Actual source code: test14.c

slepc-3.22.2 2024-12-02
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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.\n\n"
 12:   "The command line options are:\n"
 13:   "  -m <m>, where <m> = matrix rows.\n"
 14:   "  -n <n>, where <n> = matrix columns (defaults to m+2).\n\n";

 16: #include <slepcsvd.h>

 18: /*
 19:    This example computes the singular values of two rectangular bidiagonal matrices

 21:               |  1  2                     |       |  1                        |
 22:               |     1  2                  |       |  2  1                     |
 23:               |        1  2               |       |     2  1                  |
 24:           A = |          .  .             |   B = |       .  .                |
 25:               |             .  .          |       |          .  .             |
 26:               |                1  2       |       |             2  1          |
 27:               |                   1  2    |       |                2  1       |
 28:  */

 30: int main(int argc,char **argv)
 31: {
 32:   Mat            A,B;
 33:   SVD            svd;
 34:   PetscInt       m=20,n,Istart,Iend,i,col[2];
 35:   PetscScalar    valsa[] = { 1, 2 }, valsb[] = { 2, 1 };
 36:   PetscBool      flg;

 38:   PetscFunctionBeginUser;
 39:   PetscCall(SlepcInitialize(&argc,&argv,NULL,help));
 40:   PetscCall(PetscOptionsGetInt(NULL,NULL,"-m",&m,NULL));
 41:   PetscCall(PetscOptionsGetInt(NULL,NULL,"-n",&n,&flg));
 42:   if (!flg) n=m+2;
 43:   PetscCall(PetscPrintf(PETSC_COMM_WORLD,"\nRectangular bidiagonal matrix, m=%" PetscInt_FMT " n=%" PetscInt_FMT "\n\n",m,n));

 45:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
 46:                      Generate the matrices
 47:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

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

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

 74:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
 75:          Create the singular value solver, set options and solve
 76:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

 78:   PetscCall(SVDCreate(PETSC_COMM_WORLD,&svd));
 79:   PetscCall(SVDSetOperators(svd,A,NULL));
 80:   PetscCall(SVDSetTolerances(svd,PETSC_CURRENT,1000));
 81:   PetscCall(SVDSetFromOptions(svd));
 82:   PetscCall(SVDSolve(svd));
 83:   PetscCall(SVDErrorView(svd,SVD_ERROR_RELATIVE,NULL));

 85:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
 86:                        Solve with second matrix
 87:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

 89:   PetscCall(SVDSetOperators(svd,B,NULL));
 90:   PetscCall(SVDSolve(svd));
 91:   PetscCall(SVDErrorView(svd,SVD_ERROR_RELATIVE,NULL));

 93:   /* Free work space */
 94:   PetscCall(SVDDestroy(&svd));
 95:   PetscCall(MatDestroy(&A));
 96:   PetscCall(MatDestroy(&B));
 97:   PetscCall(SlepcFinalize());
 98:   return 0;
 99: }

101: /*TEST

103:    testset:
104:       args: -svd_nsv 3
105:       requires: !single
106:       output_file: output/test14_1.out
107:       test:
108:          suffix: 1
109:          args: -svd_type {{lanczos trlanczos lapack}}
110:       test:
111:          suffix: 1_cross
112:          args: -svd_type cross -svd_cross_explicitmatrix {{0 1}}
113:       test:
114:          suffix: 1_cyclic
115:          args: -svd_type cyclic -svd_cyclic_explicitmatrix {{0 1}}

117:    testset:
118:       args: -n 18 -svd_nsv 3
119:       requires: !single
120:       output_file: output/test14_2.out
121:       test:
122:          suffix: 2
123:          args: -svd_type {{lanczos trlanczos lapack}}
124:       test:
125:          suffix: 2_cross
126:          args: -svd_type cross -svd_cross_explicitmatrix {{0 1}}
127:       test:
128:          suffix: 2_cyclic
129:          args: -svd_type cyclic -svd_cyclic_explicitmatrix {{0 1}}

131: TEST*/