/m;
49: PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Loaded vibrating string, n=%" PetscInt_FMT " kappa=%g m=%g\n\n",n,(double)kappa,(double)m));
51: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
52: Build the problem matrices
53: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
55: /* initialize matrices */
56: for (i=0;i<NMAT;i++) {
57: PetscCall(MatCreate(PETSC_COMM_WORLD,&A[i]));
58: PetscCall(MatSetSizes(A[i],PETSC_DECIDE,PETSC_DECIDE,n,n));
59: PetscCall(MatSetFromOptions(A[i]));
60: }
62: /* A0 */
63: PetscCall(MatGetOwnershipRange(A[0],&Istart,&Iend));
64: for (i=Istart;i<Iend;i++) {
65: PetscCall(MatSetValue(A[0],i,i,(i==n-1)?1.0*n:2.0*n,INSERT_VALUES));
66: if (i>0) PetscCall(MatSetValue(A[0],i,i-1,-1.0*n,INSERT_VALUES));
67: if (i<n-1) PetscCall(MatSetValue(A[0],i,i+1,-1.0*n,INSERT_VALUES));
68: }
70: /* A1 */
71: PetscCall(MatGetOwnershipRange(A[1],&Istart,&Iend));
72: for (i=Istart;i<Iend;i++) {
73: PetscCall(MatSetValue(A[1],i,i,(i==n-1)?2.0/(6.0*n):4.0/(6.0*n),INSERT_VALUES));
74: if (i>0) PetscCall(MatSetValue(A[1],i,i-1,1.0/(6.0*n),INSERT_VALUES));
75: if (i<n-1) PetscCall(MatSetValue(A[1],i,i+1,1.0/(6.0*n),INSERT_VALUES));
76: }
78: /* A2 */
79: PetscCall(MatGetOwnershipRange(A[2],&Istart,&Iend));
80: if (Istart<=n-1 && n-1<Iend) PetscCall(MatSetValue(A[2],n-1,n-1,kappa,INSERT_VALUES));
82: /* assemble matrices */
83: for (i=0;i<NMAT;i++) PetscCall(MatAssemblyBegin(A[i],MAT_FINAL_ASSEMBLY));
84: for (i=0;i<NMAT;i++) PetscCall(MatAssemblyEnd(A[i],MAT_FINAL_ASSEMBLY));
86: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
87: Create the problem functions
88: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
90: /* f1=1 */
91: PetscCall(FNCreate(PETSC_COMM_WORLD,&f[0]));
92: PetscCall(FNSetType(f[0],FNRATIONAL));
93: numer[0] = 1.0;
94: PetscCall(FNRationalSetNumerator(f[0],1,numer));
96: /* f2=-lambda */
97: PetscCall(FNCreate(PETSC_COMM_WORLD,&f[1]));
98: PetscCall(FNSetType(f[1],FNRATIONAL));
99: numer[0] = -1.0; numer[1] = 0.0;
100: PetscCall(FNRationalSetNumerator(f[1],2,numer));
102: /* f3=lambda/(lambda-sigma) */
103: PetscCall(FNCreate(PETSC_COMM_WORLD,&f[2]));
104: PetscCall(FNSetType(f[2],FNRATIONAL));
105: numer[0] = 1.0; numer[1] = 0.0;
106: denom[0] = 1.0; denom[1] = -sigma;
107: PetscCall(FNRationalSetNumerator(f[2],2,numer));
108: PetscCall(FNRationalSetDenominator(f[2],2,denom));
110: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
111: Create the eigensolver and solve the problem
112: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
114: PetscCall(NEPCreate(PETSC_COMM_WORLD,&nep));
115: PetscCall(NEPSetSplitOperator(nep,3,A,f,SUBSET_NONZERO_PATTERN));
116: PetscCall(NEPSetProblemType(nep,NEP_RATIONAL));
117: PetscCall(NEPSetFromOptions(nep));
118: PetscCall(NEPSolve(nep));
120: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
121: Display solution and clean up
122: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
124: /* show detailed info unless -terse option is given by user */
125: PetscCall(PetscOptionsHasName(NULL,NULL,"-terse",&terse));
126: if (terse) PetscCall(NEPErrorView(nep,NEP_ERROR_RELATIVE,NULL));
127: else {
128: PetscCall(PetscViewerPushFormat(PETSC_VIEWER_STDOUT_WORLD,PETSC_VIEWER_ASCII_INFO_DETAIL));
129: PetscCall(NEPConvergedReasonView(nep,PETSC_VIEWER_STDOUT_WORLD));
130: PetscCall(NEPErrorView(nep,NEP_ERROR_RELATIVE,PETSC_VIEWER_STDOUT_WORLD));
131: PetscCall(PetscViewerPopFormat(PETSC_VIEWER_STDOUT_WORLD));
132: }
133: PetscCall(NEPDestroy(&nep));
134: for (i=0;i<NMAT;i++) {
135: PetscCall(MatDestroy(&A[i]));
136: PetscCall(FNDestroy(&f[i]));
137: }
138: PetscCall(SlepcFinalize());
139: return 0;
140: }
142: /*TEST
144: test:
145: suffix: 1
