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## [igraph] Inconsistency problems with large 19 million edges graph (prope

 From: Stefano Scerra Subject: [igraph] Inconsistency problems with large 19 million edges graph (proper email) Date: Sun, 5 Apr 2015 19:17:52 +0200

(Sorry for accidentally double posting)
Hello,
I'm having a really strange problem with the library and I was hoping 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.

I try to load the graph in two different ways, by using Graph.Read_Ncol, and by manually reading the edgelist and then using Graph.TupleList. In both cases, iterating on the graph's edge sequence (the es attribute) yields inconsistent results: for instance, the nonexisting edge 10->11 is returned.

I'm using igraph 0.7.1-4 on Python 3.4.3 64 bit on Windows 7 SP1 64 bit
`from igraph import Graphimport csvimport timeitdef create_graph(file_graph):    # load graph using Graph.Read_Ncol    with open(file_graph, "r") as in_file:        g = Graph.Read_Ncol(in_file, weights=False, directed=True)        return gdef create_graph2(file_graph):    # load graph using Graph.TupleList    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 Graph.TupleList(edges=edges, directed=True)def generate_weighted_graph(input, output):    g = create_graph2(input)    print("ecount:", g.ecount(), "vcount:", g.vcount())    with open(output, "w") as output_file:        writer = csv.writer(output_file, delimiter=" ")        for e in g.es:            i, j = e.source, e.target            writer.writerow([i, j])if __name__ == "__main__":    generate_weighted_graph("C:/datasets/network", "C:/datasets/network_weighted")`