support for compact SVD

This commit is contained in:
Jiri Pittner 2025-10-21 17:04:59 +02:00
parent 72b8ce30e2
commit 6a3595f03e
2 changed files with 70 additions and 28 deletions

View File

@ -801,11 +801,11 @@ void singular_decomposition(NRMat<double> &a, NRMat<double> *u, NRVec<double> &s
if(m<=0) m=(int)m0;
if(n<=0) n=(int)n0;
if(n>n0 || m>m0) laerror("bad dimension in singular_decomposition");
if (u) if (m > u->nrows() || m> u->ncols())
if (u) if (m > u->nrows() || s.size()> u->ncols())
laerror("inconsistent dimension of U Mat in singular_decomposition()");
if (s.size() < m && s.size() < n)
laerror("inconsistent dimension of S Vec in singular_decomposition()");
if (v) if (n > v->nrows() || n > v->ncols())
if (v) if (s.size() > v->nrows() || n > v->ncols())
laerror("inconsistent dimension of V Mat in singular_decomposition()");
a.copyonwrite();
@ -815,31 +815,31 @@ void singular_decomposition(NRMat<double> &a, NRMat<double> *u, NRVec<double> &s
// C-order (transposed) input and swap u,v matrices,
// v should be transposed at the end
char jobu = u ? 'A' : 'N';
char jobv = v ? 'A' : 'N';
char jobu = u ? (u->nrows()==u->ncols() ? 'A' : 'S') : 'N';
char jobv = v ? (v->nrows()==v->ncols() ? 'A' : 'S') : 'N';
double work0;
FINT lwork = -1;
FINT r;
FINT lda=a.ncols();
FINT ldu= u ? u->ncols():0;
FINT ldv= v ? v->ncols():0;
#ifdef FORINT
FINT ntmp = n;
FINT mtmp = m;
FORNAME(dgesvd)(&jobv, &jobu, &ntmp, &mtmp, a, &n0, s, v?(*v)[0]:0, &n0,
u?(*u)[0]:0, &m0, &work0, &lwork, &r);
FORNAME(dgesvd)(&jobv, &jobu, &ntmp, &mtmp, a, &lda, s, v?(*v)[0]:0, &ldv, u?(*u)[0]:0, &ldu, &work0, &lwork, &r);
#else
FORNAME(dgesvd)(&jobv, &jobu, &n, &m, a, &n0, s, v?(*v)[0]:0, &n0,
u?(*u)[0]:0, &m0, &work0, &lwork, &r);
FORNAME(dgesvd)(&jobv, &jobu, &n, &m, a, &lda, s, v?(*v)[0]:0, &ldv, u?(*u)[0]:0, &ldu, &work0, &lwork, &r);
#endif
lwork = (FINT) work0;
double *work = new double[lwork];
#ifdef FORINT
FORNAME(dgesvd)(&jobv, &jobu, &ntmp, &mtmp, a, &n0, s, v?(*v)[0]:0, &n0,
u?(*u)[0]:0, &m0, work, &lwork, &r);
FORNAME(dgesvd)(&jobv, &jobu, &ntmp, &mtmp, a, &lda, s, v?(*v)[0]:0, &ldv, u?(*u)[0]:0, &ldu, work, &lwork, &r);
#else
FORNAME(dgesvd)(&jobv, &jobu, &n, &m, a, &n0, s, v?(*v)[0]:0, &n0,
u?(*u)[0]:0, &m0, work, &lwork, &r);
FORNAME(dgesvd)(&jobv, &jobu, &n, &m, a, &lda, s, v?(*v)[0]:0, &ldv, u?(*u)[0]:0, &ldu, work, &lwork, &r);
#endif
delete[] work;
@ -866,11 +866,11 @@ void singular_decomposition(NRMat<std::complex<double> > &a, NRMat<std::complex<
if(m<=0) m=(int)m0;
if(n<=0) n=(int)n0;
if(n>n0 || m>m0) laerror("bad dimension in singular_decomposition");
if (u) if (m > u->nrows() || m> u->ncols())
if (u) if (m > u->nrows() || s.size()> u->ncols())
laerror("inconsistent dimension of U Mat in singular_decomposition()");
if (s.size() < m && s.size() < n)
laerror("inconsistent dimension of S Vec in singular_decomposition()");
if (v) if (n > v->nrows() || n > v->ncols())
if (v) if (s.size() > v->nrows() || n > v->ncols())
laerror("inconsistent dimension of V Mat in singular_decomposition()");
int nmin = n<m?n:m;
@ -881,32 +881,32 @@ void singular_decomposition(NRMat<std::complex<double> > &a, NRMat<std::complex<
// C-order (transposed) input and swap u,v matrices,
// v should be transposed at the end
char jobu = u ? 'A' : 'N';
char jobv = v ? 'A' : 'N';
char jobu = u ? (u->nrows()==u->ncols() ? 'A' : 'S') : 'N';
char jobv = v ? (v->nrows()==v->ncols() ? 'A' : 'S') : 'N';
std::complex<double> work0;
FINT lwork = -1;
FINT r;
double *rwork = new double[5*nmin];
FINT lda=a.ncols();
FINT ldu= u ? u->ncols():0;
FINT ldv= v ? v->ncols():0;
#ifdef FORINT
FINT ntmp = n;
FINT mtmp = m;
FORNAME(zgesvd)(&jobv, &jobu, &ntmp, &mtmp, a, &n0, s, v?(*v)[0]:0, &n0,
u?(*u)[0]:0, &m0, &work0, &lwork, rwork, &r);
FORNAME(zgesvd)(&jobv, &jobu, &ntmp, &mtmp, a, &lda, s, v?(*v)[0]:0, &ldv, u?(*u)[0]:0, &ldu, &work0, &lwork, rwork, &r);
#else
FORNAME(zgesvd)(&jobv, &jobu, &n, &m, a, &n0, s, v?(*v)[0]:0, &n0,
u?(*u)[0]:0, &m0, &work0, &lwork, rwork, &r);
FORNAME(zgesvd)(&jobv, &jobu, &n, &m, a, &lda, s, v?(*v)[0]:0, &ldv, u?(*u)[0]:0, &ldu, &work0, &lwork, rwork, &r);
#endif
lwork = (FINT) work0.real();
std::complex<double> *work = new std::complex<double>[lwork];
#ifdef FORINT
FORNAME(zgesvd)(&jobv, &jobu, &ntmp, &mtmp, a, &n0, s, v?(*v)[0]:0, &n0,
u?(*u)[0]:0, &m0, work, &lwork, rwork, &r);
FORNAME(zgesvd)(&jobv, &jobu, &ntmp, &mtmp, a, &lda, s, v?(*v)[0]:0, &ldv, u?(*u)[0]:0, &ldu, work, &lwork, rwork, &r);
#else
FORNAME(zgesvd)(&jobv, &jobu, &n, &m, a, &n0, s, v?(*v)[0]:0, &n0,
u?(*u)[0]:0, &m0, work, &lwork, rwork, &r);
FORNAME(zgesvd)(&jobv, &jobu, &n, &m, a, &lda, s, v?(*v)[0]:0, &ldv, u?(*u)[0]:0, &ldu, work, &lwork, rwork, &r);
#endif
delete[] work;

