Date: 2017-05-17T08:27:37+00:00

Actual source code: ex23.c
slepc-3.7.4 2017-05-17
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      1: /*
      2:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      3:    SLEPc - Scalable Library for Eigenvalue Problem Computations
      4:    Copyright (c) 2002-2016, Universitat Politecnica de Valencia, Spain

      6:    This file is part of SLEPc.

      8:    SLEPc is free software: you can redistribute it and/or modify it under  the
      9:    terms of version 3 of the GNU Lesser General Public License as published by
     10:    the Free Software Foundation.

     12:    SLEPc  is  distributed in the hope that it will be useful, but WITHOUT  ANY
     13:    WARRANTY;  without even the implied warranty of MERCHANTABILITY or  FITNESS
     14:    FOR  A  PARTICULAR PURPOSE. See the GNU Lesser General Public  License  for
     15:    more details.

     17:    You  should have received a copy of the GNU Lesser General  Public  License
     18:    along with SLEPc. If not, see <http://www.gnu.org/licenses/>.
     19:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     20: */

     22: static char help[] = "Computes exp(t*A)*v for a matrix associated with a Markov model.\n\n"
     23:   "The command line options are:\n"
     24:   "  -t <t>, where <t> = time parameter (multiplies the matrix).\n\n"
     25:   "  -m <m>, where <m> = number of grid subdivisions in each dimension.\n\n";

     27: #include <slepcmfn.h>

     29: /*
     30:    User-defined routines
     31: */
     32: PetscErrorCode MatMarkovModel(PetscInt m,Mat A);

     36: int main(int argc,char **argv)
     37: {
     38:   Mat                A;           /* problem matrix */
     39:   MFN                mfn;
     40:   FN                 f;
     41:   PetscReal          tol,norm;
     42:   PetscScalar        t=2.0;
     43:   Vec                v,y;
     44:   PetscInt           N,m=15,ncv,maxit,its;
     45:   PetscErrorCode     ierr;
     46:   PetscBool          draw_sol;
     47:   MFNConvergedReason reason;

     49:   SlepcInitialize(&argc,&argv,(char*)0,help);

     51:   PetscOptionsGetInt(NULL,NULL,"-m",&m,NULL);
     52:   PetscOptionsGetScalar(NULL,NULL,"-t",&t,NULL);
     53:   N = m*(m+1)/2;
     54:   PetscPrintf(PETSC_COMM_WORLD,"\nMarkov y=exp(t*A)*e_1, N=%D (m=%D)\n\n",N,m);

     56:   PetscOptionsHasName(NULL,NULL,"-draw_sol",&draw_sol);

     58:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     59:             Compute the transition probability matrix, A
     60:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

     62:   MatCreate(PETSC_COMM_WORLD,&A);
     63:   MatSetSizes(A,PETSC_DECIDE,PETSC_DECIDE,N,N);
     64:   MatSetFromOptions(A);
     65:   MatSetUp(A);
     66:   MatMarkovModel(m,A);

     68:   /* set v = e_1 */
     69:   MatCreateVecs(A,NULL,&y);
     70:   MatCreateVecs(A,NULL,&v);
     71:   VecSetValue(v,0,1.0,INSERT_VALUES);
     72:   VecAssemblyBegin(v);
     73:   VecAssemblyEnd(v);

     75:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     76:                 Create the solver and set various options
     77:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
     78:   /*
     79:      Create matrix function solver context
     80:   */
     81:   MFNCreate(PETSC_COMM_WORLD,&mfn);

     83:   /*
     84:      Set operator matrix, the function to compute, and other options
     85:   */
     86:   MFNSetOperator(mfn,A);
     87:   MFNGetFN(mfn,&f);
     88:   FNSetType(f,FNEXP);
     89:   FNSetScale(f,t,1.0);
     90:   MFNSetTolerances(mfn,1e-07,PETSC_DEFAULT);

