Date: 2022-10-01T06:40:17+00:00

Actual source code: test16.c
slepc-3.18.0 2022-10-01
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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[] = "Tests multiple calls to SVDSolve with equal matrix size (GSVD).\n\n"
     12:   "The command line options are:\n"
     13:   "  -m <m>, where <m> = number of rows of A.\n"
     14:   "  -n <n>, where <n> = number of columns of A.\n"
     15:   "  -p <p>, where <p> = number of rows of B.\n\n";

     17: #include <slepcsvd.h>

     19: /*
     20:    This example solves two GSVD problems for the bidiagonal matrices

     22:               |  1  2                     |       |  1                        |
     23:               |     1  2                  |       |  2  1                     |
     24:               |        1  2               |       |     2  1                  |
     25:          A1 = |          .  .             |  A2 = |       .  .                |
     26:               |             .  .          |       |          .  .             |
     27:               |                1  2       |       |             2  1          |
     28:               |                   1  2    |       |                2  1       |

     30:    with B = tril(ones(p,n))
     31:  */

     33: int main(int argc,char **argv)
     34: {
     35:   Mat            A1,A2,B;
     36:   SVD            svd;
     37:   PetscInt       m=15,n=20,p=21,Istart,Iend,i,j,d,col[2];
     38:   PetscScalar    valsa[] = { 1, 2 }, valsb[] = { 2, 1 };

     41:   SlepcInitialize(&argc,&argv,(char*)0,help);
     42:   PetscOptionsGetInt(NULL,NULL,"-m",&m,NULL);
     43:   PetscOptionsGetInt(NULL,NULL,"-n",&n,NULL);
     44:   PetscOptionsGetInt(NULL,NULL,"-p",&p,NULL);
     45:   PetscPrintf(PETSC_COMM_WORLD,"\nGeneralized singular value decomposition, (%" PetscInt_FMT "+%" PetscInt_FMT ")x%" PetscInt_FMT "\n\n",m,p,n);

     47:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     48:                      Generate the matrices
     49:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

     51:   MatCreate(PETSC_COMM_WORLD,&A1);
     52:   MatSetSizes(A1,PETSC_DECIDE,PETSC_DECIDE,m,n);
     53:   MatSetFromOptions(A1);
     54:   MatSetUp(A1);
     55:   MatGetOwnershipRange(A1,&Istart,&Iend);
     56:   for (i=Istart;i<Iend;i++) {
     57:     col[0]=i; col[1]=i+1;
     58:     if (i<n-1) MatSetValues(A1,1,&i,2,col,valsa,INSERT_VALUES);
     59:     else if (i==n-1) MatSetValue(A1,i,col[0],valsa[0],INSERT_VALUES);
     60:   }
     61:   MatAssemblyBegin(A1,MAT_FINAL_ASSEMBLY);
     62:   MatAssemblyEnd(A1,MAT_FINAL_ASSEMBLY);

     64:   MatCreate(PETSC_COMM_WORLD,&A2);
     65:   MatSetSizes(A2,PETSC_DECIDE,PETSC_DECIDE,m,n);
     66:   MatSetFromOptions(A2);
     67:   MatSetUp(A2);
     68:   MatGetOwnershipRange(A2,&Istart,&Iend);
     69:   for (i=Istart;i<Iend;i++) {
     70:     col[0]=i-1; col[1]=i;
     71:     if (i==0) MatSetValue(A2,i,col[1],valsb[1],INSERT_VALUES);
     72:     else if (i<n) MatSetValues(A2,1,&i,2,col,valsb,INSERT_VALUES);
     73:     else if (i==n) MatSetValue(A2,i,col[0],valsb[0],INSERT_VALUES);
     74:   }
     75:   MatAssemblyBegin(A2,MAT_FINAL_ASSEMBLY);
     76:   MatAssemblyEnd(A2,MAT_FINAL_ASSEMBLY);

     78:   MatCreate(PETSC_COMM_WORLD,&B);
     79:   MatSetSizes(B,PETSC_DECIDE,PETSC_DECIDE,p,n);
     80:   MatSetFromOptions(B);
     81:   MatSetUp(B);
     82:   MatGetOwnershipRange(B,&Istart,&Iend);
     83:   d = PetscMax(0,n-p);
     84:   for (i=Istart;i<Iend;i++) {
     85:     for (j=PetscMax(0,i-5);j<=PetscMin(i,n-1);j++) MatSetValue(B,i,j+d,1.0,INSERT_VALUES);
     86:   }
     87:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
     88:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);

     90:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     91:          Create the singular value solver, set options and solve
     92:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

     94:   SVDCreate(PETSC_COMM_WORLD,&svd);
     95:   SVDSetOperators(svd,A1,B);
     96:   SVDSetFromOptions(svd);
     97:   SVDSolve(svd);
     98:   SVDErrorView(svd,SVD_ERROR_NORM,NULL);

    100:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    101:                        Solve second problem
    102:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

    104:   SVDSetOperators(svd,A2,B);
    105:   SVDSolve(svd);
    106:   SVDErrorView(svd,SVD_ERROR_NORM,NULL);

    108:   /* Free work space */
    109:   SVDDestroy(&svd);
    110:   MatDestroy(&A1);
    111:   MatDestroy(&A2);
    112:   MatDestroy(&B);
    113:   SlepcFinalize();
    114:   return 0;
    115: }

    117: /*TEST

    119:    testset:
    120:       args: -svd_nsv 3
    121:       requires: !single
    122:       output_file: output/test16_1.out
    123:       test:
    124:          suffix: 1_lapack
    125:          args: -svd_type lapack
    126:       test:
    127:          suffix: 1_cross
    128:          args: -svd_type cross -svd_cross_explicitmatrix {{0 1}}
    129:       test:
    130:          suffix: 1_cyclic
    131:          args: -svd_type cyclic -svd_cyclic_explicitmatrix {{0 1}}
    132:       test:
    133:          suffix: 1_trlanczos
    134:          args: -svd_type trlanczos -svd_trlanczos_gbidiag {{single lower}} -svd_trlanczos_ksp_rtol 1e-10
    135:          requires: double
    136:       test:
    137:          suffix: 1_trlanczos_par
    138:          nsize: 2
    139:          args: -svd_type trlanczos -ds_parallel {{redundant synchronized}}

    141: TEST*/