Date: 2021-09-20T09:44:07+00:00

Actual source code: butterfly.c
slepc-3.15.2 2021-09-20
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      1: /*
      2:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      3:    SLEPc - Scalable Library for Eigenvalue Problem Computations
      4:    Copyright (c) 2002-2021, 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 butterfly problem is a quartic PEP with T-even structure.
     19: */

     21: static char help[] = "Quartic polynomial eigenproblem with T-even structure.\n\n"
     22:   "The command line options are:\n"
     23:   "  -m <m>, grid size, the dimension of the matrices is n=m*m.\n"
     24:   "  -c <array>, problem parameters, must be 10 comma-separated real values.\n\n";

     26: #include <slepcpep.h>

     28: #define NMAT 5

     30: int main(int argc,char **argv)
     31: {
     32:   Mat            A[NMAT];         /* problem matrices */
     33:   PEP            pep;             /* polynomial eigenproblem solver context */
     34:   PetscInt       n,m=8,k,II,Istart,Iend,i,j;
     35:   PetscReal      c[10] = { 0.6, 1.3, 1.3, 0.1, 0.1, 1.2, 1.0, 1.0, 1.2, 1.0 };
     36:   PetscBool      flg;
     37:   PetscBool      terse;

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

     42:   PetscOptionsGetInt(NULL,NULL,"-m",&m,NULL);
     43:   n = m*m;
     44:   k = 10;
     45:   PetscOptionsGetRealArray(NULL,NULL,"-c",c,&k,&flg);
     46:   if (flg && k!=10) SETERRQ1(PETSC_COMM_WORLD,1,"The number of parameters -c should be 10, you provided %D",k);
     47:   PetscPrintf(PETSC_COMM_WORLD,"\nButterfly problem, n=%D (m=%D)\n\n",n,m);

     49:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     50:                      Compute the polynomial matrices
     51:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

     53:   /* initialize matrices */
     54:   for (i=0;i<NMAT;i++) {
     55:     MatCreate(PETSC_COMM_WORLD,&A[i]);
     56:     MatSetSizes(A[i],PETSC_DECIDE,PETSC_DECIDE,n,n);
     57:     MatSetFromOptions(A[i]);
     58:     MatSetUp(A[i]);
     59:   }
     60:   MatGetOwnershipRange(A[0],&Istart,&Iend);

     62:   /* A0 */
     63:   for (II=Istart;II<Iend;II++) {
     64:     i = II/m; j = II-i*m;
     65:     MatSetValue(A[0],II,II,4.0*c[0]/6.0+4.0*c[1]/6.0,INSERT_VALUES);
     66:     if (j>0) { MatSetValue(A[0],II,II-1,c[0]/6.0,INSERT_VALUES); }
     67:     if (j<m-1) { MatSetValue(A[0],II,II+1,c[0]/6.0,INSERT_VALUES); }
     68:     if (i>0) { MatSetValue(A[0],II,II-m,c[1]/6.0,INSERT_VALUES); }
     69:     if (i<m-1) { MatSetValue(A[0],II,II+m,c[1]/6.0,INSERT_VALUES); }
     70:   }

     72:   /* A1 */
     73:   for (II=Istart;II<Iend;II++) {
     74:     i = II/m; j = II-i*m;
     75:     if (j>0) { MatSetValue(A[1],II,II-1,c[2],INSERT_VALUES); }
     76:     if (j<m-1) { MatSetValue(A[1],II,II+1,-c[2],INSERT_VALUES); }
     77:     if (i>0) { MatSetValue(A[1],II,II-m,c[3],INSERT_VALUES); }
     78:     if (i<m-1) { MatSetValue(A[1],II,II+m,-c[3],INSERT_VALUES); }
     79:   }

