tensor.h

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#pragma once
 
#include "grid.h"
#include "operator.h"
#include "evaluation.h"
#include "evaluationX.h"
#include "dg/functors.h"
#include "dg/blas1.h"
 
namespace dg
{
    //separate algorithms from interface!!
 
template<class container>
struct SparseTensor
{
    using container_type = container;
    SparseTensor( ):m_mat_idx(3,-1) {}
 
    template<class Topology>
    SparseTensor( const Topology& grid){
        construct(grid);
    }
 
    SparseTensor( const container& copyable ){
        construct(copyable);
    }
    template<class Topology>
    void construct( const Topology& grid){
        m_mat_idx.resize(3,0);
        for( int i=0; i<3; i++)
            m_mat_idx( i,i) = 1;
        m_values.resize(2);
        dg::assign( dg::evaluate( dg::zero, grid), m_values[0]);
        dg::assign( dg::evaluate( dg::one, grid), m_values[1]);
    }
    void construct( const container& copyable ){
        m_mat_idx.resize(3,0);
        for( int i=0; i<3; i++)
            m_mat_idx( i,i) = 1;
        m_values.assign(2,copyable);
        dg::blas1::copy( 0., m_values[0]);
        dg::blas1::copy( 1., m_values[1]);
    }
 
    template<class OtherContainer>
    SparseTensor( const SparseTensor<OtherContainer>& src): m_mat_idx(3,-1), m_values(src.values().size()){
        for(unsigned i=0; i<3; i++)
            for(unsigned j=0; j<3; j++)
                m_mat_idx(i,j)=src.idx(i,j);
 
        for( unsigned i=0; i<src.values().size(); i++)
            dg::assign( src.values()[i], m_values[i]);
    }
 
    int idx(unsigned i, unsigned j)const{
        return m_mat_idx(i,j);
    }
    int& idx(unsigned i, unsigned j){
        return m_mat_idx(i,j);
    }
 
    const container& value(size_t i, size_t j)const{
        int k = m_mat_idx(i,j);
        return m_values[k];
    }
    //if you're looking for this function: YOU DON'T NEED IT!! (ALIASING)
    //T& value(size_t i, size_t j);
    std::vector<container>& values() {
        return m_values;
    }
    const std::vector<container>& values()const{
        return m_values;
    }
 
    SparseTensor transpose()const{
        SparseTensor tmp(*this);
        tmp.m_mat_idx = m_mat_idx.transpose();
        return tmp;
    }
 
    private:
    dg::SquareMatrix<int> m_mat_idx;
    std::vector<container> m_values;
};
 
}//namespace dg