50
t.cc
View File

@ -463,11 +463,11 @@ NRMat<double> u(a.nrows(),a.nrows()),v(a.ncols(),a.ncols());
NRVec<double>s(a.ncols()<a.nrows()?a.ncols():a.nrows());
singular_decomposition(a,&u,s,&v,0);
cout <<u;
NRMat<double> sdiag(0., u.ncols(),v.nrows());
sdiag.diagonalset(s);
cout <<sdiag;
cout <<s;
cout <<v;
NRMat<double> sdiag(0., u.ncols(),v.nrows()); sdiag.diagonalset(s);
cout << "Error "<<(u*sdiag*v-abak).norm()<<endl;
NRMat<double> ai=calcinverse(abak2);
cout <<"regular inverse "<<ai;
NRVec<double>ss(s);ss.copyonwrite();
@ -3481,7 +3481,7 @@ v.printsorted(cout,1,false);
}
if(1)
if(0)
{
//grassmann product of n identical rank=2 tensors in m-dim space
int n,m;
@ -3498,6 +3498,29 @@ x.randomize(1);
cout <<x;
int sign;
for(int j=0; j<m; ++j)
for(int i=0; i<m; ++i)
{
FLATINDEX I(2);
I[0]=i; I[1]=j;
cout <<" test "<<i<<" "<<j<<" "<<x.index(&sign,I)<<endl;
}
NRMat<double> xm=x.matrix();
cout <<xm;
Tensor<double> xu=x.unwind_index(0,0);
NRMat<double> xum=xu.matrix();
cout <<xum;
Tensor<double> xut=x.unwind_index(0,1);
NRMat<double> xutm=xut.matrix();
cout <<xutm;
if((xum-xutm.transpose()).norm()>1e-14) laerror("error in unwinding");
//generate antisymmetrizer of even indices, with identity on odd indices
NRVec<NRVec_from1<int> > indexclasses(1);
indexclasses[0].resize(n);
@ -3534,5 +3557,24 @@ y.apply_permutation_algebra(rhsvec,b,false,1.,0.);
cout <<y;
}
if(1)
{
//compact SVD
NRMat<double> a;
cin >>a ;
NRMat<double> abak=a;
NRMat<double> abak2=a;
int min = a.ncols()<a.nrows()?a.ncols():a.nrows();
NRMat<double> u(a.nrows(),min),vt(min,a.ncols());
NRVec<double>s(min);
singular_decomposition(a,&u,s,&vt,0);
cout <<u;
cout <<s;
cout <<vt;
NRMat<double> sdiag(0., u.ncols(),vt.nrows()); sdiag.diagonalset(s);
cout << "Error "<<(u*sdiag*vt-abak).norm()<<endl;
}
}//main