boost图库图的构建;迭代地添加边属性

boost graph library graph construction; adding edge properties iteratively

本文关键字：添加 属性 迭代 构建 boost      更新时间：2023-10-16

我正在尝试使用boost图库定义一个图。我已经阅读了一个文本文件，以获得如下定义的from_to_and_ddistance矩阵。我计划简单地迭代矩阵来定义图的边，但我不明白如何使用这种方法定义边属性。具体来说，我想使用下面定义的distance_from_a_to_b变量，并为其分配每个主题边缘。正如你所看到的，我对c++还比较陌生，所以虽然库文档可能有答案，但我似乎无法理解。有人能帮忙吗？我计划在这张图完成后将其输入到dijkstra算法中——如果这有区别的话。

提前感谢！

struct site_properties{
};
struct reach_properties{
    double distance;
};
//Note that from_to_and_distance_matrix is std::vector<std::vector<double> > and
//includes inner vectors of [from_node,to_node,distance] 
boost::adjacency_list<boost::vecS,boost::vecS,boost::directedS,site_properties,reach_properties> graph(unique_node_ids.size());
for(unsigned int i = 0; i < from_to_and_distance_matrix.size(); i++){
    int node_a = (int)from_to_and_distance_matrix[i][0];
    int node_b = (int)from_to_and_distance_matrix[i][1];
    //How do I assign the distance_from_a_to_b variable to the edge?!
    double distance_from_a_to_b = from_to_and_distance_matrix[i][2];
    boost::add_edge(node_a,node_b,graph);
}

由于您要将其提供给dijkstra（我假设为dijkstra_shortest_paths），您可以通过将距离存储在edge_weight属性中来简化它，该算法默认读取该属性。

#include <vector>
#include <stack>
#include <iostream>
#include <boost/graph/adjacency_list.hpp>
#include <boost/graph/dijkstra_shortest_paths.hpp>
int main()
{
    // [from_node,to_node,distance] 
    std::vector<std::vector<double>> from_to_and_distance_matrix =
        {{0,1,0.13}, {1,2,0.1}, {1,3,0.2},
         {2,3,0.1}, {1,3,0.3}, {2,4,0.1}};
    using namespace boost;
    typedef adjacency_list<listS, vecS, directedS, no_property,
                           property<edge_weight_t, double>> graph_t;
    graph_t g;
    for(auto& v: from_to_and_distance_matrix)
        get(edge_weight, g)[add_edge(v[0], v[1], g).first] = v[2];
    std::cout << "Loaded graph with " << num_vertices(g) << " nodesn";
    // call Dijkstra
    typedef graph_traits<graph_t>::vertex_descriptor vertex_descriptor;
    std::vector<vertex_descriptor> p(num_vertices(g)); // predecessors
    std::vector<double> d(num_vertices(g)); // distances
    vertex_descriptor start = vertex(0, g); // starting point
    vertex_descriptor goal = vertex(4, g); // end point
    dijkstra_shortest_paths(g, start,
                            predecessor_map(&p[0]).distance_map(&d[0]));
    // print the results
    std::stack<vertex_descriptor> path;
    for(vertex_descriptor v = goal; v != start; v = p[v])
        path.push(v);
    path.push(start);
    std::cout << "Total length of the shortest path: " << d[4] << 'n'
              << "The number of steps: " << path.size() << 'n';
    while(!path.empty()) {
        int pos = path.top();
        std::cout << '[' << pos << "] ";
        path.pop();
    }
    std::cout << 'n';
}

在线演示：http://coliru.stacked-crooked.com/a/4f065507bb5bef35

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