146: args: -nep_type rii -nep_target 4 -terse
147: requires: !single
148: filter: sed -e "s/[+-]0\.0*i//g"
150: testset:
151: args: -nep_type interpol -rg_type interval -rg_interval_endpoints 5,700,-.1,.1 -nep_nev 7 -nep_target 5 -nep_interpol_interpolation_degree 12 -nep_refine simple -terse
152: requires: !single
153: output_file: output/loaded_string_2.out
154: test:
155: suffix: 2
156: args: -nep_refine_scheme {{schur explicit}}
157: test:
158: suffix: 2_mbe
159: args: -nep_refine_scheme mbe -nep_refine_ksp_type preonly -nep_refine_pc_type lu
161: testset:
162: nsize: 2
163: args: -nep_type interpol -rg_type interval -rg_interval_endpoints 5,700,-.1,.1 -nep_nev 7 -nep_target 5 -nep_interpol_interpolation_degree 12 -nep_refine simple -nep_refine_partitions 2 -nep_interpol_st_ksp_type bcgs -nep_interpol_st_pc_type bjacobi -terse
164: requires: !single
165: output_file: output/loaded_string_2.out
166: timeoutfactor: 2
167: test:
168: suffix: 3_explicit
169: args: -nep_refine_scheme explicit
170: test:
171: suffix: 3_mbe
172: args: -nep_refine_scheme mbe -nep_refine_ksp_type preonly -nep_refine_pc_type cholesky
174: test:
175: suffix: 4
176: nsize: 4
177: args: -nep_type interpol -rg_type interval -rg_interval_endpoints 5,700,-.1,.1 -nep_nev 7 -nep_target 5 -nep_interpol_interpolation_degree 10 -nep_refine simple -nep_refine_partitions 2 -nep_refine_scheme explicit -nep_interpol_st_ksp_type bcgs -nep_interpol_st_pc_type bjacobi -terse -log_exclude nep,pep,fn
178: requires: !single
179: output_file: output/loaded_string_2.out
180: timeoutfactor: 4
182: test:
183: suffix: 5
184: args: -nep_type nleigs -rg_type interval -rg_interval_endpoints 4,700,-.1,.1 -nep_nev 8 -nep_target 5 -terse
185: filter: sed -e "s/[+-]0\.0*i//g"
186: requires: !single
188: test:
189: suffix: 6
190: args: -nep_type nleigs -rg_type interval -rg_interval_endpoints 100,700 -nep_nev 5 -nep_tol 1e-9 -nep_target 140 -nep_nleigs_interpolation_degree 15 -nep_general -terse
191: requires: !complex !single
193: test:
194: suffix: 6_complex
195: args: -nep_type nleigs -rg_type interval -rg_interval_endpoints 100,700,-.1,.1 -nep_nev 5 -nep_tol 1e-9 -nep_target 140 -nep_nleigs_interpolation_degree 15 -nep_general -terse
196: filter: sed -e "s/[+-]0\.0*i//g"
197: requires: complex !single
198: output_file: output/loaded_string_6.out
200: test:
201: suffix: 7
202: args: -nep_type interpol -rg_type interval -rg_interval_endpoints 5,700 -nep_nev 5 -nep_target 100 -nep_interpol_interpolation_degree 20 -nep_ncv 20 -n 20 -nep_refine simple -nep_refine_its 1 -terse
203: requires: !complex double
205: test:
206: suffix: 7_complex
207: args: -nep_type interpol -rg_type interval -rg_interval_endpoints 5,700,-.1,.1 -nep_nev 5 -nep_target 100 -nep_interpol_interpolation_degree 20 -nep_ncv 20 -n 20 -nep_refine simple -nep_refine_its 1 -terse
208: requires: complex double
209: output_file: output/loaded_string_7.out
211: testset:
212: args: -nep_target 10 -nep_nev 3 -nep_tol 5e-10 -terse
213: requires: !single
214: output_file: output/loaded_string_8.out
215: filter: sed -e "s/[+-]0\.0*i//g"
216: test:
217: suffix: 8
218: args: -nep_type {{rii slp narnoldi}}
219: test:
220: suffix: 8_rii_thres
221: args: -nep_type rii -nep_rii_deflation_threshold 5e-10
222: test:
223: suffix: 8_slp_thres
224: args: -nep_type slp -nep_slp_deflation_threshold 5e-10
226: test:
227: suffix: 8_slp_two_thres
228: args: -nep_type slp -nep_slp_deflation_threshold 5e-10 -nep_two_sided
230: test:
231: suffix: 9
232: args: -nep_type ciss -rg_type ellipse -rg_ellipse_center 500 -rg_ellipse_radius 500 -rg_ellipse_vscale .1 -nep_ciss_moments 4 -nep_ciss_blocksize 5 -terse
233: requires: complex double
235: TEST*/