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 DSSVD.\n\n";
      12             : 
      13             : #include <slepcds.h>
      14             : 
      15           4 : int main(int argc,char **argv)
      16             : {
      17           4 :   DS             ds;
      18           4 :   SlepcSC        sc;
      19           4 :   PetscReal      sigma,rnorm,aux;
      20           4 :   PetscScalar    *A,*U,*w,d;
      21           4 :   PetscInt       i,j,k,n=15,m=10,m1,ld;
      22           4 :   PetscViewer    viewer;
      23           4 :   PetscBool      verbose,extrarow;
      24             : 
      25           4 :   PetscFunctionBeginUser;
      26           4 :   PetscCall(SlepcInitialize(&argc,&argv,NULL,help));
      27           4 :   PetscCall(PetscOptionsGetInt(NULL,NULL,"-n",&n,NULL));
      28           4 :   PetscCall(PetscOptionsGetInt(NULL,NULL,"-m",&m,NULL));
      29           4 :   k = PetscMin(n,m);
      30           4 :   PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Solve a Dense System of type SVD - dimension %" PetscInt_FMT "x%" PetscInt_FMT ".\n",n,m));
      31           4 :   PetscCall(PetscOptionsHasName(NULL,NULL,"-verbose",&verbose));
      32           4 :   PetscCall(PetscOptionsHasName(NULL,NULL,"-extrarow",&extrarow));
      33             : 
      34             :   /* Create DS object */
      35           4 :   PetscCall(DSCreate(PETSC_COMM_WORLD,&ds));
      36           4 :   PetscCall(DSSetType(ds,DSSVD));
      37           4 :   PetscCall(DSSetFromOptions(ds));
      38           4 :   ld = PetscMax(n,m)+2;  /* test leading dimension larger than n */
      39           4 :   PetscCall(DSAllocate(ds,ld));
      40           4 :   PetscCall(DSSetDimensions(ds,n,0,0));
      41           4 :   PetscCall(DSSVDSetDimensions(ds,m));
      42           4 :   PetscCall(DSSVDGetDimensions(ds,&m1));
      43           4 :   PetscCheck(m1==m,PETSC_COMM_WORLD,PETSC_ERR_PLIB,"Inconsistent dimension value");
      44           4 :   PetscCall(DSSetExtraRow(ds,extrarow));
      45             : 
      46             :   /* Set up viewer */
      47           4 :   PetscCall(PetscViewerASCIIGetStdout(PETSC_COMM_WORLD,&viewer));
      48           4 :   PetscCall(PetscViewerPushFormat(viewer,PETSC_VIEWER_ASCII_INFO_DETAIL));
      49           4 :   PetscCall(DSView(ds,viewer));
      50           4 :   PetscCall(PetscViewerPopFormat(viewer));
      51             : 
      52             :   /* Fill with a rectangular Toeplitz matrix */
      53           4 :   PetscCall(DSGetArray(ds,DS_MAT_A,&A));
      54          44 :   for (i=0;i<k;i++) A[i+i*ld]=1.0;
      55          12 :   for (j=1;j<3;j++) {
      56          76 :     for (i=0;i<m-j;i++) { if ((i+j)<m) A[i+(i+j)*ld]=(PetscScalar)(j+1); }
      57             :   }
      58          28 :   for (j=1;j<n/2;j++) {
      59         300 :     for (i=0;i<n-j;i++) { if ((i+j)<n && i<m) A[(i+j)+i*ld]=-1.0; }
      60             :   }
      61           4 :   if (extrarow) { A[n-2+m*ld]=1.0; A[n-1+m*ld]=1.0; }  /* really an extra column */
      62           4 :   PetscCall(DSRestoreArray(ds,DS_MAT_A,&A));
      63           4 :   PetscCall(DSSetState(ds,DS_STATE_RAW));
      64           4 :   if (verbose) {
      65           0 :     PetscCall(PetscViewerPushFormat(viewer,PETSC_VIEWER_ASCII_MATLAB));
      66           0 :     PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Initial - - - - - - - - -\n"));
      67             :   }
      68           4 :   PetscCall(DSView(ds,viewer));
      69             : 
