Actual source code: svdlapack.c

slepc-3.6.1 2015-09-03
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  1: /*
  2:    This file implements a wrapper to the LAPACK SVD subroutines.

  4:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  5:    SLEPc - Scalable Library for Eigenvalue Problem Computations
  6:    Copyright (c) 2002-2015, Universitat Politecnica de Valencia, Spain

  8:    This file is part of SLEPc.

 10:    SLEPc is free software: you can redistribute it and/or modify it under  the
 11:    terms of version 3 of the GNU Lesser General Public License as published by
 12:    the Free Software Foundation.

 14:    SLEPc  is  distributed in the hope that it will be useful, but WITHOUT  ANY
 15:    WARRANTY;  without even the implied warranty of MERCHANTABILITY or  FITNESS
 16:    FOR  A  PARTICULAR PURPOSE. See the GNU Lesser General Public  License  for
 17:    more details.

 19:    You  should have received a copy of the GNU Lesser General  Public  License
 20:    along with SLEPc. If not, see <http://www.gnu.org/licenses/>.
 21:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
 22: */

 24: #include <slepc/private/svdimpl.h>

 28: PetscErrorCode SVDSetUp_LAPACK(SVD svd)
 29: {
 31:   PetscInt       M,N;

 34:   SVDMatGetSize(svd,&M,&N);
 35:   svd->ncv = N;
 36:   if (svd->mpd) { PetscInfo(svd,"Warning: parameter mpd ignored\n"); }
 37:   svd->max_it = 1;
 38:   svd->leftbasis = PETSC_TRUE;
 39:   SVDAllocateSolution(svd,0);
 40:   DSSetType(svd->ds,DSSVD);
 41:   DSAllocate(svd->ds,PetscMax(M,N));
 42:   return(0);
 43: }

 47: PetscErrorCode SVDSolve_LAPACK(SVD svd)
 48: {
 50:   PetscInt       M,N,n,i,j,k,ld;
 51:   Mat            mat;
 52:   Vec            u,v;
 53:   PetscScalar    *pU,*pVT,*pmat,*pu,*pv,*A,*w;

 56:   DSGetLeadingDimension(svd->ds,&ld);
 57:   MatConvert(svd->OP,MATSEQDENSE,MAT_INITIAL_MATRIX,&mat);
 58:   MatGetSize(mat,&M,&N);
 59:   DSSetDimensions(svd->ds,M,N,0,0);
 60:   MatDenseGetArray(mat,&pmat);
 61:   DSGetArray(svd->ds,DS_MAT_A,&A);
 62:   for (i=0;i<M;i++)
 63:     for (j=0;j<N;j++)
 64:       A[i+j*ld] = pmat[i+j*M];
 65:   DSRestoreArray(svd->ds,DS_MAT_A,&A);
 66:   MatDenseRestoreArray(mat,&pmat);
 67:   DSSetState(svd->ds,DS_STATE_RAW);

 69:   n = PetscMin(M,N);
 70:   PetscMalloc1(n,&w);
 71:   DSSolve(svd->ds,w,NULL);
 72:   DSSort(svd->ds,w,NULL,NULL,NULL,NULL);

 74:   /* copy singular vectors */
 75:   DSGetArray(svd->ds,DS_MAT_U,&pU);
 76:   DSGetArray(svd->ds,DS_MAT_VT,&pVT);
 77:   for (i=0;i<n;i++) {
 78:     if (svd->which == SVD_SMALLEST) k = n - i - 1;
 79:     else k = i;
 80:     svd->sigma[k] = PetscRealPart(w[i]);
 81:     BVGetColumn(svd->U,k,&u);
 82:     BVGetColumn(svd->V,k,&v);
 83:     VecGetArray(u,&pu);
 84:     VecGetArray(v,&pv);
 85:     if (M>=N) {
 86:       for (j=0;j<M;j++) pu[j] = pU[i*ld+j];
 87:       for (j=0;j<N;j++) pv[j] = PetscConj(pVT[j*ld+i]);
 88:     } else {
 89:       for (j=0;j<N;j++) pu[j] = PetscConj(pVT[j*ld+i]);
 90:       for (j=0;j<M;j++) pv[j] = pU[i*ld+j];
 91:     }
 92:     VecRestoreArray(u,&pu);
 93:     VecRestoreArray(v,&pv);
 94:     BVRestoreColumn(svd->U,k,&u);
 95:     BVRestoreColumn(svd->V,k,&v);
 96:   }
 97:   DSRestoreArray(svd->ds,DS_MAT_U,&pU);
 98:   DSRestoreArray(svd->ds,DS_MAT_VT,&pVT);

100:   svd->nconv = n;
101:   svd->reason = SVD_CONVERGED_TOL;

103:   MatDestroy(&mat);
104:   PetscFree(w);
105:   return(0);
106: }

110: PETSC_EXTERN PetscErrorCode SVDCreate_LAPACK(SVD svd)
111: {
113:   svd->ops->setup   = SVDSetUp_LAPACK;
114:   svd->ops->solve   = SVDSolve_LAPACK;
115:   return(0);
116: }