/usr/include/dolfin/la/TensorLayout.h is in libdolfin-dev 2017.2.0.post0-2.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 | // Copyright (C) 2012 Garth N. Wells
//
// This file is part of DOLFIN.
//
// DOLFIN is free software: you can redistribute it and/or modify
// it under the terms of the GNU Lesser General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
//
// DOLFIN 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 Lesser General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public License
// along with DOLFIN. If not, see <http://www.gnu.org/licenses/>.
//
// First added: 2012-02-24
// Last changed:
#ifndef __TENSOR_LAYOUT_H
#define __TENSOR_LAYOUT_H
#include <memory>
#include <string>
#include <utility>
#include <vector>
#include "dolfin/common/types.h"
#include "dolfin/common/MPI.h"
namespace dolfin
{
class IndexMap;
class SparsityPattern;
/// This class described the size and possibly the sparsity of a
/// (sparse) tensor. It is used by the linear algebra backends to
/// initialise tensors.
class TensorLayout : public Variable
{
public:
/// Sparse or dense layout
enum class Sparsity : bool { SPARSE = true, DENSE = false };
/// Ghosted or unghosted layout
enum class Ghosts : bool { GHOSTED = true, UNGHOSTED = false };
/// Create empty tensor layout
TensorLayout(MPI_Comm comm, std::size_t primary_dim,
Sparsity sparsity_pattern);
/// Create a tensor layout
TensorLayout(MPI_Comm mpi_comm,
std::vector<std::shared_ptr<const IndexMap>> index_maps,
std::size_t primary_dim,
Sparsity sparsity_pattern,
Ghosts ghosted);
/// Initialize tensor layout
void init(std::vector<std::shared_ptr<const IndexMap>> index_maps,
Ghosts ghosted);
/// Return rank
std::size_t rank() const;
/// Return global size for dimension i (size of tensor, includes
/// non-zeroes)
std::size_t size(std::size_t i) const;
/// Return local range for dimension dim
std::pair<std::size_t, std::size_t> local_range(std::size_t dim) const;
/// Return sparsity pattern (possibly null)
std::shared_ptr<SparsityPattern> sparsity_pattern()
{ return _sparsity_pattern; }
/// Return sparsity pattern (possibly null), const version
std::shared_ptr<const SparsityPattern> sparsity_pattern() const
{ return _sparsity_pattern; }
/// Return informal string representation (pretty-print)
std::string str(bool verbose) const;
/// Primary storage dim (e.g., 0=row major, 1=column major)
const std::size_t primary_dim;
/// Return MPI communicator
MPI_Comm mpi_comm() const
{ return _mpi_comm.comm(); }
/// Return IndexMap for dimension
std::shared_ptr<const IndexMap> index_map(std::size_t i) const
{
dolfin_assert(i < _index_maps.size());
return _index_maps[i];
}
/// Require ghosts
Ghosts is_ghosted() const
{
return _ghosted;
}
private:
// MPI communicator
dolfin::MPI::Comm _mpi_comm;
// Index maps
std::vector<std::shared_ptr<const IndexMap>> _index_maps;
// Sparsity pattern
std::shared_ptr<SparsityPattern> _sparsity_pattern;
// Ghosted tensor (typically vector) required
Ghosts _ghosted = Ghosts::UNGHOSTED;
};
}
#endif
|