NAME¶

asr - associative sparse matrix (rheolef-6.5)

SYNOPSYS¶

Associative sparse matrix container, used during FEM assembling process.

IMPLEMENTATION NOTE¶

Elements are stored row by row using the pair_set class bqsed on the STL map class. Implementation of asr uses array<pair_set>

IMPLEMENTATION¶

template<class T, class M = rheo_default_memory_model, class A = std::allocator<T> >
class asr : public array<pair_set<T,A>, M, A> {
public:
// typedefs:

    typedef pair_set<T,A>                    row_type;
    typedef array<row_type,M,A>              base;
    typedef typename base::size_type         size_type;
    typedef M                                memory_type;

    struct dis_reference {
      dis_reference (typename base::dis_reference row_dis_i, size_type dis_j)
       : _row_dis_i(row_dis_i), _dis_j(dis_j) {}

      dis_reference& operator+= (const T& value) {
        _row_dis_i += std::pair<size_type,T>(_dis_j,value);
        return *this;
      }
      typename base::dis_reference  _row_dis_i;
      size_type                     _dis_j;
    };

// allocators/deallocators:

    asr (const A& alloc = A())
      : base(distributor(), row_type(alloc), alloc), _col_ownership(), _nnz(0), _dis_nnz(0) {}

    asr (const distributor& row_ownership, const distributor& col_ownership, const A& alloc = A())
      : base(row_ownership, row_type(alloc), alloc), _col_ownership(col_ownership), _nnz(0), _dis_nnz(0) {}

    asr (const csr_rep<T,M>&, const A& alloc = A());
    asr (const csr<T,M>&,     const A& alloc = A());
    void build_from_csr (const csr_rep<T,M>&);

    void resize (const distributor& row_ownership, const distributor& col_ownership)
    {
       base::resize (row_ownership);
       _col_ownership = col_ownership;
       _nnz = _dis_nnz = 0;
    }

// accessors:

    const communicator& comm() const { return base::comm(); }

    size_type nrow () const { return base::size(); }
    size_type ncol () const { return _col_ownership.size(); }
    size_type nnz () const { return _nnz; }

    size_type dis_nrow () const { return base::dis_size(); }
    size_type dis_ncol () const { return _col_ownership.dis_size(); }
    size_type dis_nnz () const  { return _dis_nnz; }
    const distributor& row_ownership() const { return base::ownership(); }
    const distributor& col_ownership() const { return _col_ownership; }

// modifiers:

    T operator()            (size_type     i, size_type dis_j) const;
    T&       semi_dis_entry (size_type     i, size_type dis_j);
    dis_reference dis_entry (size_type dis_i, size_type dis_j);

    // dis_entry_assembly_end is redefined in order to recompute _nnz and _dis_nnz
    void dis_entry_assembly_begin() { base::dis_entry_assembly_begin (pair_set_add_op<row_type>()); }
    void dis_entry_assembly_end()   { base::dis_entry_assembly_end   (pair_set_add_op<row_type>()); _recompute_nnz(); }
    void dis_entry_assembly()       { dis_entry_assembly_begin(); dis_entry_assembly_end(); }

// io:
    odiststream& put (odiststream& ops) const;
    idiststream& get (idiststream& ips);

// internal:
    odiststream& put_mpi               (odiststream& ops) const;
    odiststream& put_seq               (odiststream& ops, size_type first_dis_i = 0) const;
    odiststream& put_seq_sparse_matlab (odiststream& ops, size_type first_dis_i = 0) const;
    odiststream& put_seq_matrix_market (odiststream& ops, size_type first_dis_i = 0) const;
protected:
    void _recompute_nnz();
// data:
    distributor _col_ownership;
    size_type   _nnz;
    size_type   _dis_nnz;
};