ecency-mobile/ios/Pods/boost-for-react-native/boost/graph/edge_connectivity.hpp

//=======================================================================
// Copyright 2000 University of Notre Dame.
// Authors: Jeremy G. Siek, Andrew Lumsdaine, Lie-Quan Lee
//
// 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)
//=======================================================================

#ifndef BOOST_EDGE_CONNECTIVITY
#define BOOST_EDGE_CONNECTIVITY

// WARNING: not-yet fully tested!

#include <boost/config.hpp>
#include <vector>
#include <set>
#include <algorithm>
#include <boost/graph/edmonds_karp_max_flow.hpp>

namespace boost {

  namespace detail {

    template <class Graph>
    inline
    std::pair<typename graph_traits<Graph>::vertex_descriptor,
              typename graph_traits<Graph>::degree_size_type>
    min_degree_vertex(Graph& g)
    {
      typedef graph_traits<Graph> Traits;
      typename Traits::vertex_descriptor p;
      typedef typename Traits::degree_size_type size_type;
      size_type delta = (std::numeric_limits<size_type>::max)();

      typename Traits::vertex_iterator i, iend;
      for (boost::tie(i, iend) = vertices(g); i != iend; ++i)
        if (degree(*i, g) < delta) {
          delta = degree(*i, g);
          p = *i;
        }
      return std::make_pair(p, delta);
    }

    template <class Graph, class OutputIterator>
    void neighbors(const Graph& g, 
                   typename graph_traits<Graph>::vertex_descriptor u,
                   OutputIterator result)
    {
      typename graph_traits<Graph>::adjacency_iterator ai, aend;
      for (boost::tie(ai, aend) = adjacent_vertices(u, g); ai != aend; ++ai)
        *result++ = *ai;
    }

    template <class Graph, class VertexIterator, class OutputIterator>
    void neighbors(const Graph& g, 
                   VertexIterator first, VertexIterator last,
                   OutputIterator result)
    {
      for (; first != last; ++first)
        neighbors(g, *first, result);
    }

  } // namespace detail

  // O(m n)
  template <class VertexListGraph, class OutputIterator>
  typename graph_traits<VertexListGraph>::degree_size_type
  edge_connectivity(VertexListGraph& g, OutputIterator disconnecting_set)
  {
    //-------------------------------------------------------------------------
    // Type Definitions
    typedef graph_traits<VertexListGraph> Traits;
    typedef typename Traits::vertex_iterator vertex_iterator;
    typedef typename Traits::edge_iterator edge_iterator;
    typedef typename Traits::out_edge_iterator out_edge_iterator;
    typedef typename Traits::vertex_descriptor vertex_descriptor;
    typedef typename Traits::degree_size_type degree_size_type;
    typedef color_traits<default_color_type> Color;

    typedef adjacency_list_traits<vecS, vecS, directedS> Tr;
    typedef typename Tr::edge_descriptor Tr_edge_desc;
    typedef adjacency_list<vecS, vecS, directedS, no_property, 
      property<edge_capacity_t, degree_size_type,
        property<edge_residual_capacity_t, degree_size_type,
          property<edge_reverse_t, Tr_edge_desc> > > > 
      FlowGraph;
    typedef typename graph_traits<FlowGraph>::edge_descriptor edge_descriptor;

    //-------------------------------------------------------------------------
    // Variable Declarations
    vertex_descriptor u, v, p, k;
    edge_descriptor e1, e2;
    bool inserted;
    vertex_iterator vi, vi_end;
    edge_iterator ei, ei_end;
    degree_size_type delta, alpha_star, alpha_S_k;
    std::set<vertex_descriptor> S, neighbor_S;
    std::vector<vertex_descriptor> S_star, non_neighbor_S;
    std::vector<default_color_type> color(num_vertices(g));
    std::vector<edge_descriptor> pred(num_vertices(g));

    //-------------------------------------------------------------------------
    // Create a network flow graph out of the undirected graph
    FlowGraph flow_g(num_vertices(g));

    typename property_map<FlowGraph, edge_capacity_t>::type
      cap = get(edge_capacity, flow_g);
    typename property_map<FlowGraph, edge_residual_capacity_t>::type
      res_cap = get(edge_residual_capacity, flow_g);
    typename property_map<FlowGraph, edge_reverse_t>::type
      rev_edge = get(edge_reverse, flow_g);

    for (boost::tie(ei, ei_end) = edges(g); ei != ei_end; ++ei) {
      u = source(*ei, g), v = target(*ei, g);
      boost::tie(e1, inserted) = add_edge(u, v, flow_g);
      cap[e1] = 1;
      boost::tie(e2, inserted) = add_edge(v, u, flow_g);
      cap[e2] = 1; // not sure about this
      rev_edge[e1] = e2;
      rev_edge[e2] = e1;
    }

    //-------------------------------------------------------------------------
    // The Algorithm

    boost::tie(p, delta) = detail::min_degree_vertex(g);
    S_star.push_back(p);
    alpha_star = delta;
    S.insert(p);
    neighbor_S.insert(p);
    detail::neighbors(g, S.begin(), S.end(), 
                      std::inserter(neighbor_S, neighbor_S.begin()));

    boost::tie(vi, vi_end) = vertices(g);
    std::set_difference(vi, vi_end,
                        neighbor_S.begin(), neighbor_S.end(),
                        std::back_inserter(non_neighbor_S));

    while (!non_neighbor_S.empty()) { // at most n - 1 times
      k = non_neighbor_S.front();

      alpha_S_k = edmonds_karp_max_flow
        (flow_g, p, k, cap, res_cap, rev_edge, &color[0], &pred[0]);

      if (alpha_S_k < alpha_star) {
        alpha_star = alpha_S_k;
        S_star.clear();
        for (boost::tie(vi, vi_end) = vertices(flow_g); vi != vi_end; ++vi)
          if (color[*vi] != Color::white())
            S_star.push_back(*vi);
      }
      S.insert(k);
      neighbor_S.insert(k);
      detail::neighbors(g, k, std::inserter(neighbor_S, neighbor_S.begin()));
      non_neighbor_S.clear();
      boost::tie(vi, vi_end) = vertices(g);
      std::set_difference(vi, vi_end,
                          neighbor_S.begin(), neighbor_S.end(),
                          std::back_inserter(non_neighbor_S));
    }
    //-------------------------------------------------------------------------
    // Compute edges of the cut [S*, ~S*]
    std::vector<bool> in_S_star(num_vertices(g), false);
    typename std::vector<vertex_descriptor>::iterator si;
    for (si = S_star.begin(); si != S_star.end(); ++si)
      in_S_star[*si] = true;

    degree_size_type c = 0;
    for (si = S_star.begin(); si != S_star.end(); ++si) {
      out_edge_iterator ei, ei_end;
      for (boost::tie(ei, ei_end) = out_edges(*si, g); ei != ei_end; ++ei)
        if (!in_S_star[target(*ei, g)]) {
          *disconnecting_set++ = *ei;
          ++c;
        }
    }
    return c;
  }

} // namespace boost

#endif // BOOST_EDGE_CONNECTIVITY