Creating Cliques From Connected Components Using Networkx

I have created a graph using networkx in Python. import networkx as nx G = createGraph ('abc.csv') #My function that returns graph from file. connected_components = nx.connected_c

Solution 1:

You can use itertools.permutations:

>>>G
<networkx.classes.graph.Graph object at 0x7f123559f3c8>
>>>list(nx.connected_components(G))
[{0, 4, 5, 6, 7, 9}, {1}, {8, 2}, {3}]

>>>import itertools>>>import csv>>>>>>withopen('cliques.csv', 'tw') as f:...    w = csv.writer(f, csv.excel_tab)...    w.writerow(['node1', 'node2', 'clique'])...    w.writerows(p + (i,) for i, n inenumerate(nx.connected_components(G), 1) for p in itertools.permutations(n, 2))... 
20

Creates a file containing:

node1   node2   clique
0       4       1
0       5       1
0       6       1
0       7       1
0       9       1
4       0       1
4       5       1

...

9       6       1
9       7       1
8       2       3
2       8       3

Solution 2:

This answer is effectively identical to PaulPanzer's answer once you look at how the specific algorithms I use are coded in networkx:

G=nx.Graph()
G.add_edges_from([(1,2), (2,3), (4,5), (5,6)])
list(nx.connected_components(G))
> [{1,2,3},{4,5,6}]

#we're done setting G up.  Let's do it.

CCs = nx.connected_components(G)
complete_subgraphs = (nx.complete_graph(component) for component in CCs)
H=nx.compose_all(complete_subgraphs)

Here we first find the connected components (technically we create a generator for them). Then we find all the complete graphs using nx.complete_graph(nodes) for each of those components. Finally we join all the graphs together with compose_all.