Actual source code: test8.c

slepc-3.11.2 2019-07-30
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  1: /*
  2:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  3:    SLEPc - Scalable Library for Eigenvalue Problem Computations
  4:    Copyright (c) 2002-2019, 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 with compact storage.\n\n";

 13: #include <slepcds.h>

 15: int main(int argc,char **argv)
 16: {
 18:   DS             ds;
 19:   SlepcSC        sc;
 20:   PetscReal      *T,sigma;
 21:   PetscScalar    *w;
 22:   PetscInt       i,n=10,m,l=2,k=5,ld;
 23:   PetscViewer    viewer;
 24:   PetscBool      verbose;

 26:   SlepcInitialize(&argc,&argv,(char*)0,help);if (ierr) return ierr;
 27:   PetscOptionsGetInt(NULL,NULL,"-n",&n,NULL);
 28:   m = n;
 29:   PetscPrintf(PETSC_COMM_WORLD,"Solve a Dense System of type SVD with compact storage - dimension %Dx%D.\n",n,m);
 30:   PetscOptionsGetInt(NULL,NULL,"-l",&l,NULL);
 31:   PetscOptionsGetInt(NULL,NULL,"-k",&k,NULL);
 32:   if (l>n || k>n || l>k) SETERRQ(PETSC_COMM_WORLD,1,"Wrong value of dimensions");
 33:   PetscOptionsHasName(NULL,NULL,"-verbose",&verbose);

 35:   /* Create DS object */
 36:   DSCreate(PETSC_COMM_WORLD,&ds);
 37:   DSSetType(ds,DSSVD);
 38:   DSSetFromOptions(ds);
 39:   ld = n+2;  /* test leading dimension larger than n */
 40:   DSAllocate(ds,ld);
 41:   DSSetDimensions(ds,n,m,l,k);
 42:   DSSetCompact(ds,PETSC_TRUE);

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

 51:   /* Fill upper arrow-tridiagonal matrix */
 52:   DSGetArrayReal(ds,DS_MAT_T,&T);
 53:   for (i=0;i<n;i++) T[i] = (PetscReal)(i+1);
 54:   for (i=l;i<n-1;i++) T[i+ld] = 1.0;
 55:   DSRestoreArrayReal(ds,DS_MAT_T,&T);
 56:   if (l==0 && k==0) {
 57:     DSSetState(ds,DS_STATE_INTERMEDIATE);
 58:   } else {
 59:     DSSetState(ds,DS_STATE_RAW);
 60:   }
 61:   PetscPrintf(PETSC_COMM_WORLD,"Initial - - - - - - - - -\n");
 62:   DSView(ds,viewer);

 64:   /* Solve */
 65:   PetscMalloc1(n,&w);
 66:   DSGetSlepcSC(ds,&sc);
 67:   sc->comparison    = SlepcCompareLargestReal;
 68:   sc->comparisonctx = NULL;
 69:   sc->map           = NULL;
 70:   sc->mapobj        = NULL;
 71:   DSSolve(ds,w,NULL);
 72:   DSSort(ds,w,NULL,NULL,NULL,NULL);
 73:   if (verbose) {
 74:     PetscPrintf(PETSC_COMM_WORLD,"After solve - - - - - - - - -\n");
 75:     DSView(ds,viewer);
 76:   }

 78:   /* Print singular values */
 79:   PetscPrintf(PETSC_COMM_WORLD,"Computed singular values =\n");
 80:   for (i=0;i<n;i++) {
 81:     sigma = PetscRealPart(w[i]);
 82:     PetscViewerASCIIPrintf(viewer,"  %.5f\n",(double)sigma);
 83:   }
 84:   PetscFree(w);
 85:   DSDestroy(&ds);
 86:   SlepcFinalize();
 87:   return ierr;
 88: }

 90: /*TEST

 92:    test:
 93:       suffix: 1
 94:       requires: !single

 96: TEST*/