提升图表 bellman_ford_shortest_paths 与 labeled_graph

Question

我正在尝试运行使用 Boost 库的 Bellman-Ford 算法。我有一个带标签的图表，但出现异常 invalid conversion from ‘void*’ to ‘int。任何帮助将不胜感激。这是我的代码：

// g++ -std=c++17 -Wall test.c++ -l boost_system && ./a.out 

#include <iostream>                  // for cout
#include <utility>                   // for pair
#include <algorithm>                 // for for_each
#include <vector>                    // For dist[] and pred[]
#include <limits>                    // To reliably indicate infinity
#include <map>
#include <list>

#include <boost/config.hpp>
#include <boost/graph/graph_traits.hpp>
#include <boost/graph/adjacency_list.hpp>
#include <boost/graph/graph_utility.hpp>
#include <boost/graph/directed_graph.hpp>
#include <boost/graph/labeled_graph.hpp>
#include <boost/graph/bellman_ford_shortest_paths.hpp>

using namespace boost;
using namespace std;

class Node
{
  public:
    int id;
    int group;
};

struct EdgeProperties {
  double weight;

  EdgeProperties(){}
  EdgeProperties(double w){ weight = w; }
};

typedef labeled_graph<adjacency_list<hash_setS, hash_setS, directedS, Node, EdgeProperties>, int> Graph;

int main(){

    cout << "Calling main()" << endl;

    Graph g;

    // populate the graph
    {
        add_vertex( 0, g );
        g[0].id  = 0;
        g[0].group = 10;
        add_vertex( 1, g );
        g[1].id  = 1;
        g[1].group = 20;
        add_edge_by_label( 0, 1, EdgeProperties(110), g);
        add_edge_by_label( 1, 0, EdgeProperties(222), g);
        print_graph(g, get(&Node::id, g));
        cout << "There are " << num_vertices(g) << " nodes and " << num_edges(g) << " edges in the graph" << endl;
    }

    // number of verticies in the graph
    auto n = num_vertices(g);

    // weight map
    auto ewp = weight_map(get(&EdgeProperties::weight, g.graph()));

    const int source = 0;
    const int target = 1;

    // Distance Map (with n elements of value infinity; source's value is 0)
    auto inf = numeric_limits<double>::max();
    vector<double> dist(n, inf);
    dist[source] = 0.0;

    // Predecessor Map (with n elements)
    vector<int> pred(n);

    bellman_ford_shortest_paths(
        g.graph(), 
        n, 
        ewp
            .distance_map(make_iterator_property_map(dist.begin(), get(&Node::id, g)))
            .predecessor_map(make_iterator_property_map(pred.begin(), get(&Node::id, g)))
    );

    return 0;
}

我在 https://www.boost.org/doc/libs/1_53_0/libs/graph/example/bellman-example.cpp 上看到了示例，但该示例未使用带标签的图表。

这是我的代码的实时预览：

https://wandbox.org/permlink/WsQA8A0IyRvGWTIj

谢谢

Answer 1

问题的根源已在您接受的现有答案中触及。

然而，还有更多。

首先，您几乎 "within your right" 想要使用 Node::id 作为顶点索引，并且可能有很多充分的理由使用 vector 以外的其他东西作为 顶点容器选择器¹.

其次，这些东西应该......可能已经奏效了。 bellman_ford documents:

The PredecessorMap type must be a Read/Write Property Map which key and vertex types the same as the vertex descriptor type of the graph.

和iterator_property_map documents：

This property map is an adaptor that converts any random access iterator into a Lvalue Property Map. The OffsetMap type is responsible for converting key objects to integers that can be used as offsets with the random access iterator.

现在 LValuePropertyMap 可能实际上是只读的，但在这种情况下显然不应该是只读的。

当使用带有附加 id-map 参数的 make_iterator_property_map 时，它实际上应该表现得像任何关联属性映射键和值类型 vertex_descriptor 所要求的算法。

UPDATE See "BONUS" below

稍后我可能会更详细地了解为什么它不起作用，但现在让我们在不修改图形模型的情况下解决这个问题：

Live On Coliru

auto gg = g.graph();
auto id = get(&Node::id, gg);
std::map<Graph::vertex_descriptor, Graph::vertex_descriptor> assoc_pred;

bellman_ford_shortest_paths(gg, n,
    weight_map(get(&EdgeProperties::weight, gg))
    .distance_map(make_iterator_property_map(dist.begin(), id))
    .predecessor_map(make_assoc_property_map(assoc_pred))
    );

按预期工作：

Calling main()
1 --> 0 
0 --> 1 
There are 2 nodes and 2 edges in the graph

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我找到了缺失的 link：前身映射定义了错误的值类型：

vector<Graph::vertex_descriptor> pred(n);

显然会起作用：Live On Coliru

¹ 这与顶点描述符略有不同，但在某种意义上相关，即顶点容器的选择通常会预测顶点描述符的实际类型

提升图表 bellman_ford_shortest_paths 与 labeled_graph

Boost Graph bellman_ford_shortest_paths with labeled_graph

c++

boost

boost-graph

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