Provided by: librheolef-dev_6.6-1build2_amd64 bug


       asr - associative sparse matrix (rheolef-6.6)


       Associative sparse matrix container, used during FEM assembling process.


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


       template<class T, class M = rheo_default_memory_model, class A = std::allocator<T> >
       class asr : public array<pair_set<T,A>, M, A> {
       // 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;
           void _recompute_nnz();
       // data:
           distributor _col_ownership;
           size_type   _nnz;
           size_type   _dis_nnz;