问题
If you look at https://en.wikipedia.org/wiki/Clique_problem, you'll notice there is a distinction between cliques and maximal cliques. A maximal clique is contained in no other clique but itself. So I want those clique, but networkx seems to only provide:
networkx.algorithms.clique.enumerate_all_cliques(G)
So I tried a simple for loop filtering mechanism (see below).
def filter_cliques(self, cliques):
# TODO: why do we need this? Post in forum...
res = []
for C in cliques:
C = set(C)
for D in res:
if C.issuperset(D) and len(C) != len(D):
res.remove(D)
res.append(C)
break
elif D.issuperset(C):
break
else:
res.append(C)
res1 = []
for C in res:
for D in res1:
if C.issuperset(D) and len(C) != len(D):
res1.remove(D)
res1.append(C)
elif D.issuperset(C):
break
else:
res1.append(C)
return res1
I want to filter out all the proper subcliques. But as you can see it sucks because I had to filter it twice. It's not very elegant. So, the problem is, given a list of lists of objects (integers, strings), which were the node labels in the graph; enumerate_all_cliques(G)
returns exactly this list of lists of labels. Now, given this list of lists, filter out all proper subcliques. So for instance:
[[a, b, c], [a, b], [b, c, d]] => [[a, b, c], [b, c, d]]
What's the quickest pythonic way of doing that?
回答1:
There's a function for that: networkx.algorithms.clique.find_cliques, and yes, it does return only maximal cliques, despite the absence of "maximal" from the name. It should run a lot faster than any filtering approach.
If you find the name confusing (I do), you can rename it:
from networkx.algorithms.clique import find_cliques as maximal_cliques
来源:https://stackoverflow.com/questions/54682789/how-do-i-enumerate-all-maximal-cliques-in-a-graph-using-networkx-python