Actual source code: svdlapack.c

slepc-3.7.0 2016-05-16
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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) 2002-2016, 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:   if (svd->stop!=SVD_STOP_BASIC) SETERRQ(PetscObjectComm((PetscObject)svd),PETSC_ERR_SUP,"User-defined stopping test not supported in this solver");
 38:   svd->max_it = 1;
 39:   svd->leftbasis = PETSC_TRUE;
 40:   SVDAllocateSolution(svd,0);
 41:   DSSetType(svd->ds,DSSVD);
 42:   DSAllocate(svd->ds,PetscMax(M,N));
 43:   return(0);
 44: }

 48: PetscErrorCode SVDSolve_LAPACK(SVD svd)
 49: {
 51:   PetscInt       M,N,n,i,j,k,ld;
 52:   Mat            mat;
 53:   Vec            u,v;
 54:   PetscScalar    *pU,*pVT,*pmat,*pu,*pv,*A,*w;

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

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

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

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

104:   MatDestroy(&mat);
105:   PetscFree(w);
106:   return(0);
107: }

111: PETSC_EXTERN PetscErrorCode SVDCreate_LAPACK(SVD svd)
112: {
114:   svd->ops->setup   = SVDSetUp_LAPACK;
115:   svd->ops->solve   = SVDSolve_LAPACK;
116:   return(0);
117: }