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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