Thanks for the quick response.
dist = shortest_distance(g, source=v)
k_disk = GraphView(g, vfilt=dist.fa <= k)
This will work. But doesn't it first compute the shortest distance from
v to all other vertices in g and then applies a filter? This is rather
inefficient, especially when then graph is huge...
On 11.09.2015 17:30, Tiago de Paula Peixoto wrote:
On 11.09.2015 13:59, Christopher Morris wrote:
Hello,
given an undirected, unweighted graph and a vertex v, I want to
compute the k-disk around v, i.e. the induced subgraph of vertices at
a distanst at most k from v.
Of course, this can be easily be done by a variation of BFS or DFS. Is
it possible do use graph_tool.search.bfs_search in some way for this?
Just do:
dist = shortest_distance(g, source=v)
k_disk = GraphView(g, vfilt=dist.fa <= k)
Best,
Tiago
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