使用图权重提升深度优先访问者最小生成树
Boost depth first visitor minimum spanning tree with graph weights
我想从具有边权重的顶点创建一个最小生成树,并按深度优先顺序遍历图形。我可以构建图形和最小生成树,但我无法编写自定义访问者。
#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器中的顶点和边权重。这可能吗?我看到这个 post: boost minimum spanning tree, how to do depth first? 但我不想构建单独的权重图。
此外,是否可以在不编写自定义访问者的情况下使用增强工具以深度优先顺序遍历树?
MyVisitor vis();
那是一个函数声明。参见 Most Vexing Parse
boost::depth_first_search(spanning_tree, visitor(vis));
在 std::list<Edge>
上调用图形算法。 depth_first_search
requires a graph that models the right graph concepts:
std::list 两者都不建模。
建议
您可以构建一个仅包含 MST 集边的图。您链接到的问题的答案就是这样。
但是,创建同一个图的 filtered_graph<>
视图似乎更容易也更有效,因此可以通过相同的机制简单地使用边属性。
首先,让我们更喜欢在 set<>
而不是 list<>
中获取 MST 边:
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()));
有趣的是,InSpanning
是 也是 函数对象,用作 filtering_graph
的过滤谓词:
boost::filtered_graph<MyGraph, InSpanning, boost::keep_all> mst(g, spanning, {});
现在可以调用de DFS了:
boost::depth_first_search(mst, visitor(vis));
我稍微调整了访问者:
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:
- 它不再对
MyGraph
类型进行硬编码(因为 filtered_graph 具有不同的类型)。
- 它打印你想看的信息。
现场演示
#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();
}
版画
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
我想从具有边权重的顶点创建一个最小生成树,并按深度优先顺序遍历图形。我可以构建图形和最小生成树,但我无法编写自定义访问者。
#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器中的顶点和边权重。这可能吗?我看到这个 post: boost minimum spanning tree, how to do depth first? 但我不想构建单独的权重图。
此外,是否可以在不编写自定义访问者的情况下使用增强工具以深度优先顺序遍历树?
MyVisitor vis();
那是一个函数声明。参见 Most Vexing Parse
boost::depth_first_search(spanning_tree, visitor(vis));
在 std::list<Edge>
上调用图形算法。 depth_first_search
requires a graph that models the right graph concepts:
std::list 两者都不建模。
建议
您可以构建一个仅包含 MST 集边的图。您链接到的问题的答案就是这样。
但是,创建同一个图的 filtered_graph<>
视图似乎更容易也更有效,因此可以通过相同的机制简单地使用边属性。
首先,让我们更喜欢在 set<>
而不是 list<>
中获取 MST 边:
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()));
有趣的是,InSpanning
是 也是 函数对象,用作 filtering_graph
的过滤谓词:
boost::filtered_graph<MyGraph, InSpanning, boost::keep_all> mst(g, spanning, {});
现在可以调用de DFS了:
boost::depth_first_search(mst, visitor(vis));
我稍微调整了访问者:
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:
- 它不再对
MyGraph
类型进行硬编码(因为 filtered_graph 具有不同的类型)。 - 它打印你想看的信息。
现场演示
#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();
}
版画
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