LCOV - code coverage report
Current view: top level - svd/tests - test1.c (source / functions) Hit Total Coverage
Test: SLEPc Lines: 54 56 96.4 %
Date: 2024-11-21 00:34:55 Functions: 1 1 100.0 %
Legend: Lines: hit not hit

          Line data    Source code
       1             : /*
       2             :    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
       3             :    SLEPc - Scalable Library for Eigenvalue Problem Computations
       4             :    Copyright (c) 2002-, Universitat Politecnica de Valencia, Spain
       5             : 
       6             :    This file is part of SLEPc.
       7             :    SLEPc is distributed under a 2-clause BSD license (see LICENSE).
       8             :    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
       9             : */
      10             : 
      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";
      15             : 
      16             : #include <slepcsvd.h>
      17             : 
      18             : /*
      19             :    This example computes the singular values of an nxn Grcar matrix,
      20             :    which is a nonsymmetric Toeplitz matrix:
      21             : 
      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 |
      31             : 
      32             :  */
      33             : 
      34           8 : int main(int argc,char **argv)
      35             : {
      36           8 :   Mat            A;               /* Grcar matrix */
      37           8 :   SVD            svd;             /* singular value solver context */
      38           8 :   PetscInt       N=30,Istart,Iend,i,col[5],nconv1,nconv2;
      39           8 :   PetscScalar    value[] = { -1, 1, 1, 1, 1 };
      40           8 :   PetscReal      sigma_1,sigma_n;
      41           8 :   char           svdtype[30] = "cross",epstype[30] = "";
      42           8 :   PetscBool      flg;
      43           8 :   EPS            eps;
      44             : 
      45           8 :   PetscFunctionBeginUser;
      46           8 :   PetscCall(SlepcInitialize(&argc,&argv,NULL,help));
      47             : 
      48           8 :   PetscCall(PetscOptionsGetInt(NULL,NULL,"-n",&N,NULL));
      49           8 :   PetscCall(PetscOptionsGetString(NULL,NULL,"-type",svdtype,sizeof(svdtype),NULL));
      50           8 :   PetscCall(PetscOptionsGetString(NULL,NULL,"-epstype",epstype,sizeof(epstype),&flg));
      51           8 :   PetscCall(PetscPrintf(PETSC_COMM_WORLD,"\nEstimate the condition number of a Grcar matrix, n=%" PetscInt_FMT,N));
      52           8 :   PetscCall(PetscPrintf(PETSC_COMM_WORLD,"\n\n"));
      53             : 
      54             :   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      55             :         Generate the matrix
      56             :      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
      57             : 
      58           8 :   PetscCall(MatCreate(PETSC_COMM_WORLD,&A));
      59           8 :   PetscCall(MatSetSizes(A,PETSC_DECIDE,PETSC_DECIDE,N,N));
      60           8 :   PetscCall(MatSetFromOptions(A));
      61             : 
      62           8 :   PetscCall(MatGetOwnershipRange(A,&Istart,&Iend));
      63         248 :   for (i=Istart;i<Iend;i++) {
      64         240 :     col[0]=i-1; col[1]=i; col[2]=i+1; col[3]=i+2; col[4]=i+3;
      65         240 :     if (i==0) PetscCall(MatSetValues(A,1,&i,4,col+1,value+1,INSERT_VALUES));
      66         240 :     else PetscCall(MatSetValues(A,1,&i,PetscMin(5,N-i+1),col,value,INSERT_VALUES));
      67             :   }
      68             : 
      69           8 :   PetscCall(MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY));
      70           8 :   PetscCall(MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY));
      71             : 
      72             :   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      73             :          Create the singular value solver and set the solution method
      74             :      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
      75             : 
      76             :   /*
      77             :      Create singular value context
      78             :   */
      79           8 :   PetscCall(SVDCreate(PETSC_COMM_WORLD,&svd));
      80             : 
      81             :   /*
      82             :      Set operator
      83             :   */
      84           8 :   PetscCall(SVDSetOperators(svd,A,NULL));
      85             : 
      86             :   /*
      87             :      Set solver parameters at runtime
      88             :   */
