On 07/16/2014 03:27 AM, Panos Achlioptas wrote:
Dear all,
I am using the following code to extract for a node of a graph the induced subgraph containing the node and her neighbors (aka, the ego-netwkork).
Can I make it more /efficiently/? In particular, is there a way to avoid using python to create the neighbor list (or at least avoid the type casting).
If not, could I use some code in C/C++ for doing this an embedded in graph_tool?
Thanks a lot, Panos
def egoNetwork(inGraph, node): ''' Compute the ego-network subgraph of the -inGraph- where the ego is the -node-. Precondition: inGraph is undirected ''' neighbors = [int(n) for n in node.out_neighbours()] neighborhood = inGraph.new_vertex_property("bool") neighborhood.a[neighbors] = 1 neighborhood.a[int(node)] = 1 returnGraphView(inGraph, vfilt = neighborhood)
The simplest thing one could do is: mask = g.new_vertex_property("bool") for u in node.out_neighbours(): mask[u] = True mask[node] = True ego = GraphView(inGraph, vfilt=mask) but if you have many neighbours in comparison to the whole graph, the following may be faster: mask = shortest_distance(g, source=node, max_dist=1) mask.a[mask.a > 1] = False mask[node] = True ego = GraphView(inGraph, vfilt=mask) Best, Tiago -- Tiago de Paula Peixoto <tiago@skewed.de>