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apply_permutation_algebra for tensors from product rhs

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Jiri Pittner
2025-10-17 15:07:43 +02:00
parent 1dd3905d14
commit 08cdf7c971
3 changed files with 110 additions and 6 deletions
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51
tensor.cc
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@@ -924,6 +924,32 @@ for(int p=0; p<help_pa<T>->size(); ++p)
}
static int help_tn;
template<typename T>
static Tensor<T> *help_tv;
template<typename T>
static void permutationalgebra_callback2(const SUPERINDEX &I, T *v)
{
FLATINDEX J = superindex2flat(I);
for(int p=0; p<help_pa<T>->size(); ++p)
{
FLATINDEX Jp = J.permuted((*help_pa<T>)[p].perm,help_inverse);
T product;
//build product from the vector of tensors using the Jp index
int rankshift=0;
for(int i=0; i<help_tn; ++i)
{
int rank = help_tv<T>[i].rank();
FLATINDEX indi = Jp.subvector(rankshift,rankshift+rank-1);
if(i==0) product= help_tv<T>[i](indi);
else product *= help_tv<T>[i](indi);
rankshift += rank;
}
*v += help_alpha<T> * (*help_pa<T>)[p].weight * product;
}
}
template<typename T>
void Tensor<T>::apply_permutation_algebra(const Tensor<T> &rhs, const PermutationAlgebra<int,T> &pa, bool inverse, T alpha, T beta)
@@ -932,6 +958,8 @@ if(beta!=(T)0) {if(beta!=(T)1) *this *= beta;} else clear();
if(alpha==(T)0) return;
copyonwrite();
if(rank()!=rhs.rank()) laerror("rank mismatch in apply_permutation_algebra");
help_t<T> = const_cast<Tensor<T> *>(&rhs);
help_pa<T> = &pa;
help_inverse = inverse;
@@ -940,6 +968,29 @@ loopover(permutationalgebra_callback);
}
template<typename T>
void Tensor<T>::apply_permutation_algebra(const NRVec<Tensor<T> > &rhsvec, const PermutationAlgebra<int,T> &pa, bool inverse, T alpha, T beta)
{
if(beta!=(T)0) {if(beta!=(T)1) *this *= beta;} else clear();
if(alpha==(T)0) return;
copyonwrite();
int totrank=0;
for(int i=0; i<rhsvec.size(); ++i) totrank+=rhsvec[i].rank();
if(totrank!=rank()) laerror("rank mismatch in apply_permutation_algebra");
help_tv<T> = const_cast<Tensor<T> *>(&rhsvec[0]);
help_tn = rhsvec.size();
help_pa<T> = &pa;
help_inverse = inverse;
help_alpha<T> = alpha;
loopover(permutationalgebra_callback2);
}
template<typename T>
void Tensor<T>::split_index_group(int group)
{