Actual source code: spring.c

slepc-3.20.2 2024-03-15
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  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 spring problem is a QEP from the finite element model of a damped
 19:    mass-spring system. This implementation supports only scalar parameters,
 20:    that is all masses, dampers and springs have the same constants.
 21:    Furthermore, this implementation does not consider different constants
 22:    for dampers and springs connecting adjacent masses or masses to the ground.
 23: */

 25: static char help[] = "FEM model of a damped mass-spring system.\n\n"
 26:   "The command line options are:\n"
 27:   "  -n <n> ... dimension of the matrices.\n"
 28:   "  -mu <value> ... mass (default 1).\n"
 29:   "  -tau <value> ... damping constant of the dampers (default 10).\n"
 30:   "  -kappa <value> ... damping constant of the springs (default 5).\n\n";

 32: #include <slepcpep.h>

 34: int main(int argc,char **argv)
 35: {
 36:   Mat            M,C,K,A[3];      /* problem matrices */
 37:   PEP            pep;             /* polynomial eigenproblem solver context */
 38:   PetscInt       n=5,Istart,Iend,i;
 39:   PetscReal      mu=1.0,tau=10.0,kappa=5.0;
 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,"-mu",&mu,NULL));
 47:   PetscCall(PetscOptionsGetReal(NULL,NULL,"-tau",&tau,NULL));
 48:   PetscCall(PetscOptionsGetReal(NULL,NULL,"-kappa",&kappa,NULL));
 49:   PetscCall(PetscPrintf(PETSC_COMM_WORLD,"\nDamped mass-spring system, n=%" PetscInt_FMT " mu=%g tau=%g kappa=%g\n\n",n,(double)mu,(double)tau,(double)kappa));

 51:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
 52:      Compute the matrices that define the eigensystem, (k^2*M+k*C+K)x=0
 53:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

 55:   /* K is a tridiagonal */
 56:   PetscCall(MatCreate(PETSC_COMM_WORLD,&K));
 57:   PetscCall(MatSetSizes(K,PETSC_DECIDE,PETSC_DECIDE,n,n));
 58:   PetscCall(MatSetFromOptions(K));
 59:   PetscCall(MatSetUp(K));

 61:   PetscCall(MatGetOwnershipRange(K,&Istart,&Iend));
 62:   for (i=Istart;i<Iend;i++) {
 63:     if (i>0) PetscCall(MatSetValue(K,i,i-1,-kappa,INSERT_VALUES));
 64:     PetscCall(MatSetValue(K,i,i,kappa*3.0,INSERT_VALUES));
 65:     if (i<n-1) PetscCall(MatSetValue(K,i,i+1,-kappa,INSERT_VALUES));
 66:   }

 68:   PetscCall(MatAssemblyBegin(K,MAT_FINAL_ASSEMBLY));
 69:   PetscCall(MatAssemblyEnd(K,MAT_FINAL_ASSEMBLY));

 71:   /* C is a tridiagonal */
 72:   PetscCall(MatCreate(PETSC_COMM_WORLD,&C));
 73:   PetscCall(MatSetSizes(C,PETSC_DECIDE,PETSC_DECIDE,n,n));
 74:   PetscCall(MatSetFromOptions(C));
 75:   PetscCall(MatSetUp(C));

 77:   PetscCall(MatGetOwnershipRange(C,&Istart,&Iend));
 78:   for (i=Istart;i<Iend;i++) {
 79:     if (i>0) PetscCall(MatSetValue(C,i,i-1,-tau,INSERT_VALUES));
 80:     PetscCall(MatSetValue(C,i,i,tau*3.0,INSERT_VALUES));
 81:     if (i<n-1) PetscCall(MatSetValue(C,i,i+1,-tau,INSERT_VALUES));
 82:   }

 84:   PetscCall(MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY));
 85:   PetscCall(MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY));

