Actual source code: ex38.c

      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: */

     11: static char help[] = "Spectrum slicing on quadratic symmetric eigenproblem.\n\n"
     12:   "The command line options are:\n"
     13:   "  -n <n> ... dimension of the matrices.\n\n";

     15: #include <slepcpep.h>

     17: int main(int argc,char **argv)
     18: {
     19:   Mat            M,C,K,A[3]; /* problem matrices */
     20:   PEP            pep;        /* polynomial eigenproblem solver context */
     21:   ST             st;         /* spectral transformation context */
     22:   KSP            ksp;
     23:   PC             pc;
     24:   PEPType        type;
     25:   PetscBool      show=PETSC_FALSE,terse;
     26:   PetscInt       n=100,Istart,Iend,nev,i,*inertias,ns;
     27:   PetscReal      mu=1,tau=10,kappa=5,inta,intb,*shifts;

     29:   PetscFunctionBeginUser;
     30:   PetscCall(SlepcInitialize(&argc,&argv,NULL,help));

     32:   PetscCall(PetscOptionsGetInt(NULL,NULL,"-n",&n,NULL));
     33:   PetscCall(PetscOptionsGetBool(NULL,NULL,"-show_inertias",&show,NULL));
     34:   PetscCall(PetscOptionsHasName(NULL,NULL,"-terse",&terse));
     35:   PetscCall(PetscPrintf(PETSC_COMM_WORLD,"\nSpectrum slicing on PEP, n=%" PetscInt_FMT "\n\n",n));

     37:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     38:      Compute the matrices that define the eigensystem, (k^2*M+k*C+K)x=0
     39:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

     41:   /* K is a tridiagonal */
     42:   PetscCall(MatCreate(PETSC_COMM_WORLD,&K));
     43:   PetscCall(MatSetSizes(K,PETSC_DECIDE,PETSC_DECIDE,n,n));
     44:   PetscCall(MatSetFromOptions(K));

     46:   PetscCall(MatGetOwnershipRange(K,&Istart,&Iend));
     47:   for (i=Istart;i<Iend;i++) {
     48:     if (i>0) PetscCall(MatSetValue(K,i,i-1,-kappa,INSERT_VALUES));
     49:     PetscCall(MatSetValue(K,i,i,kappa*3.0,INSERT_VALUES));
     50:     if (i<n-1) PetscCall(MatSetValue(K,i,i+1,-kappa,INSERT_VALUES));
     51:   }

     53:   PetscCall(MatAssemblyBegin(K,MAT_FINAL_ASSEMBLY));
     54:   PetscCall(MatAssemblyEnd(K,MAT_FINAL_ASSEMBLY));

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

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

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

     71:   /* M is a diagonal matrix */
     72:   PetscCall(MatCreate(PETSC_COMM_WORLD,&M));
     73:   PetscCall(MatSetSizes(M,PETSC_DECIDE,PETSC_DECIDE,n,n));
     74:   PetscCall(MatSetFromOptions(M));
     75:   PetscCall(MatGetOwnershipRange(M,&Istart,&Iend));
     76:   for (i=Istart;i<Iend;i++) PetscCall(MatSetValue(M,i,i,mu,INSERT_VALUES));
     77:   PetscCall(MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY));
     78:   PetscCall(MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY));

     80:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     81:                 Create the eigensolver and solve the problem
     82:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

     84:   /*
     85:      Create eigensolver context
     86:   */
     87:   PetscCall(PEPCreate(PETSC_COMM_WORLD,&pep));

     89:   /*
     90:      Set operators and set problem type
     91:   */
     92:   A[0] = K; A[1] = C; A[2] = M;
     93:   PetscCall(PEPSetOperators(pep,3,A));
     94:   PetscCall(PEPSetProblemType(pep,PEP_HYPERBOLIC));

     96:   /*
     97:      Set interval for spectrum slicing
     98:   */
     99:   inta = -11.3;
    100:   intb = -9.5;
    101:   PetscCall(PEPSetInterval(pep,inta,intb));
    102:   PetscCall(PEPSetWhichEigenpairs(pep,PEP_ALL));

    104:   /*
    105:      Spectrum slicing requires STOAR
    106:   */
    107:   PetscCall(PEPSetType(pep,PEPSTOAR));

    109:   /*
    110:      Set shift-and-invert with Cholesky; select MUMPS if available
    111:   */
    112:   PetscCall(PEPGetST(pep,&st));
    113:   PetscCall(STSetType(st,STSINVERT));

    115:   PetscCall(STGetKSP(st,&ksp));
    116:   PetscCall(KSPSetType(ksp,KSPPREONLY));
    117:   PetscCall(KSPGetPC(ksp,&pc));
    118:   PetscCall(PCSetType(pc,PCCHOLESKY));

