Date: 2022-08-09T09:05:46+00:00

Actual source code: test1.c
slepc-3.17.2 2022-08-09
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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: */

     11: static char help[] = "Test the solution of a SVD without calling SVDSetFromOptions (based on ex8.c).\n\n"
     12:   "The command line options are:\n"
     13:   "  -n <n>, where <n> = matrix dimension.\n"
     14:   "  -type <svd_type> = svd type to test.\n\n";

     16: #include <slepcsvd.h>

     18: /*
     19:    This example computes the singular values of an nxn Grcar matrix,
     20:    which is a nonsymmetric Toeplitz matrix:

     22:               |  1  1  1  1               |
     23:               | -1  1  1  1  1            |
     24:               |    -1  1  1  1  1         |
     25:               |       .  .  .  .  .       |
     26:           A = |          .  .  .  .  .    |
     27:               |            -1  1  1  1  1 |
     28:               |               -1  1  1  1 |
     29:               |                  -1  1  1 |
     30:               |                     -1  1 |

     32:  */

     34: int main(int argc,char **argv)
     35: {
     36:   Mat            A;               /* Grcar matrix */
     37:   SVD            svd;             /* singular value solver context */
     38:   PetscInt       N=30,Istart,Iend,i,col[5],nconv1,nconv2;
     39:   PetscScalar    value[] = { -1, 1, 1, 1, 1 };
     40:   PetscReal      sigma_1,sigma_n;
     41:   char           svdtype[30] = "cross",epstype[30] = "";
     42:   PetscBool      flg;
     43:   EPS            eps;

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

     47:   PetscOptionsGetInt(NULL,NULL,"-n",&N,NULL);
     48:   PetscOptionsGetString(NULL,NULL,"-type",svdtype,sizeof(svdtype),NULL);
     49:   PetscOptionsGetString(NULL,NULL,"-epstype",epstype,sizeof(epstype),&flg);
     50:   PetscPrintf(PETSC_COMM_WORLD,"\nEstimate the condition number of a Grcar matrix, n=%" PetscInt_FMT,N);
     51:   PetscPrintf(PETSC_COMM_WORLD,"\n\n");

     53:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     54:         Generate the matrix
     55:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

     57:   MatCreate(PETSC_COMM_WORLD,&A);
     58:   MatSetSizes(A,PETSC_DECIDE,PETSC_DECIDE,N,N);
     59:   MatSetFromOptions(A);
     60:   MatSetUp(A);

     62:   MatGetOwnershipRange(A,&Istart,&Iend);
     63:   for (i=Istart;i<Iend;i++) {
     64:     col[0]=i-1; col[1]=i; col[2]=i+1; col[3]=i+2; col[4]=i+3;
     65:     if (i==0) MatSetValues(A,1,&i,4,col+1,value+1,INSERT_VALUES);
     66:     else MatSetValues(A,1,&i,PetscMin(5,N-i+1),col,value,INSERT_VALUES);
     67:   }

     69:   MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
     70:   MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);

     72:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     73:          Create the singular value solver and set the solution method
     74:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

     76:   /*
     77:      Create singular value context
     78:   */
     79:   SVDCreate(PETSC_COMM_WORLD,&svd);

     81:   /*
     82:      Set operator
     83:   */
     84:   SVDSetOperators(svd,A,NULL);

     86:   /*
     87:      Set solver parameters at runtime
     88:   */
     89:   SVDSetType(svd,svdtype);
     90:   if (flg) {
     91:     PetscObjectTypeCompare((PetscObject)svd,SVDCROSS,&flg);
     92:     if (flg) {
     93:       SVDCrossGetEPS(svd,&eps);
     94:       EPSSetType(eps,epstype);
     95:     }
     96:     PetscObjectTypeCompare((PetscObject)svd,SVDCYCLIC,&flg);
     97:     if (flg) {
     98:       SVDCyclicGetEPS(svd,&eps);
     99:       EPSSetType(eps,epstype);
    100:     }
    101:   }
    102:   SVDSetDimensions(svd,1,PETSC_DEFAULT,PETSC_DEFAULT);
    103:   SVDSetTolerances(svd,1e-6,1000);

    105:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    106:                       Compute the singular values
    107:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

    109:   /*
    110:      First request the largest singular value
    111:   */
    112:   SVDSetWhichSingularTriplets(svd,SVD_LARGEST);
    113:   SVDSolve(svd);
    114:   /*
    115:      Get number of converged singular values
    116:   */
    117:   SVDGetConverged(svd,&nconv1);
    118:   /*
    119:      Get converged singular values: largest singular value is stored in sigma_1.
    120:      In this example, we are not interested in the singular vectors
    121:   */
    122:   if (nconv1 > 0) SVDGetSingularTriplet(svd,0,&sigma_1,NULL,NULL);
    123:   else PetscPrintf(PETSC_COMM_WORLD," Unable to compute large singular value!\n\n");

    125:   /*
    126:      Request the smallest singular value
    127:   */
    128:   SVDSetWhichSingularTriplets(svd,SVD_SMALLEST);
    129:   SVDSolve(svd);
    130:   /*
    131:      Get number of converged triplets
    132:   */
    133:   SVDGetConverged(svd,&nconv2);
    134:   /*
    135:      Get converged singular values: smallest singular value is stored in sigma_n.
    136:      As before, we are not interested in the singular vectors
    137:   */
    138:   if (nconv2 > 0) SVDGetSingularTriplet(svd,0,&sigma_n,NULL,NULL);
    139:   else PetscPrintf(PETSC_COMM_WORLD," Unable to compute small singular value!\n\n");

    141:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    142:                     Display solution and clean up
    143:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
    144:   if (nconv1 > 0 && nconv2 > 0) {
    145:     PetscPrintf(PETSC_COMM_WORLD," Computed singular values: sigma_1=%.4f, sigma_n=%.4f\n",(double)sigma_1,(double)sigma_n);
    146:     PetscPrintf(PETSC_COMM_WORLD," Estimated condition number: sigma_1/sigma_n=%.4f\n\n",(double)(sigma_1/sigma_n));
    147:   }

    149:   /*
    150:      Free work space
    151:   */
    152:   SVDDestroy(&svd);
    153:   MatDestroy(&A);
    154:   SlepcFinalize();
    155:   return 0;
    156: }

    158: /*TEST

    160:    test:
    161:       suffix: 1
    162:       args: -type {{lanczos trlanczos cross cyclic lapack}}

    164:    test:
    165:       suffix: 1_cross_gd
    166:       args: -type cross -epstype gd
    167:       output_file: output/test1_1.out

    169:    test:
    170:       suffix: 1_cyclic_gd
    171:       args: -type cyclic -epstype gd
    172:       output_file: output/test1_1.out
    173:       requires: !single

    175:    test:
    176:       suffix: 1_primme
    177:       args: -type primme
    178:       requires: primme
    179:       output_file: output/test1_1.out

    181: TEST*/