Actual source code: test18.c

slepc-3.19.2 2023-09-05
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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 GSVD with user-provided initial vectors.\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 a GSVD problem for the bidiagonal matrices

 22:               |  1  2                     |       |  2                        |
 23:               |     1  2                  |       | -1  2                     |
 24:               |        1  2               |       |    -1  2                  |
 25:           A = |          .  .             |   B = |       .  .                |
 26:               |             .  .          |       |          .  .             |
 27:               |                1  2       |       |            -1  2          |
 28:               |                   1  2    |       |               -1  2       |
 29:  */

 31: int main(int argc,char **argv)
 32: {
 33:   Mat            A,B;
 34:   SVD            svd;
 35:   Vec            v0,w0;           /* initial vectors */
 36:   VecType        vtype;
 37:   PetscInt       m=22,n=20,p=22,Istart,Iend,i,col[2];
 38:   PetscScalar    valsa[] = { 1, 2 }, valsb[] = { -1, 2 };

 40:   PetscFunctionBeginUser;
 41:   PetscCall(SlepcInitialize(&argc,&argv,(char*)0,help));
 42:   PetscCall(PetscOptionsGetInt(NULL,NULL,"-m",&m,NULL));
 43:   PetscCall(PetscOptionsGetInt(NULL,NULL,"-n",&n,NULL));
 44:   PetscCall(PetscOptionsGetInt(NULL,NULL,"-p",&p,NULL));
 45:   PetscCall(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:   PetscCall(MatCreate(PETSC_COMM_WORLD,&A));
 52:   PetscCall(MatSetSizes(A,PETSC_DECIDE,PETSC_DECIDE,m,n));
 53:   PetscCall(MatSetFromOptions(A));
 54:   PetscCall(MatSetUp(A));
 55:   PetscCall(MatGetOwnershipRange(A,&Istart,&Iend));
 56:   for (i=Istart;i<Iend;i++) {
 57:     col[0]=i; col[1]=i+1;
 58:     if (i<n-1) PetscCall(MatSetValues(A,1,&i,2,col,valsa,INSERT_VALUES));
 59:     else if (i==n-1) PetscCall(MatSetValue(A,i,col[0],valsa[0],INSERT_VALUES));
 60:   }
 61:   PetscCall(MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY));
 62:   PetscCall(MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY));

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

 78:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
 79:          Create the singular value solver, set options and solve
 80:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

 82:   PetscCall(SVDCreate(PETSC_COMM_WORLD,&svd));
 83:   PetscCall(SVDSetOperators(svd,A,B));
 84:   PetscCall(SVDSetFromOptions(svd));

 86:   /*
 87:      Set the initial vectors. This is optional, if not done the initial
 88:      vectors are set to random values
 89:   */
 90:   PetscCall(MatCreateVecs(A,&v0,NULL));        /* right initial vector, length n */
 91:   PetscCall(VecCreate(PETSC_COMM_WORLD,&w0));  /* left initial vector, length m+p */
 92:   PetscCall(VecSetSizes(w0,PETSC_DECIDE,m+p));
 93:   PetscCall(VecGetType(v0,&vtype));
 94:   PetscCall(VecSetType(w0,vtype));
 95:   PetscCall(VecSet(v0,1.0));
 96:   PetscCall(VecSet(w0,1.0));
 97:   PetscCall(SVDSetInitialSpaces(svd,1,&v0,1,&w0));

 99:   /*
100:      Compute solution
101:   */
102:   PetscCall(SVDSolve(svd));
103:   PetscCall(SVDErrorView(svd,SVD_ERROR_NORM,NULL));

105:   /* Free work space */
106:   PetscCall(VecDestroy(&v0));
107:   PetscCall(VecDestroy(&w0));
108:   PetscCall(SVDDestroy(&svd));
109:   PetscCall(MatDestroy(&A));
110:   PetscCall(MatDestroy(&B));
111:   PetscCall(SlepcFinalize());
112:   return 0;
113: }

115: /*TEST

117:    testset:
118:       args: -svd_nsv 3
119:       requires: !single
120:       output_file: output/test18_1.out
121:       test:
122:          suffix: 1
123:          args: -svd_type {{lapack cross cyclic}}
124:       test:
125:          suffix: 1_trlanczos
126:          args: -svd_type trlanczos -svd_trlanczos_gbidiag {{single upper lower}}
127:          requires: !__float128

129:    test:
130:       suffix: 2
131:       args: -svd_nsv 3 -svd_type trlanczos -svd_monitor_conditioning
132:       requires: double

134: TEST*/