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// Copyright 2004 The Trustees of Indiana University. // Distributed under the Boost Software License, Version 1.0. // (See accompanying file LICENSE_1_0.txt or copy at // http://www.boost.org/LICENSE_1_0.txt) // Authors: Jeremiah Willcock // Douglas Gregor // Andrew Lumsdaine #ifndef BOOST_GRAPH_GURSOY_ATUN_LAYOUT_HPP #define BOOST_GRAPH_GURSOY_ATUN_LAYOUT_HPP // Gürsoy-Atun graph layout, based on: // "Neighbourhood Preserving Load Balancing: A Self-Organizing Approach" // in 6th International Euro-Par Conference Munich, Germany, August 29 – // September 1, 2000 Proceedings, pp 234-241 // https://doi.org/10.1007/3-540-44520-X_32 #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include namespace boost { namespace detail { struct over_distance_limit : public std::exception { }; template < typename PositionMap, typename NodeDistanceMap, typename Topology, typename Graph > struct update_position_visitor { typedef typename Topology::point_type Point; PositionMap position_map; NodeDistanceMap node_distance; const Topology& space; Point input_vector; double distance_limit; double learning_constant; double falloff_ratio; typedef boost::on_examine_vertex event_filter; typedef typename graph_traits< Graph >::vertex_descriptor vertex_descriptor; update_position_visitor(PositionMap position_map, NodeDistanceMap node_distance, const Topology& space, const Point& input_vector, double distance_limit, double learning_constant, double falloff_ratio) : position_map(position_map) , node_distance(node_distance) , space(space) , input_vector(input_vector) , distance_limit(distance_limit) , learning_constant(learning_constant) , falloff_ratio(falloff_ratio) { } void operator()(vertex_descriptor v, const Graph&) const { #ifndef BOOST_NO_STDC_NAMESPACE using std::pow; #endif if (get(node_distance, v) > distance_limit) BOOST_THROW_EXCEPTION(over_distance_limit()); Point old_position = get(position_map, v); double distance = get(node_distance, v); double fraction = learning_constant * pow(falloff_ratio, distance * distance); put(position_map, v, space.move_position_toward( old_position, fraction, input_vector)); } }; template < typename EdgeWeightMap > struct gursoy_shortest { template < typename Graph, typename NodeDistanceMap, typename UpdatePosition > static inline void run(const Graph& g, typename graph_traits< Graph >::vertex_descriptor s, NodeDistanceMap node_distance, UpdatePosition& update_position, EdgeWeightMap weight) { boost::dijkstra_shortest_paths(g, s, weight_map(weight).visitor(boost::make_dijkstra_visitor( std::make_pair(boost::record_distances( node_distance, boost::on_edge_relaxed()), update_position)))); } }; template <> struct gursoy_shortest< dummy_property_map > { template < typename Graph, typename NodeDistanceMap, typename UpdatePosition > static inline void run(const Graph& g, typename graph_traits< Graph >::vertex_descriptor s, NodeDistanceMap node_distance, UpdatePosition& update_position, dummy_property_map) { boost::breadth_first_search(g, s, visitor(boost::make_bfs_visitor( std::make_pair(boost::record_distances( node_distance, boost::on_tree_edge()), update_position)))); } }; } // namespace detail template < typename VertexListAndIncidenceGraph, typename Topology, typename PositionMap, typename Diameter, typename VertexIndexMap, typename EdgeWeightMap > void gursoy_atun_step(const VertexListAndIncidenceGraph& graph, const Topology& space, PositionMap position, Diameter diameter, double learning_constant, VertexIndexMap vertex_index_map, EdgeWeightMap weight) { #ifndef BOOST_NO_STDC_NAMESPACE using std::exp; using std::pow; #endif typedef typename graph_traits< VertexListAndIncidenceGraph >::vertex_iterator vertex_iterator; typedef typename graph_traits< VertexListAndIncidenceGraph >::vertex_descriptor vertex_descriptor; typedef typename Topology::point_type point_type; vertex_iterator i, iend; std::vector< double > distance_from_input_vector(num_vertices(graph)); typedef boost::iterator_property_map< std::vector< double >::iterator, VertexIndexMap, double, double& > DistanceFromInputMap; DistanceFromInputMap distance_from_input( distance_from_input_vector.begin(), vertex_index_map); std::vector< double > node_distance_map_vector(num_vertices(graph)); typedef boost::iterator_property_map< std::vector< double >::iterator, VertexIndexMap, double, double& > NodeDistanceMap; NodeDistanceMap node_distance( node_distance_map_vector.begin(), vertex_index_map); point_type input_vector = space.random_point(); vertex_descriptor min_distance_loc = graph_traits< VertexListAndIncidenceGraph >::null_vertex(); double min_distance = 0.0; bool min_distance_unset = true; for (boost::tie(i, iend) = vertices(graph); i != iend; ++i) { double this_distance = space.distance(get(position, *i), input_vector); put(distance_from_input, *i, this_distance); if (min_distance_unset || this_distance < min_distance) { min_distance = this_distance; min_distance_loc = *i; } min_distance_unset = false; } BOOST_ASSERT(!min_distance_unset); // Graph must have at least one vertex boost::detail::update_position_visitor< PositionMap, NodeDistanceMap, Topology, VertexListAndIncidenceGraph > update_position(position, node_distance, space, input_vector, diameter, learning_constant, exp(-1. / (2 * diameter * diameter))); std::fill( node_distance_map_vector.begin(), node_distance_map_vector.end(), 0); try { typedef detail::gursoy_shortest< EdgeWeightMap > shortest; shortest::run( graph, min_distance_loc, node_distance, update_position, weight); } catch (const detail::over_distance_limit&) { /* Thrown to break out of BFS or Dijkstra early */ } } template < typename VertexListAndIncidenceGraph, typename Topology, typename PositionMap, typename VertexIndexMap, typename EdgeWeightMap > void gursoy_atun_refine(const VertexListAndIncidenceGraph& graph, const Topology& space, PositionMap position, int nsteps, double diameter_initial, double diameter_final, double learning_constant_initial, double learning_constant_final, VertexIndexMap vertex_index_map, EdgeWeightMap weight) { #ifndef BOOST_NO_STDC_NAMESPACE using std::exp; using std::pow; #endif typedef typename graph_traits< VertexListAndIncidenceGraph >::vertex_iterator vertex_iterator; vertex_iterator i, iend; double diameter_ratio = (double)diameter_final / diameter_initial; double learning_constant_ratio = learning_constant_final / learning_constant_initial; std::vector< double > distance_from_input_vector(num_vertices(graph)); typedef boost::iterator_property_map< std::vector< double >::iterator, VertexIndexMap, double, double& > DistanceFromInputMap; DistanceFromInputMap distance_from_input( distance_from_input_vector.begin(), vertex_index_map); std::vector< int > node_distance_map_vector(num_vertices(graph)); typedef boost::iterator_property_map< std::vector< int >::iterator, VertexIndexMap, double, double& > NodeDistanceMap; NodeDistanceMap node_distance( node_distance_map_vector.begin(), vertex_index_map); for (int round = 0; round < nsteps; ++round) { double part_done = (double)round / (nsteps - 1); // fprintf(stderr, "%2d%% done\n", int(rint(part_done * 100.))); int diameter = (int)(diameter_initial * pow(diameter_ratio, part_done)); double learning_constant = learning_constant_initial * pow(learning_constant_ratio, part_done); gursoy_atun_step(graph, space, position, diameter, learning_constant, vertex_index_map, weight); } } template < typename VertexListAndIncidenceGraph, typename Topology, typename PositionMap, typename VertexIndexMap, typename EdgeWeightMap > void gursoy_atun_layout(const VertexListAndIncidenceGraph& graph, const Topology& space, PositionMap position, int nsteps, double diameter_initial, double diameter_final, double learning_constant_initial, double learning_constant_final, VertexIndexMap vertex_index_map, EdgeWeightMap weight) { typedef typename graph_traits< VertexListAndIncidenceGraph >::vertex_iterator vertex_iterator; vertex_iterator i, iend; for (boost::tie(i, iend) = vertices(graph); i != iend; ++i) { put(position, *i, space.random_point()); } gursoy_atun_refine(graph, space, position, nsteps, diameter_initial, diameter_final, learning_constant_initial, learning_constant_final, vertex_index_map, weight); } template < typename VertexListAndIncidenceGraph, typename Topology, typename PositionMap, typename VertexIndexMap > void gursoy_atun_layout(const VertexListAndIncidenceGraph& graph, const Topology& space, PositionMap position, int nsteps, double diameter_initial, double diameter_final, double learning_constant_initial, double learning_constant_final, VertexIndexMap vertex_index_map) { gursoy_atun_layout(graph, space, position, nsteps, diameter_initial, diameter_final, learning_constant_initial, learning_constant_final, vertex_index_map, dummy_property_map()); } template < typename VertexListAndIncidenceGraph, typename Topology, typename PositionMap > void gursoy_atun_layout(const VertexListAndIncidenceGraph& graph, const Topology& space, PositionMap position, int nsteps, double diameter_initial, double diameter_final = 1.0, double learning_constant_initial = 0.8, double learning_constant_final = 0.2) { gursoy_atun_layout(graph, space, position, nsteps, diameter_initial, diameter_final, learning_constant_initial, learning_constant_final, get(vertex_index, graph)); } template < typename VertexListAndIncidenceGraph, typename Topology, typename PositionMap > void gursoy_atun_layout(const VertexListAndIncidenceGraph& graph, const Topology& space, PositionMap position, int nsteps) { #ifndef BOOST_NO_STDC_NAMESPACE using std::sqrt; #endif gursoy_atun_layout( graph, space, position, nsteps, sqrt((double)num_vertices(graph))); } template < typename VertexListAndIncidenceGraph, typename Topology, typename PositionMap > void gursoy_atun_layout(const VertexListAndIncidenceGraph& graph, const Topology& space, PositionMap position) { gursoy_atun_layout(graph, space, position, num_vertices(graph)); } template < typename VertexListAndIncidenceGraph, typename Topology, typename PositionMap, typename P, typename T, typename R > void gursoy_atun_layout(const VertexListAndIncidenceGraph& graph, const Topology& space, PositionMap position, const bgl_named_params< P, T, R >& params) { #ifndef BOOST_NO_STDC_NAMESPACE using std::sqrt; #endif std::pair< double, double > diam(sqrt(double(num_vertices(graph))), 1.0); std::pair< double, double > learn(0.8, 0.2); gursoy_atun_layout(graph, space, position, choose_param(get_param(params, iterations_t()), num_vertices(graph)), choose_param(get_param(params, diameter_range_t()), diam).first, choose_param(get_param(params, diameter_range_t()), diam).second, choose_param(get_param(params, learning_constant_range_t()), learn) .first, choose_param(get_param(params, learning_constant_range_t()), learn) .second, choose_const_pmap(get_param(params, vertex_index), graph, vertex_index), choose_param(get_param(params, edge_weight), dummy_property_map())); } } // namespace boost #endif // BOOST_GRAPH_GURSOY_ATUN_LAYOUT_HPP