[graph-tool] Accessing a compressed matrix is super slow!

Hang Mang gucko.gucko at googlemail.com
Fri Mar 21 12:15:55 CET 2014


Hi, I found that accessing a compressed matrix is really slow. I'm 
computing a similarity index called LHN1, it took 34 seconds to compute 
when I access the 'paths' variable/matrix. But when I converted paths to 
paths.asarray() it only took 11 seconds. So now I'm really ending up 
calling toarray() all over my code. I'm not sure of why using compressed 
matrices in the first place or how I could overcome this! Forget about the get_degrees_dic() 
for now.

Here's my code:

def lhn1(graph):

    A = gts.adjacency(graph)

    paths = A**2

    paths = paths.toarray()

    S = np.zeros(A.shape)

    degrees = get_degrees_dic(graph)

    for i in xrange(S.shape[0]):

        for j in xrange(S.shape[0]):

            i_degree = degrees[i] #graph.vertex(i).out_degree()

            j_degree = degrees[j] #graph.vertex(j).out_degree()

            factor = i_degree * j_degree

            S[i,j] = (1.0/factor) * paths[i,j]

    return S
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