Actual source code: test21.c

      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 DSGSVD.\n\n";

     13: #include <slepcds.h>

     15: int main(int argc,char **argv)
     16: {
     17:   DS             ds;
     18:   SlepcSC        sc;
     19:   Mat            X;
     20:   Vec            x0;
     21:   PetscReal      sigma,rnorm,cond;
     22:   PetscScalar    *A,*B,*w;
     23:   PetscInt       i,j,k,n=15,m=10,p=10,m1,p1,ld;
     24:   PetscViewer    viewer;
     25:   PetscBool      verbose;

     27:   PetscFunctionBeginUser;
     28:   PetscCall(SlepcInitialize(&argc,&argv,NULL,help));
     29:   PetscCall(PetscOptionsGetInt(NULL,NULL,"-n",&n,NULL));
     30:   PetscCall(PetscOptionsGetInt(NULL,NULL,"-m",&m,NULL));
     31:   PetscCall(PetscOptionsGetInt(NULL,NULL,"-p",&p,NULL));
     32:   PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Solve a Dense System of type GSVD - dimension (%" PetscInt_FMT "+%" PetscInt_FMT ")x%" PetscInt_FMT ".\n",n,p,m));
     33:   PetscCall(PetscOptionsHasName(NULL,NULL,"-verbose",&verbose));

     35:   /* Create DS object */
     36:   PetscCall(DSCreate(PETSC_COMM_WORLD,&ds));
     37:   PetscCall(DSSetType(ds,DSGSVD));
     38:   PetscCall(DSSetFromOptions(ds));
     39:   ld   = PetscMax(PetscMax(p,m),n)+2;  /* test leading dimension larger than n */
     40:   PetscCall(DSAllocate(ds,ld));
     41:   PetscCall(DSSetDimensions(ds,n,0,0));
     42:   PetscCall(DSGSVDSetDimensions(ds,m,p));
     43:   PetscCall(DSGSVDGetDimensions(ds,&m1,&p1));
     44:   PetscCheck(m1==m && p1==p,PETSC_COMM_WORLD,PETSC_ERR_PLIB,"Inconsistent dimension values");

     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:   k = PetscMin(n,m);
     53:   /* Fill A with a rectangular Toeplitz matrix */
     54:   PetscCall(DSGetArray(ds,DS_MAT_A,&A));
     55:   for (i=0;i<k;i++) A[i+i*ld]=1.0;
     56:   for (j=1;j<3;j++) {
     57:     for (i=0;i<n-j;i++) {
     58:       if ((i+j)<m) A[i+(i+j)*ld]=(PetscScalar)(j+1);
     59:     }
     60:   }
     61:   for (j=1;j<n/2;j++) {
     62:     for (i=0;i<n-j;i++) {
     63:       if ((i+j)<n && i<m) A[(i+j)+i*ld]=-1.0;
     64:     }
     65:   }
     66:   PetscCall(DSRestoreArray(ds,DS_MAT_A,&A));

     68:   k = PetscMin(p,m);
     69:   /* Fill B with a shifted bidiagonal matrix */
     70:   PetscCall(DSGetArray(ds,DS_MAT_B,&B));
     71:   for (i=m-k;i<m;i++) {
     72:     B[i-m+k+i*ld]=2.0-1.0/(PetscScalar)(i+1);
     73:     if (i) B[i-1-m+k+i*ld]=1.0;
     74:   }
     75:   PetscCall(DSRestoreArray(ds,DS_MAT_B,&B));

     77:   PetscCall(DSSetState(ds,DS_STATE_RAW));
     78:   if (verbose) {
     79:     PetscCall(PetscViewerPushFormat(viewer,PETSC_VIEWER_ASCII_MATLAB));
     80:     PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Initial - - - - - - - - -\n"));
     81:   }
     82:   PetscCall(DSView(ds,viewer));

