Actual source code: ex23.c
slepc-3.10.1 2018-10-23
Report Typos and Errors

      1: /*
      2:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      3:    SLEPc - Scalable Library for Eigenvalue Problem Computations
      4:    Copyright (c) 2002-2018, 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[] = "Computes exp(t*A)*v for a matrix associated with a Markov model.\n\n"
     12:   "The command line options are:\n"
     13:   "  -t <t>, where <t> = time parameter (multiplies the matrix).\n"
     14:   "  -m <m>, where <m> = number of grid subdivisions in each dimension.\n\n"
     15:   "To draw the solution run with -mfn_view_solution draw -draw_pause -1\n\n";

     17: #include <slepcmfn.h>

     19: /*
     20:    User-defined routines
     21: */
     22: PetscErrorCode MatMarkovModel(PetscInt m,Mat A);

     24: int main(int argc,char **argv)
     25: {
     26:   Mat                A;           /* problem matrix */
     27:   MFN                mfn;
     28:   FN                 f;
     29:   PetscReal          tol,norm;
     30:   PetscScalar        t=2.0;
     31:   Vec                v,y;
     32:   PetscInt           N,m=15,ncv,maxit,its;
     33:   PetscErrorCode     ierr;
     34:   MFNConvergedReason reason;

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

     38:   PetscOptionsGetInt(NULL,NULL,"-m",&m,NULL);
     39:   PetscOptionsGetScalar(NULL,NULL,"-t",&t,NULL);
     40:   N = m*(m+1)/2;
     41:   PetscPrintf(PETSC_COMM_WORLD,"\nMarkov y=exp(t*A)*e_1, N=%D (m=%D)\n\n",N,m);

     43:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     44:             Compute the transition probability matrix, A
     45:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

     47:   MatCreate(PETSC_COMM_WORLD,&A);
     48:   MatSetSizes(A,PETSC_DECIDE,PETSC_DECIDE,N,N);
     49:   MatSetFromOptions(A);
     50:   MatSetUp(A);
     51:   MatMarkovModel(m,A);

     53:   /* set v = e_1 */
     54:   MatCreateVecs(A,NULL,&y);
     55:   MatCreateVecs(A,NULL,&v);
     56:   VecSetValue(v,0,1.0,INSERT_VALUES);
     57:   VecAssemblyBegin(v);
     58:   VecAssemblyEnd(v);

     60:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     61:                 Create the solver and set various options
     62:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
     63:   /*
     64:      Create matrix function solver context
     65:   */
     66:   MFNCreate(PETSC_COMM_WORLD,&mfn);

     68:   /*
     69:      Set operator matrix, the function to compute, and other options
     70:   */
     71:   MFNSetOperator(mfn,A);
     72:   MFNGetFN(mfn,&f);
     73:   FNSetType(f,FNEXP);
     74:   FNSetScale(f,t,1.0);
     75:   MFNSetTolerances(mfn,1e-07,PETSC_DEFAULT);

     77:   /*
     78:      Set solver parameters at runtime
     79:   */
     80:   MFNSetFromOptions(mfn);

     82:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     83:                       Solve the problem, y=exp(t*A)*v
     84:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

     86:   MFNSolve(mfn,v,y);
     87:   MFNGetConvergedReason(mfn,&reason);
     88:   if (reason<0) SETERRQ(PETSC_COMM_WORLD,1,"Solver did not converge");
     89:   VecNorm(y,NORM_2,&norm);

     91:   /*
     92:      Optional: Get some information from the solver and display it
     93:   */
     94:   MFNGetIterationNumber(mfn,&its);
     95:   PetscPrintf(PETSC_COMM_WORLD," Number of iterations of the method: %D\n",its);
     96:   MFNGetDimensions(mfn,&ncv);
     97:   PetscPrintf(PETSC_COMM_WORLD," Subspace dimension: %D\n",ncv);
     98:   MFNGetTolerances(mfn,&tol,&maxit);
     99:   PetscPrintf(PETSC_COMM_WORLD," Stopping condition: tol=%.4g, maxit=%D\n",(double)tol,maxit);

    101:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    102:                     Display solution and clean up
    103:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
    104:   PetscPrintf(PETSC_COMM_WORLD," Computed vector at time t=%.4g has norm %g\n\n",(double)PetscRealPart(t),(double)norm);

    106:   /*
    107:      Free work space
    108:   */
    109:   MFNDestroy(&mfn);
    110:   MatDestroy(&A);
    111:   VecDestroy(&v);
    112:   VecDestroy(&y);
    113:   SlepcFinalize();
    114:   return ierr;
    115: }

    117: /*
    118:     Matrix generator for a Markov model of a random walk on a triangular grid.
    119:     See ex5.c for additional details.
    120: */
    121: PetscErrorCode MatMarkovModel(PetscInt m,Mat A)
    122: {
    123:   const PetscReal cst = 0.5/(PetscReal)(m-1);
    124:   PetscReal       pd,pu;
    125:   PetscInt        Istart,Iend,i,j,jmax,ix=0;
    126:   PetscErrorCode  ierr;

    129:   MatGetOwnershipRange(A,&Istart,&Iend);
    130:   for (i=1;i<=m;i++) {
    131:     jmax = m-i+1;
    132:     for (j=1;j<=jmax;j++) {
    133:       ix = ix + 1;
    134:       if (ix-1<Istart || ix>Iend) continue;  /* compute only owned rows */
    135:       if (j!=jmax) {
    136:         pd = cst*(PetscReal)(i+j-1);
    137:         /* north */
    138:         if (i==1) {
    139:           MatSetValue(A,ix-1,ix,2*pd,INSERT_VALUES);
    140:         } else {
    141:           MatSetValue(A,ix-1,ix,pd,INSERT_VALUES);
    142:         }
    143:         /* east */
    144:         if (j==1) {
    145:           MatSetValue(A,ix-1,ix+jmax-1,2*pd,INSERT_VALUES);
    146:         } else {
    147:           MatSetValue(A,ix-1,ix+jmax-1,pd,INSERT_VALUES);
    148:         }
    149:       }
    150:       /* south */
    151:       pu = 0.5 - cst*(PetscReal)(i+j-3);
    152:       if (j>1) {
    153:         MatSetValue(A,ix-1,ix-2,pu,INSERT_VALUES);
    154:       }
    155:       /* west */
    156:       if (i>1) {
    157:         MatSetValue(A,ix-1,ix-jmax-2,pu,INSERT_VALUES);
    158:       }
    159:     }
    160:   }
    161:   MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
    162:   MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
    163:   return(0);
    164: }

    166: /*TEST

    168:    test:
    169:       suffix: 1
    170:       args: -mfn_ncv 6

    172: TEST*/