 87:   /* M is a diagonal matrix */
 88:   PetscCall(MatCreate(PETSC_COMM_WORLD,&M));
 89:   PetscCall(MatSetSizes(M,PETSC_DECIDE,PETSC_DECIDE,n,n));
 90:   PetscCall(MatSetFromOptions(M));
 91:   PetscCall(MatSetUp(M));
 92:   PetscCall(MatGetOwnershipRange(M,&Istart,&Iend));
 93:   for (i=Istart;i<Iend;i++) PetscCall(MatSetValue(M,i,i,mu,INSERT_VALUES));
 94:   PetscCall(MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY));
 95:   PetscCall(MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY));

 97:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
 98:                 Create the eigensolver and solve the problem
 99:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

101:   PetscCall(PEPCreate(PETSC_COMM_WORLD,&pep));
102:   A[0] = K; A[1] = C; A[2] = M;
103:   PetscCall(PEPSetOperators(pep,3,A));
104:   PetscCall(PEPSetFromOptions(pep));
105:   PetscCall(PEPSolve(pep));

107:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
108:                     Display solution and clean up
109:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

111:   /* show detailed info unless -terse option is given by user */
112:   PetscCall(PetscOptionsHasName(NULL,NULL,"-terse",&terse));
113:   if (terse) PetscCall(PEPErrorView(pep,PEP_ERROR_BACKWARD,NULL));
114:   else {
115:     PetscCall(PetscViewerPushFormat(PETSC_VIEWER_STDOUT_WORLD,PETSC_VIEWER_ASCII_INFO_DETAIL));
116:     PetscCall(PEPConvergedReasonView(pep,PETSC_VIEWER_STDOUT_WORLD));
117:     PetscCall(PEPErrorView(pep,PEP_ERROR_BACKWARD,PETSC_VIEWER_STDOUT_WORLD));
118:     PetscCall(PetscViewerPopFormat(PETSC_VIEWER_STDOUT_WORLD));
119:   }
120:   PetscCall(PEPDestroy(&pep));
121:   PetscCall(MatDestroy(&M));
122:   PetscCall(MatDestroy(&C));
123:   PetscCall(MatDestroy(&K));
124:   PetscCall(SlepcFinalize());
125:   return 0;
126: }

128: /*TEST

130:    testset:
131:       args: -pep_nev 4 -n 24 -pep_ncv 18 -pep_target -.5 -st_type sinvert -pep_scale diagonal -terse
132:       output_file: output/spring_1.out
133:       filter: sed -e "s/[+-]0\.0*i//g"
134:       test:
135:          suffix: 1
136:          args: -pep_type {{toar linear}} -pep_conv_norm
137:       test:
138:          suffix: 1_stoar
139:          args: -pep_type stoar -pep_hermitian -pep_conv_rel
140:       test:
141:          suffix: 1_qarnoldi
142:          args: -pep_type qarnoldi -pep_conv_rel
143:       test:
144:          suffix: 1_cuda
145:          args: -mat_type aijcusparse
146:          requires: cuda

148:    test:
149:       suffix: 2
150:       args: -pep_type jd -pep_jd_minimality_index 1 -pep_nev 4 -n 24 -pep_ncv 18 -pep_target -50 -terse
151:       requires: !single
152:       filter: sed -e "s/[+-]0\.0*i//g"

154:    test:
155:       suffix: 3
156:       args: -n 300 -pep_hermitian -pep_interval -10.1,-9.5 -pep_type stoar -st_type sinvert -st_pc_type cholesky -terse
157:       filter: sed -e "s/52565/52566/" | sed -e "s/90758/90759/"
158:       requires: !single

160:    test:
161:       suffix: 4
162:       args: -n 300 -pep_hyperbolic -pep_interval -9.6,-.527 -pep_type stoar -st_type sinvert -st_pc_type cholesky -terse
163:       requires: !single
164:       timeoutfactor: 2

166:    test:
167:       suffix: 5
168:       args: -n 300 -pep_hyperbolic -pep_interval -.506,-.3 -pep_type stoar -st_type sinvert -st_pc_type cholesky -pep_stoar_nev 11 -terse
169:       requires: !single

171:    test:
172:       suffix: 6
173:       args: -n 24 -pep_ncv 18 -pep_target -.5 -terse -pep_type jd -pep_jd_restart .6 -pep_jd_fix .001
174:       requires: !single

176: TEST*/