add a little bit of documentation to understand the d_graph detection code

deconvolve.py

@@ -46,12 +46,25 @@ def get_communities(G):
     # Extract communites from all the possible d-graphes in the neighborood.
 
 
+""" This function take two cliques in the graph G and try to find if they are 2 halfes of a d-graph.
+    1 - The algorithm compute overlapp between nodes from first clique to the second and from the
+    second to the first.
+    2 - Filter the clique pairs that have less than n*(n-1)/2 traversing edges (necessary critera
+    to be considered as d-graph).
+    3 - Find the node order in the half d-graphs by sorting nodes by traversing order.
+    4 - return a paair of half d-graph ordered from the central node (not present in G).
+    @param cliq1 (resp clq2) the clique that is candidate to be composed of half of the d-graph nodes.
+    @param G the graph of the neighbors of the central node (not present).
+    @return A pair of lists that are the 2 halves of the d-graph ordered from the center.
+"""
 def compute_d_graph(clq1, clq2, G):
     # Compute the arities between the cliques
     arities1 = {name:0 for name in clq1}
     arities2 = {name:0 for name in clq2}
     sum_edges = 0
 
+    min_clq_size = min(len(clq1), len(clq2))
+
     # Compute link arities
     for node1 in clq1:
         neighbors = list(G.neighbors(node1))
@@ -64,7 +77,7 @@ def compute_d_graph(clq1, clq2, G):
                 sum_edges += 1
 
     # Reject if not enought edges
-    if sum_edges < len(clq1) * (len(clq1)-1) / 2:
+    if sum_edges < min_clq_size * (min_clq_size-1) / 2:
         return None
 
     print(clq1, clq2)