通过图权重增强深度优先访问者最小生成树 [英] Boost depth first visitor minimum spanning tree with graph weights

问题描述

我想从具有边缘权重的顶点创建最小生成树，并以深度优先的顺序遍历图形.我可以构建图形和最小生成树，但是编写自定义访问者失败.

I want to create a minimum spanning tree from vertices with edge weights and traverse the graph in depth-first order. I can build the graph and the minimum spanning tree but I am failing at writing the custom visitor.

#include <iostream>
#include <boost/graph/adjacency_list.hpp>
#include <boost/graph/kruskal_min_spanning_tree.hpp>
#include <boost/graph/depth_first_search.hpp>
#include <boost/graph/graph_traits.hpp>

#include <vector>
#include <string>

typedef boost::property<boost::edge_weight_t, double> EdgeWeightProperty;
typedef boost::adjacency_list <
    boost::listS,
    boost::vecS,
    boost::undirectedS,
    boost::no_property,
    EdgeWeightProperty> MyGraph;

typedef MyGraph::edge_descriptor Edge;

class MyVisitor : public boost::default_dfs_visitor
{
    public:
    void tree_edge(Edge e, const MyGraph& g) const {

    }
};

void mst() {
    MyGraph g;
    boost::add_edge(0, 1, 0.7, g);
    boost::add_edge(0, 2, 0.1, g);

    boost::add_edge(1, 2, 0.3, g);
    boost::add_edge(1, 0, 0.7, g);
    boost::add_edge(1, 3, 0.8, g);
    boost::add_edge(1, 4, 0.2, g);

    boost::add_edge(2, 1, 0.3, g);
    boost::add_edge(2, 0, 0.1, g);
    boost::add_edge(2, 5, 0.1, g);
    boost::add_edge(2, 4, 0.5, g);

    boost::add_edge(3, 1, 0.8, g);

    boost::add_edge(4, 1, 0.2, g);
    boost::add_edge(4, 2, 0.5, g);

    boost::add_edge(5, 2, 0.1, g);

    std::list <Edge> spanning_tree;
    boost::kruskal_minimum_spanning_tree(g, std::back_inserter(spanning_tree));

    // the following two lines are failing
    MyVisitor vis();
    boost::depth_first_search(spanning_tree, visitor(vis));
}

int main(int argc, char** argv)
{
    mst();
    std::cin.get();
    return (0);
}

我想访问自定义访问者中的顶点和边缘权重.这可能吗?我看到了这篇文章:提升最小生成树，如何进行深度首先?，但我宁愿不构建单独的体重图.

I would like to access the vertices and edge weights in the custom visitor. Is this possible? I saw this post: boost minimum spanning tree, how to do depth first? but I would prefer to not build a separate weight map.

此外，是否可以使用boost工具在深度树优先的顺序中进行迭代，而无需编写自定义访问者?

Additionally, is it possible to iterate in depth-first order through the tree with boost tools without writing a custom visitor?

推荐答案

MyVisitor vis();

那是一个函数声明.请参见大多数恼人的解析器

That is a function declaration. See Most Vexing Parse

boost::depth_first_search(spanning_tree, visitor(vis));

在std::list<Edge>上调用图算法. depth_first_search 需要一个对正确的图形概念建模的图形:

That calls the graph algorithm on a std::list<Edge>. depth_first_search requires a graph that models the right graph concepts:

std :: list都不建模.

The std::list models neither.

您可以构建仅包含MST集中的边缘的图形.您链接到的问题的答案可以尝试.

You could build a graph including just the edges from the MST set. The answer to the question you linked to tries that.

但是，创建同一图形的filtered_graph<>视图似乎更加容易和有效，因此可以通过相同的机制简单地获得边缘属性.

However, it seems easier and more efficient to create a filtered_graph<> view of the same graph, so that the edge properties are simply available through the same mechanism.