      89           8 :   PetscCall(SVDSetType(svd,svdtype));
      90           8 :   if (flg) {
      91           2 :     PetscCall(PetscObjectTypeCompare((PetscObject)svd,SVDCROSS,&flg));
      92           2 :     if (flg) {
      93           1 :       PetscCall(SVDCrossGetEPS(svd,&eps));
      94           1 :       PetscCall(EPSSetType(eps,epstype));
      95             :     }
      96           2 :     PetscCall(PetscObjectTypeCompare((PetscObject)svd,SVDCYCLIC,&flg));
      97           2 :     if (flg) {
      98           1 :       PetscCall(SVDCyclicGetEPS(svd,&eps));
      99           1 :       PetscCall(EPSSetType(eps,epstype));
     100             :     }
     101             :   }
     102           8 :   PetscCall(SVDSetDimensions(svd,1,PETSC_DETERMINE,PETSC_DETERMINE));
     103           8 :   PetscCall(SVDSetTolerances(svd,1e-6,1000));
     104             : 
     105             :   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     106             :                       Compute the singular values
     107             :      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
     108             : 
     109             :   /*
     110             :      First request the largest singular value
     111             :   */
     112           8 :   PetscCall(SVDSetWhichSingularTriplets(svd,SVD_LARGEST));
     113           8 :   PetscCall(SVDSolve(svd));
     114             :   /*
     115             :      Get number of converged singular values
     116             :   */
     117           8 :   PetscCall(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           8 :   if (nconv1 > 0) PetscCall(SVDGetSingularTriplet(svd,0,&sigma_1,NULL,NULL));
     123           0 :   else PetscCall(PetscPrintf(PETSC_COMM_WORLD," Unable to compute large singular value!\n\n"));
     124             : 
     125             :   /*
     126             :      Request the smallest singular value
     127             :   */
     128           8 :   PetscCall(SVDSetWhichSingularTriplets(svd,SVD_SMALLEST));
     129           8 :   PetscCall(SVDSolve(svd));
     130             :   /*
     131             :      Get number of converged triplets
     132             :   */
     133           8 :   PetscCall(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           8 :   if (nconv2 > 0) PetscCall(SVDGetSingularTriplet(svd,0,&sigma_n,NULL,NULL));
     139           0 :   else PetscCall(PetscPrintf(PETSC_COMM_WORLD," Unable to compute small singular value!\n\n"));
     140             : 
     141             :   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     142             :                     Display solution and clean up
     143             :      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
     144           8 :   if (nconv1 > 0 && nconv2 > 0) {
     145           8 :     PetscCall(PetscPrintf(PETSC_COMM_WORLD," Computed singular values: sigma_1=%.4f, sigma_n=%.4f\n",(double)sigma_1,(double)sigma_n));
     146           8 :     PetscCall(PetscPrintf(PETSC_COMM_WORLD," Estimated condition number: sigma_1/sigma_n=%.4f\n\n",(double)(sigma_1/sigma_n)));
     147             :   }
     148             : 
     149             :   /*
     150             :      Free work space
     151             :   */
     152           8 :   PetscCall(SVDDestroy(&svd));
     153           8 :   PetscCall(MatDestroy(&A));
     154           8 :   PetscCall(SlepcFinalize());
     155             :   return 0;
     156             : }
     157             : 
     158             : /*TEST
     159             : 
     160             :    test:
     161             :       suffix: 1
     162             :       args: -type {{lanczos trlanczos cross cyclic lapack}}
     163             : 
     164             :    test:
     165             :       suffix: 1_cross_gd
     166             :       args: -type cross -epstype gd
     167             :       output_file: output/test1_1.out
     168             : 
     169             :    test:
     170             :       suffix: 1_cyclic_gd
     171             :       args: -type cyclic -epstype gd
     172             :       output_file: output/test1_1.out
     173             :       requires: !single
     174             : 
     175             :    test:
     176             :       suffix: 1_primme
     177             :       args: -type primme
     178             :       requires: primme
     179             :       output_file: output/test1_1.out
     180             : 
     181             : TEST*/

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