Date: 2023-09-05T10:19:02+00:00

Actual source code: test7.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 DSSVD.\n\n";

     13: #include <slepcds.h>

     15: int main(int argc,char **argv)
     16: {
     17:   DS             ds;
     18:   SlepcSC        sc;
     19:   PetscReal      sigma,rnorm,aux;
     20:   PetscScalar    *A,*U,*w,d;
     21:   PetscInt       i,j,k,n=15,m=10,m1,ld;
     22:   PetscViewer    viewer;
     23:   PetscBool      verbose,extrarow;

     25:   PetscFunctionBeginUser;
     26:   PetscCall(SlepcInitialize(&argc,&argv,(char*)0,help));
     27:   PetscCall(PetscOptionsGetInt(NULL,NULL,"-n",&n,NULL));
     28:   PetscCall(PetscOptionsGetInt(NULL,NULL,"-m",&m,NULL));
     29:   k = PetscMin(n,m);
     30:   PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Solve a Dense System of type SVD - dimension %" PetscInt_FMT "x%" PetscInt_FMT ".\n",n,m));
     31:   PetscCall(PetscOptionsHasName(NULL,NULL,"-verbose",&verbose));
     32:   PetscCall(PetscOptionsHasName(NULL,NULL,"-extrarow",&extrarow));

     34:   /* Create DS object */
     35:   PetscCall(DSCreate(PETSC_COMM_WORLD,&ds));
     36:   PetscCall(DSSetType(ds,DSSVD));
     37:   PetscCall(DSSetFromOptions(ds));
     38:   ld = PetscMax(n,m)+2;  /* test leading dimension larger than n */
     39:   PetscCall(DSAllocate(ds,ld));
     40:   PetscCall(DSSetDimensions(ds,n,0,0));
     41:   PetscCall(DSSVDSetDimensions(ds,m));
     42:   PetscCall(DSSVDGetDimensions(ds,&m1));
     43:   PetscCheck(m1==m,PETSC_COMM_WORLD,PETSC_ERR_PLIB,"Inconsistent dimension value");
     44:   PetscCall(DSSetExtraRow(ds,extrarow));

     46:   /* Set up viewer */
     47:   PetscCall(PetscViewerASCIIGetStdout(PETSC_COMM_WORLD,&viewer));
     48:   PetscCall(PetscViewerPushFormat(viewer,PETSC_VIEWER_ASCII_INFO_DETAIL));
     49:   PetscCall(DSView(ds,viewer));
     50:   PetscCall(PetscViewerPopFormat(viewer));

     52:   /* Fill with a rectangular Toeplitz matrix */
     53:   PetscCall(DSGetArray(ds,DS_MAT_A,&A));
     54:   for (i=0;i<k;i++) A[i+i*ld]=1.0;
     55:   for (j=1;j<3;j++) {
     56:     for (i=0;i<m-j;i++) { if ((i+j)<m) A[i+(i+j)*ld]=(PetscScalar)(j+1); }
     57:   }
     58:   for (j=1;j<n/2;j++) {
     59:     for (i=0;i<n-j;i++) { if ((i+j)<n && i<m) A[(i+j)+i*ld]=-1.0; }
     60:   }
     61:   if (extrarow) { A[n-2+m*ld]=1.0; A[n-1+m*ld]=1.0; }  /* really an extra column */
     62:   PetscCall(DSRestoreArray(ds,DS_MAT_A,&A));
     63:   PetscCall(DSSetState(ds,DS_STATE_RAW));
     64:   if (verbose) {
     65:     PetscCall(PetscViewerPushFormat(viewer,PETSC_VIEWER_ASCII_MATLAB));
     66:     PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Initial - - - - - - - - -\n"));
     67:   }
     68:   PetscCall(DSView(ds,viewer));

     70:   /* Solve */
     71:   PetscCall(PetscMalloc1(k,&w));
     72:   PetscCall(DSGetSlepcSC(ds,&sc));
     73:   sc->comparison    = SlepcCompareLargestReal;
     74:   sc->comparisonctx = NULL;
     75:   sc->map           = NULL;
     76:   sc->mapobj        = NULL;
     77:   PetscCall(DSSolve(ds,w,NULL));
     78:   PetscCall(DSSort(ds,w,NULL,NULL,NULL,NULL));
     79:   if (extrarow) PetscCall(DSUpdateExtraRow(ds));
     80:   if (verbose) {
     81:     PetscCall(PetscPrintf(PETSC_COMM_WORLD,"After solve - - - - - - - - -\n"));
     82:     PetscCall(DSView(ds,viewer));
     83:   }

     85:   /* Print singular values */
     86:   PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Computed singular values =\n"));
     87:   for (i=0;i<k;i++) {
     88:     sigma = PetscRealPart(w[i]);
     89:     PetscCall(PetscViewerASCIIPrintf(viewer,"  %.5f\n",(double)sigma));
     90:   }

     92:   if (extrarow) {
     93:     /* Check that extra column is correct */
     94:     PetscCall(DSGetArray(ds,DS_MAT_A,&A));
     95:     PetscCall(DSGetArray(ds,DS_MAT_U,&U));
     96:     d = 0.0;
     97:     for (i=0;i<n;i++) d += A[i+m*ld]-U[n-2+i*ld]-U[n-1+i*ld];
     98:     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:     PetscCall(DSRestoreArray(ds,DS_MAT_A,&A));
    100:     PetscCall(DSRestoreArray(ds,DS_MAT_U,&U));
    101:   }

    103:   /* Singular vectors */
    104:   PetscCall(DSVectors(ds,DS_MAT_U,NULL,NULL));  /* all singular vectors */
    105:   j = 0;
    106:   rnorm = 0.0;
    107:   PetscCall(DSGetArray(ds,DS_MAT_U,&U));
    108:   for (i=0;i<n;i++) {
    109:     aux = PetscAbsScalar(U[i+j*ld]);
    110:     rnorm += aux*aux;
    111:   }
    112:   PetscCall(DSRestoreArray(ds,DS_MAT_U,&U));
    113:   rnorm = PetscSqrtReal(rnorm);
    114:   PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Norm of 1st U vector = %.3f\n",(double)rnorm));

    116:   PetscCall(PetscFree(w));
    117:   PetscCall(DSDestroy(&ds));
    118:   PetscCall(SlepcFinalize());
    119:   return 0;
    120: }

    122: /*TEST

    124:    test:
    125:       suffix: 1
    126:       requires: !single

    128:    test:
    129:       suffix: 2
    130:       args: -extrarow
    131:       requires: !single

    133: TEST*/