    120:   /*
    121:      Use MUMPS if available.
    122:      Note that in complex scalars we cannot use MUMPS for spectrum slicing,
    123:      because MatGetInertia() is not available in that case.
    124:   */
    125: #if defined(PETSC_HAVE_MUMPS) && !defined(PETSC_USE_COMPLEX)
    126:   PetscCall(PEPSTOARSetDetectZeros(pep,PETSC_TRUE));  /* enforce zero detection */
    127:   PetscCall(PCFactorSetMatSolverType(pc,MATSOLVERMUMPS));
    128:   /*
    129:      Add several MUMPS options (see ex43.c for a better way of setting them in program):
    130:      '-st_mat_mumps_icntl_13 1': turn off ScaLAPACK for matrix inertia
    131:      '-st_mat_mumps_icntl_24 1': detect null pivots in factorization (for the case that a shift is equal to an eigenvalue)
    132:      '-st_mat_mumps_cntl_3 <tol>': a tolerance used for null pivot detection (must be larger than machine epsilon)

    134:      Note: depending on the interval, it may be necessary also to increase the workspace:
    135:      '-st_mat_mumps_icntl_14 <percentage>': increase workspace with a percentage (50, 100 or more)
    136:   */
    137:   PetscCall(PetscOptionsInsertString(NULL,"-st_mat_mumps_icntl_13 1 -st_mat_mumps_icntl_24 1 -st_mat_mumps_cntl_3 1e-12"));
    138: #endif

    140:   /*
    141:      Set solver parameters at runtime
    142:   */
    143:   PetscCall(PEPSetFromOptions(pep));

    145:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    146:                       Solve the eigensystem
    147:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
    148:   PetscCall(PEPSetUp(pep));
    149:   if (show) {
    150:     PetscCall(PEPSTOARGetInertias(pep,&ns,&shifts,&inertias));
    151:     PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Subintervals (after setup):\n"));
    152:     for (i=0;i<ns;i++) PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Shift %g  Inertia %" PetscInt_FMT " \n",(double)shifts[i],inertias[i]));
    153:     PetscCall(PetscPrintf(PETSC_COMM_WORLD,"\n"));
    154:     PetscCall(PetscFree(shifts));
    155:     PetscCall(PetscFree(inertias));
    156:   }
    157:   PetscCall(PEPSolve(pep));
    158:   if (show && !terse) {
    159:     PetscCall(PEPSTOARGetInertias(pep,&ns,&shifts,&inertias));
    160:     PetscCall(PetscPrintf(PETSC_COMM_WORLD,"All shifts (after solve):\n"));
    161:     for (i=0;i<ns;i++) PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Shift %g  Inertia %" PetscInt_FMT " \n",(double)shifts[i],inertias[i]));
    162:     PetscCall(PetscPrintf(PETSC_COMM_WORLD,"\n"));
    163:     PetscCall(PetscFree(shifts));
    164:     PetscCall(PetscFree(inertias));
    165:   }

    167:   /*
    168:      Show eigenvalues in interval and print solution
    169:   */
    170:   PetscCall(PEPGetType(pep,&type));
    171:   PetscCall(PetscPrintf(PETSC_COMM_WORLD," Solution method: %s\n\n",type));
    172:   PetscCall(PEPGetDimensions(pep,&nev,NULL,NULL));
    173:   PetscCall(PEPGetInterval(pep,&inta,&intb));
    174:   PetscCall(PetscPrintf(PETSC_COMM_WORLD," %" PetscInt_FMT " eigenvalues found in [%g, %g]\n",nev,(double)inta,(double)intb));

    176:   /*
    177:      Show detailed info unless -terse option is given by user
    178:    */
    179:   if (terse) PetscCall(PEPErrorView(pep,PEP_ERROR_BACKWARD,NULL));
    180:   else {
    181:     PetscCall(PetscViewerPushFormat(PETSC_VIEWER_STDOUT_WORLD,PETSC_VIEWER_ASCII_INFO_DETAIL));
    182:     PetscCall(PEPConvergedReasonView(pep,PETSC_VIEWER_STDOUT_WORLD));
    183:     PetscCall(PEPErrorView(pep,PEP_ERROR_BACKWARD,PETSC_VIEWER_STDOUT_WORLD));
    184:     PetscCall(PetscViewerPopFormat(PETSC_VIEWER_STDOUT_WORLD));
    185:   }

    187:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    188:                     Clean up
    189:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
    190:   PetscCall(PEPDestroy(&pep));
    191:   PetscCall(MatDestroy(&M));
    192:   PetscCall(MatDestroy(&C));
    193:   PetscCall(MatDestroy(&K));
    194:   PetscCall(SlepcFinalize());
    195:   return 0;
    196: }

    198: /*TEST

    200:    testset:
    201:       requires: !single
    202:       args: -show_inertias -terse
    203:       output_file: output/ex38_1.out
    204:       test:
    205:          suffix: 1
    206:          requires: !complex
    207:       test:
    208:          suffix: 1_complex
    209:          requires: complex !mumps

    211:    test:
    212:       suffix: 2
    213:       args: -pep_interval 0,2

    215: TEST*/