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[igraph] Inconsistency problems with large 19 million edges graph

From: Stefano Scerra
Subject: [igraph] Inconsistency problems with large 19 million edges graph
Date: Sun, 5 Apr 2015 18:39:12 +0200

I'm having a really strange problem with the library and I hope to get some advice.
After loading a large 19 million edges graph, the library returns an inconsistent edge list.
More precisely, nonexistent edges appear in the graph's edge sequence attribute.

Link to dataset: https://drive.google.com/open?id=0B_wZDWWn4C1RdDhIbXlDRWFLd0E&authuser=0

def create_graph(file_graph):

with open(file_graph) as in_file:
g = igraph.Graph.Read_Ncol(in_file, weights=False, directed=True)
return g

def create_graph2(file_graph):
edges = []
with open(file_graph, "r") as in_file:
reader = csv.reader(in_file, delimiter=" ")
i = 0
for row in reader:
if row:
edges.append([int(row[0]), int(row[1])])
i += 1
if i % 100000 == 0: print(i)
return igraph.Graph.TupleList(edges=edges, directed=True)

def generate_weighted_graph(input, output):
g = create_graph2(input)
print("ecount:", g.ecount(), "vcount:", g.vcount())
k = 0
with open(output, "w") as output_file:
writer = csv.writer(output_file, delimiter=" ")
for e in g.es:
i, j = e.tuple[0], e.tuple[1]
j_in = set(g.neighbors(j, mode="IN"))
i_out = set(g.neighbors(i, mode="OUT"))
n = len(j_in.intersection(i_out))
weight = n / (len(i_out)-1 + len(j_in) - n)
writer.writerow([i, j, weight])
if k % 1000 == 0:
print(k, i, j, weight)
k += 1

if __name__ == "__main__":
generate_weighted_graph("C:/datasets/ff", "C:/datasets/ff_weighted")

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