C++ 使用捆绑属性作为dijkstra_最短路径中的权重映射

也许这是一个愚蠢的问题，但我正在尝试使用BGL的

dijkstra_最短路径

，尤其是使用我的Edge bundled属性的字段作为权重映射。我的尝试目前已经导致数十页的编译器错误，所以我希望有人知道如何帮助我。这就是我的代码的本质：

struct GraphEdge {
    float length;
    // other cruft
};
struct GraphVertex {
    ...
};
typedef boost::adjacency_list
<boost::vecS, boost::vecS, boost::directedS,
 GraphVertex, GraphEdge> GraphType;

这样，weightmap将以某种方式将我的图形的特定边与属性中相应的

length

字段相关联。我相信有一种简单的方法可以做到这一点，但是BGL的文档对我来说是非常不透明的。如果你能告诉我这个例子在文档中的什么地方被描述，我也会很高兴

---

提前谢谢你

如果有人关心这一点，使用命名参数版本的调用似乎已经奏效，如下所示：

    dijkstra_shortest_paths(m_graph, vertex_from,
                        weight_map(get(&TrafficGraphEdge::length, m_graph))
                        .distance_map(make_iterator_property_map(distances.begin(),
                                                                 get(vertex_index, m_graph))));

---

这在文档中。不过，我仍然不知道如何使用调用的“非命名参数”版本。

好的，我只是在这个问题上浪费了太多时间。以下是子孙后代的解决方案：

/**
 * @brief  Example concerning bundled properties.
 * @author Pierre-Andre Noel
 * @date   September 10 2012
 */

#include <iostream>
#include <boost/graph/adjacency_list.hpp>

/// The type of the field we are interested in.
typedef int interesting_type;

/// The struct whose elements will be bundled in each vertex.
struct bundled_in_vertex_type
{
  /// Something interesting.
  interesting_type something;
};

int main()
{
  typedef boost::adjacency_list< boost::vecS, boost::vecS, boost::undirectedS, bundled_in_vertex_type > graph_type;
  typedef graph_type::vertex_descriptor vertex_descriptor_type;

  /// Create a graph of two vertices.
  graph_type g(2);

  /// Name the two nodes.
  const vertex_descriptor_type v1(*boost::vertices(g).first), v2(*(++boost::vertices(g).first));

  // Store some stuff in the two nodes, the "easy" way.
  g[v1].something = interesting_type(42);
  g[v2].something = interesting_type(999);

  // Now what you came here for.
  /// An handle providing direct access to the field "something".
  boost::property_map< graph_type, interesting_type bundled_in_vertex_type::* >::type handle_to_something( boost::get(&bundled_in_vertex_type::something, g) );
  // You can now use "handle_to_something" for whatever deed you are interested in.

  // Just checking that it works.
  std::cout << "Vertex v1's ""something"" field is: " << handle_to_something[v1] << std::endl;
  std::cout << "Vertex v2's ""something"" field is: " << handle_to_something[v2] << std::endl;

  // Thank you and have a nice day.
  return 0;
}

---

虽然BGL可能很强大，但不幸的是，在我看来，它并不容易使用。要实现这一点需要大量的尝试和错误，但这里有一个使用Boost 1.53.0编译的工作版本[我们想对uu edge_数据中的“rate”变量使用Dijkstra算法]：

struct __edge_data
{
    double rate;
    double edge_thickness;
    size_t colour;
};

struct __vertex_data
{   
   size_t colour; 
   size_t shape_code;
   string name;
};

typedef boost::adjacency_list<boost::vecS, boost::vecS, boost::directedS, __vertex_data, __edge_data> DIgraph;
typedef boost::graph_traits<DIgraph>::vertex_descriptor vertexx;
typedef boost::graph_traits<DIgraph>::vertex_iterator   vertexx_iter;
typedef boost::graph_traits<DIgraph>::edge_descriptor   edgee;

// functor
template<typename T>
struct combine_min : public std::binary_function<T, T, T>
{
        T const operator()(const T& a, const T& b) const
        {
            return b < a ? (b) : (a);
        }
};

// functor
template<typename T>
struct compare_less_than : public std::binary_function<T, T, bool>
{
        bool const operator()(const T& a, const T& b) const
        {
            return a < b;
        }
};

void graph_analysis()
{
     ...

      std::vector<vertexx>   parents(num_vertices(G)); 
      std::vector<double>  distances(num_vertices(G)); 

      auto p_map = boost::make_iterator_property_map(&parents[0], boost::get(boost::vertex_index, G));
      auto d_map = boost::make_iterator_property_map(&distances[0], boost::get(boost::vertex_index, G));
      auto w_map = boost::get(&__edge_data::rate_rate, G); // <=== THIS IS THE TRICK!!!
      auto n_map = boost::get(&__vertex_data::name, G);

      boost::dijkstra_shortest_paths(G, start_vertex_vector,
       boost::weight_map(w_map).
              predecessor_map(p_map).
              distance_map(d_map).
              distance_combine(combine_min<double>()).
              distance_compare(compare_less_than<double>()) );

    ...
}

struct\uuuu edge\u数据
{
双倍费率；
双边缘厚度；
大小和颜色；
};
结构顶点数据
{   
大小和颜色；
尺寸、形状和代码；
字符串名；
};
typedef boost：：邻接列表有向图；
typedef boost:：graph_traits:：vertex_描述符vertexx；
typedef boost:：graph_traits:：vertex_迭代器vertexx_iter；
typedef boost:：graph_traits:：edge_描述符edgee；
//函子
模板
结构组合_min:public std:：binary_函数
{
常量运算符（）（常量T&a，常量T&b）常量
{
返回b    auto handle_to_something( boost::get(&bundled_in_vertex_type::something, g) );

struct __edge_data
{
    double rate;
    double edge_thickness;
    size_t colour;
};

struct __vertex_data
{   
   size_t colour; 
   size_t shape_code;
   string name;
};

typedef boost::adjacency_list<boost::vecS, boost::vecS, boost::directedS, __vertex_data, __edge_data> DIgraph;
typedef boost::graph_traits<DIgraph>::vertex_descriptor vertexx;
typedef boost::graph_traits<DIgraph>::vertex_iterator   vertexx_iter;
typedef boost::graph_traits<DIgraph>::edge_descriptor   edgee;

// functor
template<typename T>
struct combine_min : public std::binary_function<T, T, T>
{
        T const operator()(const T& a, const T& b) const
        {
            return b < a ? (b) : (a);
        }
};

// functor
template<typename T>
struct compare_less_than : public std::binary_function<T, T, bool>
{
        bool const operator()(const T& a, const T& b) const
        {
            return a < b;
        }
};

void graph_analysis()
{
     ...

      std::vector<vertexx>   parents(num_vertices(G)); 
      std::vector<double>  distances(num_vertices(G)); 

      auto p_map = boost::make_iterator_property_map(&parents[0], boost::get(boost::vertex_index, G));
      auto d_map = boost::make_iterator_property_map(&distances[0], boost::get(boost::vertex_index, G));
      auto w_map = boost::get(&__edge_data::rate_rate, G); // <=== THIS IS THE TRICK!!!
      auto n_map = boost::get(&__vertex_data::name, G);

      boost::dijkstra_shortest_paths(G, start_vertex_vector,
       boost::weight_map(w_map).
              predecessor_map(p_map).
              distance_map(d_map).
              distance_combine(combine_min<double>()).
              distance_compare(compare_less_than<double>()) );

    ...
}