我最近尝试做同样的事情(使用向量属性)并且未能仅使用其中一个值运行算法。但是,我发现使用外部属性是一种很好的方法,它不会导致不必要的复制操作并将属性映射显式传递给算法。
如果您使用随机访问容器,您可以使用boost::iterator_property_map
它将包装该容器并使其成为property_map
. 它需要基于 0 的边缘索引来实现边缘和属性值之间的有效映射,而不是边缘描述符。这是妙语,您还可以找到完整的示例:
// ...
EdgeIndexMap edgeIds = get(edge_index, g);
// ...
typedef std::vector<int> Weights;
typedef std::vector<Weights> WeightsVector;
typedef iterator_property_map <Weights::iterator, EdgeIndexMap> WeightMap;
// ...
Weights weights; // = ...
WeightMap wm(weights.begin(), edgeIds);
// ...
some_bgl_algorithm(g, wm);
这里有一个完整的例子:
using namespace boost;
void sampleExteriorProperties()
{
typedef adjacency_list<vecS, vecS, undirectedS,
no_property,
//property<edge_index_t, int, property<edge_weight_t, int> >
property<edge_index_t, std::size_t>
> Graph;
typedef graph_traits<Graph>::edge_descriptor Edge;
typedef graph_traits<Graph>::edge_iterator EdgeIterator;
typedef property_map<Graph, edge_index_t>::type EdgeIndexMap;
//typedef property_map<Graph, edge_weight_t>::type WeightMap;
const int NVERTICES = 5;
const int NEDGES = 8;
Graph g(NVERTICES);
// Add edges WITH indexes.
int edgeIndex = 0;
add_edge(0, 1, edgeIndex++, g);
add_edge(0, 2, edgeIndex++, g);
add_edge(0, 3, edgeIndex++, g);
add_edge(1, 2, edgeIndex++, g);
add_edge(1, 4, edgeIndex++, g);
add_edge(2, 3, edgeIndex++, g);
add_edge(2, 4, edgeIndex++, g);
add_edge(3, 4, edgeIndex++, g);
// Weights: there must be a weight for every edge.
// Weights will be later on accessed by edge index.
assert(num_edges(g) == NEDGES);
typedef std::vector<int> Weights;
typedef std::vector<Weights> WeightsVector;
WeightsVector weightVector({ { 2, 3, 5, 7, 9, 11, 13, 17 },
{ 8, 7, 6, 5, 4, 3, 2, 1 }
});
EdgeIndexMap edgeIds = get(edge_index, g);
for (Weights &weights : weightVector)
{
// Use the iterator_property_map to read the properties from a
// random access container. Remember: Edge ids are used to access
// the correct value from the container!
typedef iterator_property_map <Weights::iterator, EdgeIndexMap> WeightMap;
WeightMap wm(weights.begin(), edgeIds);
EdgeIterator eIt, eItEnd;
tie(eIt, eItEnd) = edges(g);
while (eIt!=eItEnd)
{
std::cout << *eIt << ": " << wm[*eIt] << " ";
++eIt;
}
std::cout << std::endl;
// Explicitly pass the exterior map to the algorithm.
std::vector<Edge> mstEdges;
kruskal_minimum_spanning_tree(g, std::back_inserter(mstEdges),
weight_map(wm));
std::for_each(mstEdges.begin(), mstEdges.end(),
[](const Edge &val){std::cout << val << " ";});
std::cout << std::endl;
}
}