     84:   /* Condition number */
     85:   PetscCall(DSCond(ds,&cond));
     86:   PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Condition number = %.3f\n",(double)cond));

     88:   /* Solve */
     89:   PetscCall(PetscMalloc1(m,&w));
     90:   PetscCall(DSGetSlepcSC(ds,&sc));
     91:   sc->comparison    = SlepcCompareLargestReal;
     92:   sc->comparisonctx = NULL;
     93:   sc->map           = NULL;
     94:   sc->mapobj        = NULL;
     95:   PetscCall(DSSolve(ds,w,NULL));
     96:   PetscCall(DSSort(ds,w,NULL,NULL,NULL,NULL));
     97:   PetscCall(DSSynchronize(ds,w,NULL));
     98:   if (verbose) {
     99:     PetscCall(PetscPrintf(PETSC_COMM_WORLD,"After solve - - - - - - - - -\n"));
    100:     PetscCall(DSView(ds,viewer));
    101:   }
    102:   /* Print singular values */
    103:   PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Computed singular values =\n"));
    104:   PetscCall(DSGetDimensions(ds,NULL,NULL,NULL,&k));
    105:   for (i=0;i<k;i++) {
    106:     sigma = PetscRealPart(w[i]);
    107:     PetscCall(PetscViewerASCIIPrintf(viewer,"  %g\n",(double)sigma));
    108:   }

    110:   /* Singular vectors */
    111:   PetscCall(DSVectors(ds,DS_MAT_X,NULL,NULL));  /* all singular vectors */
    112:   PetscCall(DSGetMat(ds,DS_MAT_X,&X));
    113:   PetscCall(MatCreateVecs(X,NULL,&x0));
    114:   PetscCall(MatGetColumnVector(X,x0,0));
    115:   PetscCall(VecNorm(x0,NORM_2,&rnorm));
    116:   PetscCall(DSRestoreMat(ds,DS_MAT_X,&X));
    117:   PetscCall(VecDestroy(&x0));
    118:   PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Norm of 1st X vector = %.3f\n",(double)rnorm));

    120:   PetscCall(DSGetMat(ds,DS_MAT_U,&X));
    121:   PetscCall(MatCreateVecs(X,NULL,&x0));
    122:   PetscCall(MatGetColumnVector(X,x0,0));
    123:   PetscCall(VecNorm(x0,NORM_2,&rnorm));
    124:   PetscCall(DSRestoreMat(ds,DS_MAT_U,&X));
    125:   PetscCall(VecDestroy(&x0));
    126:   if (PetscAbs(rnorm-1.0)>10*PETSC_MACHINE_EPSILON) PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Warning: the 1st U vector has norm %g\n",(double)rnorm));

    128:   PetscCall(DSGetMat(ds,DS_MAT_V,&X));
    129:   PetscCall(MatCreateVecs(X,NULL,&x0));
    130:   PetscCall(MatGetColumnVector(X,x0,0));
    131:   PetscCall(VecNorm(x0,NORM_2,&rnorm));
    132:   PetscCall(DSRestoreMat(ds,DS_MAT_V,&X));
    133:   PetscCall(VecDestroy(&x0));
    134:   if (PetscAbs(rnorm-1.0)>10*PETSC_MACHINE_EPSILON) PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Warning: the 1st V vector has norm %g\n",(double)rnorm));

    136:   PetscCall(PetscFree(w));
    137:   PetscCall(DSDestroy(&ds));
    138:   PetscCall(SlepcFinalize());
    139:   return 0;
    140: }

    142: /*TEST

    144:    testset:
    145:       output_file: output/test21_1.out
    146:       requires: !single
    147:       nsize: {{1 2 3}}
    148:       filter: grep -v "parallel operation mode" | grep -v " MPI process"
    149:       test:
    150:          suffix: 1
    151:          args: -ds_parallel redundant
    152:       test:
    153:          suffix: 2
    154:          args: -ds_parallel synchronized

    156: TEST*/