通过顶点标签属性制作增强的filtered_graph [英] Make a boost filtered_graph by vertex label property
问题描述
目前,我有一个图形,可以通过external map
跟踪vertices
和labels
.因此,只要我需要访问label属性,就可以在地图上找到标签并获取mapped vertex
.
Currently, I have a graph, that I keep tracking of vertices
and labels
by means of an external map
. So anytime I need to access the label property, I find the label in the map and get the mapped vertex
.
/// vertex properties
struct VertexData
{
std::string label;
int num;
};
/// edges properties
struct EdgeData
{
std::string edge_name;
double edge_confidence;
};
/// define the boost-graph
typedef boost::adjacency_list<boost::vecS, boost::vecS,
boost::bidirectionalS,
boost::property<boost::edge_index_t , size_t , VertexData>,
boost::property<boost::edge_weight_t, double, EdgeData> > Graph;
/// define vertexMap
std::map<std::string, vertex_t> vertexMap;
///loop through the vertices to make the vertexMap here ...
vertexMap.insert(std::pair<std::string, vertex_t> (label, v));
/// find any label in the map and access the corresponding vertex
vertex_t vertex = vertexMap.find(label)->second;
现在我的问题是:
如果要通过过滤一些标签从当前图形中创建filtered_graph
,该如何在class template
中执行此操作?提升图库中的示例有所不同,我也检查了这篇文章增强图形复制并删除顶点,但这与我想做的完全不同.
Now my question is:
If I want to make a filtered_graph
from current graph by filtering some labels, how should I do that in the class template
? The examples in the boost graph library are different, and I checked also this post boost graph copy and removing vertex but it's quite different from what I want to do.
感谢您的帮助.
推荐答案
过滤
您需要一个过滤谓词.您可以针对不同的图形元素具有多个.但是,让我们关注顶点.
Filtering
You need a filtering predicate. You can have multiple for different graph elements. But let's focus on vertices.
您想要的是一个有状态谓词.实现此目的的方法通常是将状态保持在谓词之外,并在谓词内部放置一个指向该状态的指针:
What you want is a stateful predicate. The way to do this is usually keeping the state outside the predicate and putting a pointer to that inside the predicate:
#include <boost/graph/adjacency_list.hpp>
#include <boost/graph/filtered_graph.hpp>
#include <boost/graph/graphviz.hpp>
#include <iostream>
namespace bi = boost::intrusive;
/// vertex properties
struct VertexData {
std::string label;
int num;
};
/// edges properties
struct EdgeData {
std::string edge_name;
double edge_confidence;
};
/// define the boost-graph
typedef boost::adjacency_list<boost::vecS, boost::vecS,
boost::bidirectionalS,
VertexData,
boost::property<boost::edge_weight_t, double, EdgeData> > Graph;
int main() {
using vertex_t = Graph::vertex_descriptor;
Graph g;
for (auto label : { "alerts", "amazed", "buster", "deaths", "ekes", "Enoch", "gale", "hug", "input", "knifed", "lire", "man", "pithy", "Purims", "Rodger", "suckle", "Terr", "theme", "tiling", "vases", }) {
boost::add_vertex(VertexData{label, 1+rand()%5}, g);
}
boost::write_graphviz(std::cout, g, boost::make_label_writer(boost::get(&VertexData::label, g)));
{
using labels = std::set<std::string>;
labels suppressed { "alerts", "amazed", "deaths", "ekes", "gale", "hug", "input", "knifed", "man", "pithy", "Purims", "suckle", "Terr", "theme", "vases", };
struct Predicate { // both edge and vertex
bool operator()(Graph::edge_descriptor) const { return true; } // all
bool operator()(Graph::vertex_descriptor vd) const { return suppressed_->count((*g)[vd].label) == 0; }
Graph* g;
labels* suppressed_;
} predicate {&g, &suppressed};
using Filtered = boost::filtered_graph<Graph, Predicate, Predicate>;
Filtered fg(g, predicate, predicate);
boost::write_graphviz(std::cout, fg, boost::make_label_writer(boost::get(&VertexData::label, fg)));
}
}
先打印未过滤的图形(g
),然后打印已过滤的图形(fg
):
Prints the unfiltered graph (g
) first, and then the filtered graph (fg
):
digraph G {
2[label=buster];
5[label=Enoch];
10[label=lire];
14[label=Rodger];
18[label=tiling];
}
索引
并不是真正的问题,但是您可以使用介入式容器使索引的维护更加友好.如果将钩子添加到VertexData:
Indexing
Not really the question, but you can make maintaining an index slightly more friendly using intrusive containers. If you add a hook to the VertexData:
struct VertexData : bi::set_base_hook<> {
std::string label;
int num;
struct by_label;
};
您可以使用侵入式设置:
You can use an intrusive-set:
using by_label_idx_t = bi::set<VertexData, bi::key_of_value<VertexData::by_label> >;
这意味着您可以添加所有顶点:
This means you can add all vertices:
by_label_idx_t label_idx;
for (auto vd : boost::make_iterator_range(boost::vertices(g)))
label_idx.insert(g[vd]);
这能给您带来什么?本身不是很多.但是启用自动取消链接功能后,您确实可以买到,当删除顶点时,它会自动从索引中删除.
What does this buy you? Not a lot per se. But enabling auto-unlinking, it does buy you that when a vertex is removed, it's automatically removed from the index.
#include <boost/graph/adjacency_list.hpp>
#include <boost/graph/filtered_graph.hpp>
#include <boost/intrusive/set_hook.hpp>
#include <boost/intrusive/set.hpp>
#include <iostream>
namespace bi = boost::intrusive;
/// vertex properties
struct VertexData : bi::set_base_hook<bi::link_mode<bi::auto_unlink>, bi::constant_time_size<false> > {
std::string label;
int num;
VertexData(std::string label, int num) : label(label), num(num) {}
struct by_label {
using type = std::string;
std::string const& operator()(VertexData const& vd) const { return vd.label; }
};
};
using by_label_idx_t = bi::set<VertexData, bi::constant_time_size<false>, bi::key_of_value<VertexData::by_label> >;
/// edges properties
struct EdgeData {
std::string edge_name;
double edge_confidence;
};
/// define the boost-graph
typedef boost::adjacency_list<boost::vecS, boost::vecS,
boost::bidirectionalS,
VertexData,
boost::property<boost::edge_weight_t, double, EdgeData> > Graph;
int main() {
using vertex_t = Graph::vertex_descriptor;
Graph g;
for (auto label : { "alerts", "amazed", "buster", "deaths", "ekes", "Enoch", "gale", "hug", "input", "knifed", "lire", "man", "pithy", "Purims", "Rodger", "suckle", "Terr", "theme", "tiling", "vases", }) {
boost::add_vertex(VertexData{label, 1+rand()%5}, g);
}
/// define vertexMap
by_label_idx_t label_idx;
auto reindex = [&] {
label_idx.clear();
for (auto vd : boost::make_iterator_range(boost::vertices(g)))
label_idx.insert(g[vd]);
};
reindex();
std::cout << "Index: " << label_idx.size() << " elements\n";
g.clear();
std::cout << "Index: " << label_idx.size() << " elements\n";
for (auto& vertex : label_idx) {
std::cout << vertex.label << " " << vertex.num << "\n";
}
}
这篇关于通过顶点标签属性制作增强的filtered_graph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!