/* LA: linear algebra C++ interface library Copyright (C) 2024 Jiri Pittner or This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see . */ //a simple tensor class with arbitrary symmetry of index subgroups //stored in an efficient way //presently only a rudimentary implementation //presently limited to 2G data size due to NRVec - maybe use a typedef LA_index //to uint64_t in the future in vector and matrix classes #ifndef _TENSOR_H #define _TENSOR_H #include #include #include "vec.h" #include "miscfunc.h" namespace LA { template class Signedpointer { T *ptr; int sgn; public: Signedpointer(T *p, int s) : ptr(p),sgn(s) {}; //dereferencing *ptr should intentionally segfault for sgn==0 T& operator=(const T rhs) {if(sgn>0) *ptr=rhs; else *ptr = -rhs; return *ptr;} T& operator*=(const T rhs) {*ptr *= rhs; return *ptr;} T& operator/=(const T rhs) {*ptr /= rhs; return *ptr;} T& operator+=(const T rhs) {if(sgn>0) *ptr += rhs; else *ptr -= rhs; return *ptr;} T& operator-=(const T rhs) {if(sgn>0) *ptr -= rhs; else *ptr += rhs; return *ptr;} }; typedef int LA_index; typedef int LA_largeindex; typedef class indexgroup { public: int number; //number of indices int symmetry; //-1 0 or 1 #ifdef LA_TENSOR_ZERO_OFFSET static const LA_index offset = 0; //compiler can optimiza away some computations #else LA_index offset; //indices start at a general offset #endif LA_index range; //indices span this range } INDEXGROUP; template<> class LA_traits { public: static bool is_plaindata() {return true;}; static void copyonwrite(indexgroup& x) {}; typedef INDEXGROUP normtype; static inline void put(int fd, const indexgroup &x, bool dimensions=1) {if(sizeof(indexgroup)!=write(fd,&x,sizeof(indexgroup))) laerror("write error 1 in indexgroup put"); } static inline void multiput(int nn, int fd, const indexgroup *x, bool dimensions=1) {if(nn*sizeof(indexgroup)!=write(fd,x,nn*sizeof(indexgroup))) laerror("write error 1 in indexgroup multiiput"); } static inline void get(int fd, indexgroup &x, bool dimensions=1) {if(sizeof(indexgroup)!=read(fd,&x,sizeof(indexgroup))) laerror("read error 1 in indexgroup get");} static inline void multiget(int nn, int fd, indexgroup *x, bool dimensions=1) {if(nn*sizeof(indexgroup)!=read(fd,x,nn*sizeof(indexgroup))) laerror("read error 1 in indexgroup get");} }; typedef NRVec FLATINDEX; //all indices but in a single vector typedef NRVec > SUPERINDEX; //all indices in the INDEXGROUP structure template class Tensor { int myrank; NRVec shape; NRVec groupsizes; //group sizes of symmetry index groups (a function of shape but precomputed for efficiency) NRVec cumsizes; //cumulative sizes of symmetry index groups (a function of shape but precomputed for efficiency) NRVec data; private: LA_largeindex index(int *sign, const SUPERINDEX &I) const; //map the tensor indices to the position in data LA_largeindex index(int *sign, const FLATINDEX &I) const; //map the tensor indices to the position in data LA_largeindex vindex(int *sign, LA_index i1, va_list args) const; //map list of indices to the position in data //@@@reversed index public: //constructors Tensor() : myrank(0) {}; Tensor(const NRVec &s) : shape(s), data((int)calcsize()), myrank(calcrank()) {}; //general tensor Tensor(const indexgroup &g) {shape.resize(1); shape[0]=g; data.resize(calcsize()); myrank=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) {}; void clear() {data.clear();}; int rank() const {return myrank;}; int calcrank(); //is computed from shape LA_largeindex calcsize(); //set redundant data and return total size LA_largeindex size() const {return data.size();}; void copyonwrite() {shape.copyonwrite(); data.copyonwrite();}; inline Signedpointer lhs(const SUPERINDEX &I) {int sign; LA_largeindex i=index(&sign,I); return Signedpointer(&data[i],sign);}; inline T operator()(const SUPERINDEX &I) {int sign; LA_largeindex i=index(&sign,I); if(sign==0) return 0; return sign>0 ?data[i] : -data[i];}; inline Signedpointer lhs(const FLATINDEX &I) {int sign; LA_largeindex i=index(&sign,I); return Signedpointer(&data[i],sign);}; inline T operator()(const FLATINDEX &I) {int sign; LA_largeindex i=index(&sign,I); if(sign==0) return 0; return sign>0 ?data[i] : -data[i];}; inline Signedpointer lhs(LA_index i1...) {va_list args; int sign; LA_largeindex i; va_start(args,i1); i= vindex(&sign, i1,args); return Signedpointer(&data[i],sign); }; inline T operator()(LA_index i1...) {va_list args; ; int sign; LA_largeindex i; va_start(args,i1); i= vindex(&sign, i1,args); if(sign==0) return 0; return sign>0 ?data[i] : -data[i];}; inline Tensor& operator=(const Tensor &rhs) {myrank=rhs.myrank; shape=rhs.shape; groupsizes=rhs.groupsizes; cumsizes=rhs.cumsizes; data=rhs.data; return *this;}; inline Tensor& operator*=(const T &a) {data*=a; return *this;}; inline Tensor operator*(const T &a) const {Tensor r(*this); r *=a; return r;}; inline Tensor& operator/=(const T &a) {data/=a; return *this;}; inline Tensor operator/(const T &a) const {Tensor r(*this); r /=a; return r;}; void put(int fd) const; void get(int fd); //@@@TODO - unwinding to full size in a specified index //@@@TODO - contractions - basic and efficient? first contraction in a single index; between a given group+index in group at each tensor //@@@ dvojite rekurzivni loopover s callbackem - nebo iterator s funkci next??? //@@@nebo inverse index function? //@@@ stream i/o na zaklade tohoto //@@@permuteindexgroups //@@@symmetreize a group, antisymmetrize a group, expand a (anti)symmetric grtoup //@@@@@@+= -= + - on same shape }; template int Tensor:: calcrank() { int r=0; for(int i=0; i LA_largeindex Tensor::calcsize() { groupsizes.resize(shape.size()); cumsizes.resize(shape.size()); LA_largeindex s=1; for(int i=0; i