EQ2EMu/EQ2/source/depends/boost_1_72_0/boost/graph/random_spanning_tree.hpp

// Copyright 2010 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
//           Andrew Lumsdaine

#ifndef BOOST_GRAPH_RANDOM_SPANNING_TREE_HPP
#define BOOST_GRAPH_RANDOM_SPANNING_TREE_HPP

#include <vector>
#include <boost/assert.hpp>
#include <boost/graph/loop_erased_random_walk.hpp>
#include <boost/graph/random.hpp>
#include <boost/graph/iteration_macros.hpp>
#include <boost/property_map/property_map.hpp>
#include <boost/config.hpp>
#include <boost/graph/graph_traits.hpp>
#include <boost/graph/graph_concepts.hpp>
#include <boost/graph/properties.hpp>
#include <boost/graph/named_function_params.hpp>

namespace boost {

  namespace detail {
    // Use Wilson's algorithm (based on loop-free random walks) to generate a
    // random spanning tree.  The distribution of edges used is controlled by
    // the next_edge() function, so this version allows either weighted or
    // unweighted selection of trees.
    // Algorithm is from http://en.wikipedia.org/wiki/Uniform_spanning_tree
    template <typename Graph, typename PredMap, typename ColorMap, typename NextEdge>
    void random_spanning_tree_internal(const Graph& g, typename graph_traits<Graph>::vertex_descriptor s, PredMap pred, ColorMap color, NextEdge next_edge) {
      typedef typename graph_traits<Graph>::vertex_descriptor vertex_descriptor;

      BOOST_ASSERT (num_vertices(g) >= 1); // g must also be undirected (or symmetric) and connected

      typedef color_traits<typename property_traits<ColorMap>::value_type> color_gen;
      BGL_FORALL_VERTICES_T(v, g, Graph) put(color, v, color_gen::white());

      std::vector<vertex_descriptor> path;

      put(color, s, color_gen::black());
      put(pred, s, graph_traits<Graph>::null_vertex());

      BGL_FORALL_VERTICES_T(v, g, Graph) {
        if (get(color, v) != color_gen::white()) continue;
        loop_erased_random_walk(g, v, next_edge, color, path);
        for (typename std::vector<vertex_descriptor>::const_reverse_iterator i = path.rbegin();
             boost::next(i) !=
               (typename std::vector<vertex_descriptor>::const_reverse_iterator)path.rend();
             ++i) {
          typename std::vector<vertex_descriptor>::const_reverse_iterator j = i;
          ++j;
          BOOST_ASSERT (get(color, *j) == color_gen::gray());
          put(color, *j, color_gen::black());
          put(pred, *j, *i);
        }
      }
    }
  }

  // Compute a uniformly-distributed spanning tree on a graph.  Use Wilson's algorithm:
  // @inproceedings{wilson96generating,
  //    author = {Wilson, David Bruce},
  //    title = {Generating random spanning trees more quickly than the cover time},
  //    booktitle = {STOC '96: Proceedings of the twenty-eighth annual ACM symposium on Theory of computing},
  //    year = {1996},
  //    isbn = {0-89791-785-5},
  //    pages = {296--303},
  //    location = {Philadelphia, Pennsylvania, United States},
  //    doi = {http://doi.acm.org/10.1145/237814.237880},
  //    publisher = {ACM},
  //    address = {New York, NY, USA},
  //  }
  //
  template <typename Graph, typename Gen, typename PredMap, typename ColorMap>
  void random_spanning_tree(const Graph& g, Gen& gen, typename graph_traits<Graph>::vertex_descriptor root,
                            PredMap pred, static_property_map<double>, ColorMap color) {
    unweighted_random_out_edge_gen<Graph, Gen> random_oe(gen);
    detail::random_spanning_tree_internal(g, root, pred, color, random_oe);
  }

  // Compute a weight-distributed spanning tree on a graph.
  template <typename Graph, typename Gen, typename PredMap, typename WeightMap, typename ColorMap>
  void random_spanning_tree(const Graph& g, Gen& gen, typename graph_traits<Graph>::vertex_descriptor root,
                            PredMap pred, WeightMap weight, ColorMap color) {
    weighted_random_out_edge_gen<Graph, WeightMap, Gen> random_oe(weight, gen);
    detail::random_spanning_tree_internal(g, root, pred, color, random_oe);
  }

  template <typename Graph, typename Gen, typename P, typename T, typename R>
  void random_spanning_tree(const Graph& g, Gen& gen, const bgl_named_params<P, T, R>& params) {
    using namespace boost::graph::keywords;
    typedef bgl_named_params<P, T, R> params_type;
    BOOST_GRAPH_DECLARE_CONVERTED_PARAMETERS(params_type, params)
    typedef typename graph_traits<Graph>::vertex_descriptor vertex_descriptor;
    vertex_descriptor default_vertex = *vertices(g).first;
    vertex_descriptor start_vertex = arg_pack[_root_vertex | default_vertex];
    typename boost::parameter::binding<
        arg_pack_type, 
        boost::graph::keywords::tag::predecessor_map
    >::type pred_map = arg_pack[_predecessor_map];
    static_property_map<double> default_weight_map(1.);
    typename boost::parameter::value_type<
        arg_pack_type, 
        boost::graph::keywords::tag::weight_map,
        static_property_map<double>
    >::type e_w_map = arg_pack[_weight_map | default_weight_map];
    typename boost::detail::map_maker<
        Graph,
        arg_pack_type,
        boost::graph::keywords::tag::color_map,
        boost::default_color_type
    >::map_type c_map = boost::detail::make_color_map_from_arg_pack(g, arg_pack);
    random_spanning_tree(g, gen, start_vertex, pred_map, e_w_map, c_map);
  }
}

#include <boost/graph/iteration_macros_undef.hpp>

#endif // BOOST_GRAPH_RANDOM_SPANNING_TREE_HPP