LA_library/tensor.h

214 lines
10 KiB
C++

/*
LA: linear algebra C++ interface library
Copyright (C) 2024 Jiri Pittner <jiri.pittner@jh-inst.cas.cz> or <jiri@pittnerovi.com>
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 <http://www.gnu.org/licenses/>.
*/
//a simple tensor class with arbitrary symmetry of index subgroups
//stored in an efficient way
//each index group has a specific symmetry (nosym,sym,antisym)
//additional symmetry between index groups (like in 2-electron integrals) is not supported directly, you would need to nest the class to Tensor<Tensor<T> >
//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 <stdint.h>
#include <cstdarg>
#include "vec.h"
#include "mat.h"
#include "smat.h"
#include "miscfunc.h"
namespace LA {
template<typename T>
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, later 2 for hermitian and -2 for antihermitian? - would need change in operator() and Signedpointer
#ifdef LA_TENSOR_ZERO_OFFSET
static const LA_index offset = 0; //compiler can optimize away some computations
#else
LA_index offset; //indices start at a general offset
#endif
LA_index range; //indices span this range
bool operator==(const indexgroup &rhs) const {return number==rhs.number && symmetry==rhs.symmetry && offset==rhs.offset && range==rhs.range;};
inline bool operator!=(const indexgroup &rhs) const {return !((*this)==rhs);};
} INDEXGROUP;
std::ostream & operator<<(std::ostream &s, const INDEXGROUP &x);
std::istream & operator>>(std::istream &s, INDEXGROUP &x);
template<>
class LA_traits<indexgroup> {
public:
static bool is_plaindata() {return true;};
static void copyonwrite(indexgroup& x) {};
typedef INDEXGROUP normtype;
static inline int gencmp(const indexgroup *a, const indexgroup *b, int n) {return memcmp(a,b,n*sizeof(indexgroup));};
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<LA_index> FLATINDEX; //all indices but in a single vector
typedef NRVec<NRVec<LA_index> > SUPERINDEX; //all indices in the INDEXGROUP structure
typedef NRVec<LA_largeindex> GROUPINDEX; //set of indices in the symmetry groups
FLATINDEX superindex2flat(const SUPERINDEX &I);
template<typename T>
class Tensor {
public:
NRVec<indexgroup> shape;
NRVec<T> data;
int myrank;
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
public:
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
SUPERINDEX inverse_index(LA_largeindex s) const; //inefficient, but possible if needed
//constructors
Tensor() : myrank(0) {};
Tensor(const NRVec<indexgroup> &s) : shape(s) { data.resize(calcsize()); calcrank();}; //general tensor
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) {};
explicit Tensor(const NRVec<T> &x);
explicit Tensor(const NRMat<T> &x);
explicit Tensor(const NRSMat<T> &x);
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(); groupsizes.copyonwrite(); cumsizes.copyonwrite(); data.copyonwrite();};
void resize(const NRVec<indexgroup> &s) {shape=s; data.resize(calcsize()); calcrank();};
inline Signedpointer<T> lhs(const SUPERINDEX &I) {int sign; LA_largeindex i=index(&sign,I); return Signedpointer<T>(&data[i],sign);};
inline T operator()(const SUPERINDEX &I) const {int sign; LA_largeindex i=index(&sign,I); if(sign==0) return 0; return sign>0 ?data[i] : -data[i];};
inline Signedpointer<T> lhs(const FLATINDEX &I) {int sign; LA_largeindex i=index(&sign,I); return Signedpointer<T>(&data[i],sign);};
inline T operator()(const FLATINDEX &I) const {int sign; LA_largeindex i=index(&sign,I); if(sign==0) return 0; return sign>0 ?data[i] : -data[i];};
inline Signedpointer<T> lhs(LA_index i1...) {va_list args; int sign; LA_largeindex i; va_start(args,i1); i= vindex(&sign, i1,args); return Signedpointer<T>(&data[i],sign); };
inline T operator()(LA_index i1...) const {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;};
Tensor& conjugateme() {data.conjugateme(); return *this;};
inline Tensor conjugate() const {Tensor r(*this); r.conjugateme(); return r;};
inline Tensor& operator+=(const Tensor &rhs)
{
#ifdef DEBUG
if(shape!=rhs.shape) laerror("incompatible tensors for operation");
#endif
data+=rhs.data;
return *this;
}
inline Tensor& operator-=(const Tensor &rhs)
{
#ifdef DEBUG
if(shape!=rhs.shape) laerror("incompatible tensors for operation");
#endif
data-=rhs.data;
return *this;
}
inline Tensor operator+(const Tensor &rhs) const {Tensor r(*this); r+=rhs; return r;};
inline Tensor operator-(const Tensor &rhs) const {Tensor r(*this); r-=rhs; return r;};
Tensor operator-() const {return Tensor(myrank,shape,groupsizes,cumsizes,-data);}; //unary-
void put(int fd) const;
void get(int fd);
inline void randomize(const typename LA_traits<T>::normtype &x) {data.randomize(x);};
void loopover(void (*callback)(const SUPERINDEX &, T *)); //loop over all elements
void grouploopover(void (*callback)(const GROUPINDEX &, T *)); //loop over all elements disregarding the internal structure of index groups
Tensor permute_index_groups(const NRPerm<int> &p) const; //rearrange the tensor storage permuting index groups as a whole
Tensor unwind_index(int group, int index) const; //separate an index from a group and expand it to full range as the least significant one
void addcontraction(const Tensor &rhs1, int group, int index, const Tensor &rhs, int rhsgroup, int rhsindex, T alpha=1, T beta=1, bool doresize=false, bool conjugate=false);
inline Tensor contraction(int group, int index, const Tensor &rhs, int rhsgroup, int rhsindex, T alpha=1, bool conjugate=false) const {Tensor<T> r; r.addcontraction(*this,group,index,rhs,rhsgroup,rhsindex,alpha,0,true, conjugate); return r; }
void apply_permutation_algebra(const Tensor &rhs, const PermutationAlgebra<int,T> &pa, bool inverse=false, T alpha=1, T beta=0); //general (not optimally efficient) symmetrizers, antisymmetrizers etc. acting on the flattened index list:
// this *=beta; for I over this: this(I) += alpha * sum_P c_P rhs(P(I))
// PermutationAlgebra can represent e.g. general_antisymmetrizer in Kucharski-Bartlett notation
void split_index_group(int group); //formal split of a non-symmetric index group WITHOUT the need for data reorganization
void merge_adjacent_index_groups(int groupfrom, int groupto); //formal merge of non-symmetric index groups WITHOUT the need for data reorganization
Tensor merge_index_groups(const NRVec<int> &groups) const;
//TODO perhaps implement application of a permutation algebra to a product of several tensors
};
template <typename T>
std::ostream & operator<<(std::ostream &s, const Tensor<T> &x);
template <typename T>
std::istream & operator>>(std::istream &s, Tensor<T> &x);
}//namespace
#endif