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working on tensor

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This commit is contained in:
Jiri Pittner 2024-05-17 17:16:26 +02:00
parent 052c30fd9d
commit 7a0b49c2b8
2 changed files with 15 additions and 14 deletions
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9
tensor.cc
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@ -1024,15 +1024,6 @@ return r;
}
//outer product, rhs indices will be the less significant than this
template<typename T>
Tensor<T> Tensor<T>::operator*(const Tensor &rhs) const
{
Tensor<T> r(rhs.shape.concat(shape));
r.data= data.otimes2vec(rhs.data);
return r;
}
template class Tensor<double>;

20
tensor.h
View File

@ -36,9 +36,12 @@
#include "smat.h"
#include "miscfunc.h"
//@@@permutation of individual indices??? how to treat the symmetry groups
//@@@todo - index names and contraction by named index list
//@@@contraction inside one tensor
//@@@contraction inside one tensor - compute resulting shape, loopover the shape, create index into the original tensor + loop over the contr. index, do the summation, store result
//@@@ will need to store vector of INDEX to the original tensor for the result's flatindex
//@@@ will not be particularly efficient
//
//@@@permutation of individual indices - chech the indices in sym groups remain adjacent, calculate result's shape, loopover the result and permute using unwind_callback
//@@@todo - implement index names - flat vector of names, and contraction by named index list
namespace LA {
@ -62,6 +65,12 @@ public:
typedef int LA_index;
typedef int LA_largeindex;
//indexname must not be an array due to its use as a return value in NRVec functions
#define N_INDEXNAME 8
struct INDEXNAME {
char name[N_INDEXNAME];
};
typedef class indexgroup {
public:
int number; //number of indices
@ -109,7 +118,6 @@ int index;
typedef NRVec<INDEX> INDEXLIST; //collection of several indices
int flatposition(const INDEX &i, const NRVec<indexgroup> &shape); //position of that index in FLATINDEX
int flatposition(const INDEX &i, const NRVec<indexgroup> &shape);
FLATINDEX superindex2flat(const SUPERINDEX &I);
@ -119,6 +127,7 @@ public:
NRVec<indexgroup> shape;
NRVec<T> data;
int myrank;
//@@@??? NRVec<INDEXNAME> names;
NRVec<LA_largeindex> groupsizes; //group sizes of symmetry index groups (a function of shape but precomputed for efficiency)
NRVec<LA_largeindex> cumsizes; //cumulative sizes of symmetry index groups (a function of shape but precomputed for efficiency); always cumsizes[0]=1, index group 0 is the innermost-loop one
@ -131,6 +140,7 @@ public:
//constructors
Tensor() : myrank(0) {};
Tensor(const NRVec<indexgroup> &s) : shape(s) { data.resize(calcsize()); calcrank();}; //general tensor
Tensor(const NRVec<indexgroup> &s, const NRVec<T> &mydata) : shape(s) { LA_largeindex dsize=calcsize(); calcrank(); if(mydata.size()!=dsize) laerror("inconsistent data size with shape"); data=mydata;}
Tensor(const indexgroup &g) {shape.resize(1); shape[0]=g; data.resize(calcsize()); calcrank();}; //tensor with a single index group
Tensor(const Tensor &rhs): myrank(rhs.myrank), shape(rhs.shape), groupsizes(rhs.groupsizes), cumsizes(rhs.cumsizes), data(rhs.data) {};
Tensor(int xrank, const NRVec<indexgroup> &xshape, const NRVec<LA_largeindex> &xgroupsizes, const NRVec<LA_largeindex> xcumsizes, const NRVec<T> &xdata) : myrank(xrank), shape(xshape), groupsizes(xgroupsizes), cumsizes(xcumsizes), data(xdata) {};
@ -159,7 +169,7 @@ public:
inline Tensor& operator/=(const T &a) {data/=a; return *this;};
inline Tensor operator/(const T &a) const {Tensor r(*this); r /=a; return r;};
Tensor operator*(const Tensor &rhs) const; //outer product
inline Tensor operator*(const Tensor &rhs) const {return Tensor(rhs.shape.concat(shape),data.otimes2vec(rhs.data));} //outer product, rhs indices will be the less significant
Tensor& conjugateme() {data.conjugateme(); return *this;};
inline Tensor conjugate() const {Tensor r(*this); r.conjugateme(); return r;};