首先，让我们更喜欢在set<>而不是list<>中获得MST边缘:

First, let's prefer to get the MST edges in a set<> instead of a list<>:

struct InSpanning {
    std::set<Edge> edges;
    bool operator()(Edge e) const { return edges.count(e); }
} spanning;

boost::kruskal_minimum_spanning_tree(g, std::inserter(spanning.edges, spanning.edges.end()));

您会注意到的有趣的事情是InSpanning也是也是一个函数对象，可用作filtering_graph的过滤谓词:

The interesting thing you'll note is that InSpanning is also a function object that be used as a filtering predicate for filtering_graph:

boost::filtered_graph<MyGraph, InSpanning, boost::keep_all> mst(g, spanning, {});

现在您可以致电de DFS:

Now you can call de DFS:

boost::depth_first_search(mst, visitor(vis));

我已经微调了访客的位置:

I've tweaked the visitor slightly:

struct MyVisitor : boost::default_dfs_visitor {
    template <typename Graph>
    void tree_edge(Edge e, const Graph& g) {
        std::cout << "Visiting: " << e << " with weight " << get(boost::edge_weight, g, e) << "\n";
    }
};

注意:

1. 它不再对MyGraph类型进行硬编码(因为filtered_graph具有不同的类型).
2. 它会打印您想要查看的信息.

1. It doesn't hardcode the MyGraph type anymore (because the filtered_graph has a different type).
2. It prints the information you wanted to see.

实时演示

在Coliru上直播

#include <boost/graph/adjacency_list.hpp>
#include <boost/graph/filtered_graph.hpp>
#include <boost/graph/depth_first_search.hpp>
#include <boost/graph/kruskal_min_spanning_tree.hpp>
#include <iostream>

#include <string>
#include <vector>

typedef boost::property<boost::edge_weight_t, double> EdgeWeightProperty;
typedef boost::adjacency_list<boost::listS, boost::vecS, boost::undirectedS, boost::no_property, EdgeWeightProperty>
    MyGraph;

typedef MyGraph::edge_descriptor Edge;

struct MyVisitor : boost::default_dfs_visitor {
    template <typename Graph>
    void tree_edge(Edge e, const Graph& g) {
        std::cout << "Visiting: " << e << " with weight " << get(boost::edge_weight, g, e) << "\n";
    }
};

void run_mst_test() {
    MyGraph g;
    boost::add_edge(0, 1, 0.7, g);
    boost::add_edge(0, 2, 0.1, g);

    boost::add_edge(1, 2, 0.3, g);
    boost::add_edge(1, 0, 0.7, g);
    boost::add_edge(1, 3, 0.8, g);
    boost::add_edge(1, 4, 0.2, g);

    boost::add_edge(2, 1, 0.3, g);
    boost::add_edge(2, 0, 0.1, g);
    boost::add_edge(2, 5, 0.1, g);
    boost::add_edge(2, 4, 0.5, g);

    boost::add_edge(3, 1, 0.8, g);

    boost::add_edge(4, 1, 0.2, g);
    boost::add_edge(4, 2, 0.5, g);

    boost::add_edge(5, 2, 0.1, g);

    struct InSpanning {
        std::set<Edge> edges;
        bool operator()(Edge e) const { return edges.count(e); }
    } spanning;

    boost::kruskal_minimum_spanning_tree(g, std::inserter(spanning.edges, spanning.edges.end()));

    MyVisitor vis;
    boost::filtered_graph<MyGraph, InSpanning, boost::keep_all> mst(g, spanning, {});
    boost::depth_first_search(mst, visitor(vis));
}

int main() {
    run_mst_test();
}

打印

Visiting: (0,2) with weight 0.1
Visiting: (2,1) with weight 0.3
Visiting: (1,3) with weight 0.8
Visiting: (1,4) with weight 0.2
Visiting: (2,5) with weight 0.1

这篇关于通过图权重增强深度优先访问者最小生成树的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！