Actual source code: sleeper.c

slepc-3.11.2 2019-07-30
Report Typos and Errors
  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:    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 sleeper problem is a proportionally damped QEP describing the
 19:    oscillations of a rail track resting on sleepers.
 20: */

 22: static char help[] = "Oscillations of a rail track resting on sleepers.\n\n"
 23:   "The command line options are:\n"
 24:   "  -n <n>, where <n> = dimension of the matrices.\n\n";

 26: #include <slepcpep.h>

 28: int main(int argc,char **argv)
 29: {
 30:   Mat            M,C,K,A[3];      /* problem matrices */
 31:   PEP            pep;             /* polynomial eigenproblem solver context */
 32:   PetscInt       n=10,Istart,Iend,i;
 33:   PetscBool      terse;

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

 38:   PetscOptionsGetInt(NULL,NULL,"-n",&n,NULL);
 39:   PetscPrintf(PETSC_COMM_WORLD,"\nRailtrack resting on sleepers, n=%D\n\n",n);

 41:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
 42:      Compute the matrices that define the eigensystem, (k^2*M+k*C+K)x=0
 43:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

 45:   /* K is a pentadiagonal */
 46:   MatCreate(PETSC_COMM_WORLD,&K);
 47:   MatSetSizes(K,PETSC_DECIDE,PETSC_DECIDE,n,n);
 48:   MatSetFromOptions(K);
 49:   MatSetUp(K);

 51:   MatGetOwnershipRange(K,&Istart,&Iend);
 52:   for (i=Istart;i<Iend;i++) {
 53:     if (i==0) {
 54:       MatSetValue(K,i,n-1,-3.0,INSERT_VALUES);
 55:       MatSetValue(K,i,n-2,1.0,INSERT_VALUES);
 56:     }
 57:     if (i==1) { MatSetValue(K,i,n-1,1.0,INSERT_VALUES); }
 58:     if (i>0) { MatSetValue(K,i,i-1,-3.0,INSERT_VALUES); }
 59:     if (i>1) { MatSetValue(K,i,i-2,1.0,INSERT_VALUES); }
 60:     MatSetValue(K,i,i,5.0,INSERT_VALUES);
 61:     if (i==n-1) {
 62:       MatSetValue(K,i,0,-3.0,INSERT_VALUES);
 63:       MatSetValue(K,i,1,1.0,INSERT_VALUES);
 64:     }
 65:     if (i==n-2) { MatSetValue(K,i,0,1.0,INSERT_VALUES); }
 66:     if (i<n-1) { MatSetValue(K,i,i+1,-3.0,INSERT_VALUES); }
 67:     if (i<n-2) { MatSetValue(K,i,i+2,1.0,INSERT_VALUES); }
 68:   }

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

 73:   /* C is a circulant matrix */
 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,n-1,-4.0,INSERT_VALUES);
 83:       MatSetValue(C,i,n-2,1.0,INSERT_VALUES);
 84:     }
 85:     if (i==1) { MatSetValue(C,i,n-1,1.0,INSERT_VALUES); }
 86:     if (i>0) { MatSetValue(C,i,i-1,-4.0,INSERT_VALUES); }
 87:     if (i>1) { MatSetValue(C,i,i-2,1.0,INSERT_VALUES); }
 88:     MatSetValue(C,i,i,7.0,INSERT_VALUES);
 89:     if (i==n-1) {
 90:       MatSetValue(C,i,0,-4.0,INSERT_VALUES);
 91:       MatSetValue(C,i,1,1.0,INSERT_VALUES);
 92:     }
 93:     if (i==n-2) { MatSetValue(C,i,0,1.0,INSERT_VALUES); }
 94:     if (i<n-1) { MatSetValue(C,i,i+1,-4.0,INSERT_VALUES); }
 95:     if (i<n-2) { MatSetValue(C,i,i+2,1.0,INSERT_VALUES); }
 96:   }

 98:   MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);
 99:   MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);

101:   /* M is the identity matrix */
102:   MatCreate(PETSC_COMM_WORLD,&M);
103:   MatSetSizes(M,PETSC_DECIDE,PETSC_DECIDE,n,n);
104:   MatSetFromOptions(M);
105:   MatSetUp(M);
106:   MatGetOwnershipRange(M,&Istart,&Iend);
107:   for (i=Istart;i<Iend;i++) {
108:     MatSetValue(M,i,i,1.0,INSERT_VALUES);
109:   }
110:   MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);
111:   MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);

113:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
114:                 Create the eigensolver and solve the problem
115:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

117:   PEPCreate(PETSC_COMM_WORLD,&pep);
118:   A[0] = K; A[1] = C; A[2] = M;
119:   PEPSetOperators(pep,3,A);
120:   PEPSetFromOptions(pep);
121:   PEPSolve(pep);

123:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
124:                     Display solution and clean up
125:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

127:   /* show detailed info unless -terse option is given by user */
128:   PetscOptionsHasName(NULL,NULL,"-terse",&terse);
129:   if (terse) {
130:     PEPErrorView(pep,PEP_ERROR_BACKWARD,NULL);
131:   } else {
132:     PetscViewerPushFormat(PETSC_VIEWER_STDOUT_WORLD,PETSC_VIEWER_ASCII_INFO_DETAIL);
133:     PEPReasonView(pep,PETSC_VIEWER_STDOUT_WORLD);
134:     PEPErrorView(pep,PEP_ERROR_BACKWARD,PETSC_VIEWER_STDOUT_WORLD);
135:     PetscViewerPopFormat(PETSC_VIEWER_STDOUT_WORLD);
136:   }
137:   PEPDestroy(&pep);
138:   MatDestroy(&M);
139:   MatDestroy(&C);
140:   MatDestroy(&K);
141:   SlepcFinalize();
142:   return ierr;
143: }

145: /*TEST

147:    testset:
148:       args: -n 100 -pep_nev 4 -pep_ncv 24 -st_type sinvert -terse
149:       output_file: output/sleeper_1.out
150:       test:
151:          suffix: 1
152:          args: -pep_type {{toar linear}} -pep_ncv 20
153:       test:
154:          suffix: 1_qarnoldi
155:          args: -pep_type qarnoldi -pep_qarnoldi_restart 0.4

157:    testset:
158:       args: -n 24 -pep_nev 4 -pep_ncv 9 -pep_target -.62 -terse 
159:       output_file: output/sleeper_2.out
160:       test:
161:          suffix: 2_toar
162:          args: -pep_type toar -pep_toar_restart .3 -st_type sinvert
163:          requires: !single
164:       test:
165:          suffix: 2_jd
166:          args: -pep_type jd -pep_jd_restart .3 -pep_jd_projection orthogonal

168:    test:
169:       suffix: 3
170:       args: -n 275 -pep_type stoar -pep_hermitian -st_type sinvert -pep_nev 2 -pep_target -.89 -terse
171:       requires: !single

173:    test:
174:       suffix: 4
175:       args: -n 270 -pep_type stoar -pep_hermitian -pep_interval -3,-2.51 -st_type sinvert -st_pc_type cholesky -terse
176:       requires: !complex !single

178: TEST*/