     92:   /*
     93:      Set solver parameters at runtime
     94:   */
     95:   MFNSetFromOptions(mfn);

     97:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     98:                       Solve the problem, y=exp(t*A)*v
     99:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

    101:   MFNSolve(mfn,v,y);
    102:   MFNGetConvergedReason(mfn,&reason);
    103:   if (reason<0) SETERRQ(PETSC_COMM_WORLD,1,"Solver did not converge");
    104:   VecNorm(y,NORM_2,&norm);
    105:
    106:   /*
    107:      Optional: Get some information from the solver and display it
    108:   */
    109:   MFNGetIterationNumber(mfn,&its);
    110:   PetscPrintf(PETSC_COMM_WORLD," Number of iterations of the method: %D\n",its);
    111:   MFNGetDimensions(mfn,&ncv);
    112:   PetscPrintf(PETSC_COMM_WORLD," Subspace dimension: %D\n",ncv);
    113:   MFNGetTolerances(mfn,&tol,&maxit);
    114:   PetscPrintf(PETSC_COMM_WORLD," Stopping condition: tol=%.4g, maxit=%D\n",(double)tol,maxit);

    116:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    117:                     Display solution and clean up
    118:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
    119:   PetscPrintf(PETSC_COMM_WORLD," Computed vector at time t=%.4g has norm %g\n\n",(double)PetscRealPart(t),(double)norm);
    120:   if (draw_sol) {
    121:     PetscViewerDrawSetPause(PETSC_VIEWER_DRAW_WORLD,-1);
    122:     VecView(y,PETSC_VIEWER_DRAW_WORLD);
    123:   }

    125:   /*
    126:      Free work space
    127:   */
    128:   MFNDestroy(&mfn);
    129:   MatDestroy(&A);
    130:   VecDestroy(&v);
    131:   VecDestroy(&y);
    132:   SlepcFinalize();
    133:   return ierr;
    134: }

    138: /*
    139:     Matrix generator for a Markov model of a random walk on a triangular grid.
    140:     See ex5.c for additional details.
    141: */
    142: PetscErrorCode MatMarkovModel(PetscInt m,Mat A)
    143: {
    144:   const PetscReal cst = 0.5/(PetscReal)(m-1);
    145:   PetscReal       pd,pu;
    146:   PetscInt        Istart,Iend,i,j,jmax,ix=0;
    147:   PetscErrorCode  ierr;

    150:   MatGetOwnershipRange(A,&Istart,&Iend);
    151:   for (i=1;i<=m;i++) {
    152:     jmax = m-i+1;
    153:     for (j=1;j<=jmax;j++) {
    154:       ix = ix + 1;
    155:       if (ix-1<Istart || ix>Iend) continue;  /* compute only owned rows */
    156:       if (j!=jmax) {
    157:         pd = cst*(PetscReal)(i+j-1);
    158:         /* north */
    159:         if (i==1) {
    160:           MatSetValue(A,ix-1,ix,2*pd,INSERT_VALUES);
    161:         } else {
    162:           MatSetValue(A,ix-1,ix,pd,INSERT_VALUES);
    163:         }
    164:         /* east */
    165:         if (j==1) {
    166:           MatSetValue(A,ix-1,ix+jmax-1,2*pd,INSERT_VALUES);
    167:         } else {
    168:           MatSetValue(A,ix-1,ix+jmax-1,pd,INSERT_VALUES);
    169:         }
    170:       }
    171:       /* south */
    172:       pu = 0.5 - cst*(PetscReal)(i+j-3);
    173:       if (j>1) {
    174:         MatSetValue(A,ix-1,ix-2,pu,INSERT_VALUES);
    175:       }
    176:       /* west */
    177:       if (i>1) {
    178:         MatSetValue(A,ix-1,ix-jmax-2,pu,INSERT_VALUES);
    179:       }
    180:     }
    181:   }
    182:   MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
    183:   MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
    184:   return(0);
    185: }