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I'm counting the number of motifs (3-nodes isophormic class of connected subgraphs) in a random directed network. There are 13 of this. One is, for example S1={1 -> 2, 2 -> 3} and another one S2={1 -> 2, 2 -> 3, 1 -> 3}. They are two distinct motifs, and I wouldn't count a S1 when I actually find S2. The problem is that S1 is in S2, hence subgraph_search() finds a S1 in each S2 and all related functions inherit the problem (wrong counting, wrong iterator...).

Any idea how to resolve this issue? Similar things would happen for 4-nodes motifs and so on...

The code I used goes like: import numpy M1 = DiGraph(numpy.array([[0,1,0],[0,0,1],[0,0,0]])) #first motif M5 = DiGraph(numpy.array([[0,1,1],[0,0,1],[0,0,0]])) #second motif g = digraphs.RandomDirectedGNP(20,0.1) #a random network l1 = [] for p in g.subgraph_search_iterator(M1): #search first motif l1.append(p) #make a list of its occurences l5 = [] for p in g.subgraph_search_iterator(M5): #the same for the second motif l5.append(p)

I'm counting the number of motifs (3-nodes isophormic class of connected subgraphs) in a random directed network. There are 13 of this. One is, for example S1={1 -> 2, 2 -> 3} and another one S2={1 -> 2, 2 -> 3, 1 -> 3}. They are two distinct motifs, and I wouldn't count a S1 when I actually find S2. The problem is that S1 is in S2, hence subgraph_search() finds a S1 in each S2 and all related functions inherit the problem (wrong counting, wrong iterator...).

Any idea how to resolve this issue? Similar things would happen for 4-nodes motifs and so on...

The code I used goes like: like:

import numpy
M1 = DiGraph(numpy.array([[0,1,0],[0,0,1],[0,0,0]])) #first motif
M5 = DiGraph(numpy.array([[0,1,1],[0,0,1],[0,0,0]])) #second motif
g = digraphs.RandomDirectedGNP(20,0.1) #a random network
l1 = []
for p in g.subgraph_search_iterator(M1): #search first motif
  l1.append(p) #make a list of its occurences
l5 = []
for p in g.subgraph_search_iterator(M5): #the same for the second motif
  l5.append(p)
l5.append(p)