jiri/LA_library
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

simplified (inverse)Tucker for non-iverting index order

Browse Source
This commit is contained in:
Jiri Pittner
2025-11-20 16:00:53 +01:00
parent 54642a71cc
commit a342032b58
3 changed files with 55 additions and 22 deletions
Download Patch File Download Diff File Expand all files Collapse all files

40
tensor.cc
View File

@@ -1722,14 +1722,15 @@ if(r==1) //create an analogous output for the trivial case
}
//loop over all indices; relies on the fact that unwinding does not change order of remaining indices
//for inverseorder=false, to avoid inverting order by permute_index_groups we repeatedly unwind the LAST index, and all indices rotate at this position with the first one in the last iteration due to the unwind!
for(int i=0; i<r; ++i)
{
INDEX I=indexposition(i,shape);
INDEX I= inverseorder? indexposition(i,shape) : indexposition(r-1,shape);
NRMat<T> um;
NRVec<INDEXGROUP> ushape;
{
Tensor<T> uu=unwind_index(I);
ushape=uu.shape; //ushape.copyonwrite(); should not be needed
ushape=uu.shape;
um=uu.matrix();
}
int mini=um.nrows(); if(um.ncols()<mini) mini=um.ncols(); //compact SVD, expect descendingly sorted values
@@ -1755,9 +1756,10 @@ for(int i=0; i<r; ++i)
umnew=u.submatrix(0,umnr-1,0,preserve-1);
}
else umnew=u;
ret[(inverseorder? r-i-1 : i)]=vt.transpose(true);
ret[r-i-1]=vt.transpose(true);
umnew.diagmultr(w);
//rebuild tensor of the preserved shape from matrix
ushape.copyonwrite();
ushape[0].range=preserve;
{
NRVec<T> newdata(umnew);
@@ -1766,17 +1768,10 @@ for(int i=0; i<r; ++i)
}
}
if(!is_flat()) laerror("this should not happen");
if(!inverseorder)
{
NRPerm<int> p(r);
for(int i=1; i<=r; ++i) p[r-i+1]=i;
*this = permute_index_groups(p);
}
return ret;
}
template<typename T>
Tensor<T> Tensor<T>::inverseTucker(const NRVec<NRMat<T> > &x, bool inverseorder) const
{
@@ -1784,9 +1779,11 @@ if(rank()!=x.size()) laerror("input of inverseTucker does not match rank");
Tensor<T> tmp(*this);
Tensor<T> r;
if(!is_flat()) laerror("inverseTucker only for flat tensors as produced by Tucker");
if(inverseorder)
{
for(int i=0; i<rank(); ++i)
{
Tensor<T> mat(x[i],true);
Tensor<T> mat(x[i],true); //flat tensor from a matrix
r= tmp.contraction(i,0,mat,0,0,(T)1,false,false);
if(i<rank()-1)
{
@@ -1794,14 +1791,21 @@ for(int i=0; i<rank(); ++i)
r.deallocate();
}
}
if(!inverseorder)
}
else //not inverseroder
{
for(int i=rank()-1; i>=0; --i)
{
NRPerm<int> p(r.rank());
for(int i=1; i<=r.rank(); ++i) p[r.rank()-i+1]=i;
return r.permute_index_groups(p);
Tensor<T> mat(x[i],true); //flat tensor from a matrix
r= tmp.contraction(rank()-1,0,mat,0,0,(T)1,false,false); //the current index will be the last after previous contractions
if(i>0)
{
tmp=r;
r.deallocate();
}
}
else
return r;
}
return r;
}
@@ -2116,7 +2120,7 @@ NRVec<NRVec_from1<int> > antigroups;
parse_antisymmetrizer(antisymmetrizer,antigroups,antinames);
//check the names make sense and fill in the possibly missing ones as separate group
if(antinames.size()>tmpnames.size()) laerror("too many indices in the antisymmetrizet");
if(antinames.size()>tmpnames.size()) laerror("too many indices in the antisymmetrizer");
bitvector isexplicit(tmpnames.size());
isexplicit.clear();
for(int i=0; i<antinames.size(); ++i)