     81:   /* A2 */
     82:   for (II=Istart;II<Iend;II++) {
     83:     i = II/m; j = II-i*m;
     84:     MatSetValue(A[2],II,II,-2.0*c[4]-2.0*c[5],INSERT_VALUES);
     85:     if (j>0) { MatSetValue(A[2],II,II-1,c[4],INSERT_VALUES); }
     86:     if (j<m-1) { MatSetValue(A[2],II,II+1,c[4],INSERT_VALUES); }
     87:     if (i>0) { MatSetValue(A[2],II,II-m,c[5],INSERT_VALUES); }
     88:     if (i<m-1) { MatSetValue(A[2],II,II+m,c[5],INSERT_VALUES); }
     89:   }

     91:   /* A3 */
     92:   for (II=Istart;II<Iend;II++) {
     93:     i = II/m; j = II-i*m;
     94:     if (j>0) { MatSetValue(A[3],II,II-1,c[6],INSERT_VALUES); }
     95:     if (j<m-1) { MatSetValue(A[3],II,II+1,-c[6],INSERT_VALUES); }
     96:     if (i>0) { MatSetValue(A[3],II,II-m,c[7],INSERT_VALUES); }
     97:     if (i<m-1) { MatSetValue(A[3],II,II+m,-c[7],INSERT_VALUES); }
     98:   }

    100:   /* A4 */
    101:   for (II=Istart;II<Iend;II++) {
    102:     i = II/m; j = II-i*m;
    103:     MatSetValue(A[4],II,II,2.0*c[8]+2.0*c[9],INSERT_VALUES);
    104:     if (j>0) { MatSetValue(A[4],II,II-1,-c[8],INSERT_VALUES); }
    105:     if (j<m-1) { MatSetValue(A[4],II,II+1,-c[8],INSERT_VALUES); }
    106:     if (i>0) { MatSetValue(A[4],II,II-m,-c[9],INSERT_VALUES); }
    107:     if (i<m-1) { MatSetValue(A[4],II,II+m,-c[9],INSERT_VALUES); }
    108:   }

    110:   /* assemble matrices */
    111:   for (i=0;i<NMAT;i++) {
    112:     MatAssemblyBegin(A[i],MAT_FINAL_ASSEMBLY);
    113:   }
    114:   for (i=0;i<NMAT;i++) {
    115:     MatAssemblyEnd(A[i],MAT_FINAL_ASSEMBLY);
    116:   }

    118:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    119:                 Create the eigensolver and solve the problem
    120:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

    122:   PEPCreate(PETSC_COMM_WORLD,&pep);
    123:   PEPSetOperators(pep,NMAT,A);
    124:   PEPSetFromOptions(pep);
    125:   PEPSolve(pep);

    127:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    128:                     Display solution and clean up
    129:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

    131:   /* show detailed info unless -terse option is given by user */
    132:   PetscOptionsHasName(NULL,NULL,"-terse",&terse);
    133:   if (terse) {
    134:     PEPErrorView(pep,PEP_ERROR_BACKWARD,NULL);
    135:   } else {
    136:     PetscViewerPushFormat(PETSC_VIEWER_STDOUT_WORLD,PETSC_VIEWER_ASCII_INFO_DETAIL);
    137:     PEPConvergedReasonView(pep,PETSC_VIEWER_STDOUT_WORLD);
    138:     PEPErrorView(pep,PEP_ERROR_BACKWARD,PETSC_VIEWER_STDOUT_WORLD);
    139:     PetscViewerPopFormat(PETSC_VIEWER_STDOUT_WORLD);
    140:   }
    141:   PEPDestroy(&pep);
    142:   for (i=0;i<NMAT;i++) {
    143:     MatDestroy(&A[i]);
    144:   }
    145:   SlepcFinalize();
    146:   return ierr;
    147: }

    149: /*TEST

    151:    testset:
    152:       args: -pep_nev 4 -st_type sinvert -pep_target 0.01 -terse
    153:       output_file: output/butterfly_1.out
    154:       test:
    155:          suffix: 1_toar
    156:          args: -pep_type toar -pep_toar_restart 0.3
    157:       test:
    158:          suffix: 1_linear
    159:          args: -pep_type linear

    161:    test:
    162:       suffix: 2
    163:       args: -pep_type {{toar linear}} -pep_nev 4 -terse
    164:       requires: double

    166: TEST*/