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working on tensor

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Jiri Pittner
2024-04-05 15:25:05 +02:00
parent 87dd0c5b65
commit 2b20bff532
3 changed files with 54 additions and 15 deletions
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40
tensor.cc
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@@ -83,7 +83,7 @@ switch(I.size()) //a few special cases for efficiency
//compressed storage case
NRVec<LA_index> II(I);
II.copyonwrite();
II -= g.offset;
if(g.offset!=0) II -= g.offset;
int parity=netsort(II.size(),&II[0]);
if(g.symmetry<0 && (parity&1)) *sign= -1;
if(g.symmetry<0) //antisymmetric
@@ -137,7 +137,7 @@ for(int g=0; g<shape.size(); ++g) //loop over index groups
{
int gsign;
LA_largeindex groupindex = subindex(&gsign,shape[g],I[g]);
std::cout <<"INDEX TEST group "<<g<<" cumsizes "<< cumsizes[g]<<" groupindex "<<groupindex<<std::endl;
//std::cout <<"INDEX TEST group "<<g<<" cumsizes "<< cumsizes[g]<<" groupindex "<<groupindex<<std::endl;
*sign *= gsign;
if(groupindex == -1) return -1;
r += groupindex * cumsizes[g];
@@ -145,16 +145,45 @@ for(int g=0; g<shape.size(); ++g) //loop over index groups
return r;
}
//@@@@todo flatindex
template<typename T>
LA_largeindex Tensor<T>::index(int *sign, const FLATINDEX &I) const
{
#ifdef DEBUG
if(rank()!=I.size()) laerror("tensor rank mismatch in index");
#endif
LA_largeindex r=0;
*sign=1;
int gstart=0;
for(int g=0; g<shape.size(); ++g) //loop over index groups
{
int gsign;
int gend= gstart+shape[g].number-1;
NRVec<LA_index> subI = I.subvector(gstart,gend);
gstart=gend+1;
LA_largeindex groupindex = subindex(&gsign,shape[g],subI);
//std::cout <<"FLATINDEX TEST group "<<g<<" cumsizes "<< cumsizes[g]<<" groupindex "<<groupindex<<std::endl;
*sign *= gsign;
if(groupindex == -1) return -1;
r += groupindex * cumsizes[g];
}
return r;
}
//@@@@todo vindex
template<typename T>
LA_largeindex Tensor<T>::vindex(int *sign, int i1, va_list args) const
LA_largeindex Tensor<T>::vindex(int *sign, LA_index i1, va_list args) const
{
NRVec<LA_index> I(rank());
I[0]=i1;
for(int i=1; i<rank(); ++i)
{
I[i] = va_arg(args,LA_index);
}
va_end(args);
return index(sign,I);
}
@@ -172,6 +201,7 @@ template<typename T>
void Tensor<T>::get(int fd)
{
shape.get(fd,true);
myrank=calcrank(); //is not stored but recomputed
cumsizes.get(fd,true);
data.get(fd,true);
}