      70             :   /* Solve */
      71           4 :   PetscCall(PetscMalloc1(k,&w));
      72           4 :   PetscCall(DSGetSlepcSC(ds,&sc));
      73           4 :   sc->comparison    = SlepcCompareLargestReal;
      74           4 :   sc->comparisonctx = NULL;
      75           4 :   sc->map           = NULL;
      76           4 :   sc->mapobj        = NULL;
      77           4 :   PetscCall(DSSolve(ds,w,NULL));
      78           4 :   PetscCall(DSSort(ds,w,NULL,NULL,NULL,NULL));
      79           4 :   if (extrarow) PetscCall(DSUpdateExtraRow(ds));
      80           4 :   if (verbose) {
      81           0 :     PetscCall(PetscPrintf(PETSC_COMM_WORLD,"After solve - - - - - - - - -\n"));
      82           0 :     PetscCall(DSView(ds,viewer));
      83             :   }
      84             : 
      85             :   /* Print singular values */
      86           4 :   PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Computed singular values =\n"));
      87          44 :   for (i=0;i<k;i++) {
      88          40 :     sigma = PetscRealPart(w[i]);
      89          40 :     PetscCall(PetscViewerASCIIPrintf(viewer,"  %.5f\n",(double)sigma));
      90             :   }
      91             : 
      92           4 :   if (extrarow) {
      93             :     /* Check that extra column is correct */
      94           2 :     PetscCall(DSGetArray(ds,DS_MAT_A,&A));
      95           2 :     PetscCall(DSGetArray(ds,DS_MAT_U,&U));
      96             :     d = 0.0;
      97          32 :     for (i=0;i<n;i++) d += A[i+m*ld]-U[n-2+i*ld]-U[n-1+i*ld];
      98           2 :     if (PetscAbsScalar(d)>10*PETSC_MACHINE_EPSILON) PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Warning: there is a mismatch in the extra row of %g\n",(double)PetscAbsScalar(d)));
      99           2 :     PetscCall(DSRestoreArray(ds,DS_MAT_A,&A));
     100           2 :     PetscCall(DSRestoreArray(ds,DS_MAT_U,&U));
     101             :   }
     102             : 
     103             :   /* Singular vectors */
     104           4 :   PetscCall(DSVectors(ds,DS_MAT_U,NULL,NULL));  /* all singular vectors */
     105           4 :   j = 0;
     106           4 :   rnorm = 0.0;
     107           4 :   PetscCall(DSGetArray(ds,DS_MAT_U,&U));
     108          64 :   for (i=0;i<n;i++) {
     109          60 :     aux = PetscAbsScalar(U[i+j*ld]);
     110          60 :     rnorm += aux*aux;
     111             :   }
     112           4 :   PetscCall(DSRestoreArray(ds,DS_MAT_U,&U));
     113           4 :   rnorm = PetscSqrtReal(rnorm);
     114           4 :   PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Norm of 1st U vector = %.3f\n",(double)rnorm));
     115             : 
     116           4 :   PetscCall(PetscFree(w));
     117           4 :   PetscCall(DSDestroy(&ds));
     118           4 :   PetscCall(SlepcFinalize());
     119             :   return 0;
     120             : }
     121             : 
     122             : /*TEST
     123             : 
     124             :    test:
     125             :       args: -ds_method {{0 1}}
     126             :       suffix: 1
     127             :       filter: grep -v "solving the problem"
     128             :       requires: !single
     129             : 
     130             :    test:
     131             :       suffix: 2
     132             :       args: -extrarow -ds_method {{0 1}}
     133             :       filter: grep -v "solving the problem"
     134             :       requires: !single
     135             : 
     136             : TEST*/