104 lines
2.6 KiB
C++
104 lines
2.6 KiB
C++
/*
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LA: linear algebra C++ interface library
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Copyright (C) 2024 Jiri Pittner <jiri.pittner@jh-inst.cas.cz> or <jiri@pittnerovi.com>
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This program is free software: you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation, either version 3 of the License, or
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(at your option) any later version.
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This program is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with this program. If not, see <http://www.gnu.org/licenses/>.
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*/
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//a simple tensor class with arbitrary summetry of index subgroups
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//stored in an efficient way
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//presently only a rudimentary implementation
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//presently limited to 2G data size due to NRVec - maybe use a typedef LA_index
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//to uint64_t in the future in vector and matrix classes
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#ifndef _TENSOR_H
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#define _TENSOR_H
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#include <stdint.h>
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#include "vec.h"
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#include "miscfunc.h"
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namespace LA {
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typedef int LA_index;
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typedef int LA_largeindex;
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typedef class indexgroup {
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int number; //number of indices
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int symmetry; //-1 0 or 1
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LA_index offset; //indices start at
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LA_index size; //indices span this range
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} INDEXGROUP;
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template<typename T>
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class Tensor {
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NRVec<indexgroup> shape;
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NRVec<T> data;
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public:
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Tensor() {};
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Tensor(const NRVec<indexgroup> &s) : shape(s), data((int)size()) {data.clear();};
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int rank() const; //is computed from shape
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LA_largeindex size() const; //expensive, is computed from shape
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void copyonwrite() {shape.copyonwrite(); data.copyonwrite();};
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//@@@operator() lhs and rhs both via vararg a via superindex of flat and nested types, get/put to file, stream i/o
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};
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template<typename T>
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int Tensor<T>:: rank() const
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{
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int r=0;
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for(int i=0; i<shape.size(); ++i)
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{
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if(shape[i].number==0) laerror("empty index group");
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r+=shape[i].number;
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}
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return r;
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}
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template<typename T>
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LA_largeindex Tensor<T>::size() const
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{
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LA_largeindex s=1;
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for(int i=0; i<shape.size(); ++i)
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{
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if(shape[i].number==0) laerror("empty index group");
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if(shape[i].size==0) return 0;
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switch(shape[i].symmetry)
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{
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case 0:
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s *= longpow(shape[i].size,shape[i].number);
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break;
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case 1:
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s *= binom(shape[i].size+shape[i].number-1,shape[i].number);
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break;
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case -1:
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s *= binom(shape[i].size,shape[i].number);
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break;
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default:
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laerror("illegal index group symmetry");
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break;
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}
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}
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return s;
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}
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}//namespace
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#endif
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