Network Properties calculation speed problem about teneto

[hexie1995]

Also, I dont quite understand the example you have on your website:
G = np.random.beta(1, 1, [5,5,3])
this will give me a 5x5x3 array, and I am not sure exactly what is the structure of the edgelist here because it is not in the format of "i j t".

However, if i try to calculate the shortest path by generating G= np.random.beta(1,1,[50,50,3]), the algorithm is really fast to calculate that, usually finishes within two minutes. But when I try to do the exact same calculation of shortest path but with a different input network I created myself, and let tnet be created from edgelist, it is extremely slow. Could you walk me through as why this is the case and what can I do to improve this?

tnet = TemporalNetwork(from_edgelist=A_tr_list, nettype='bd', diagonal=True)

[wiheto]

Known issue. #74. Whenever I have time to fix it, I will. All shortest paths outside of toy examples will take a long time to run cause of inefficient code when I tried to improve the algorithm.

Unfortunately, I am completely swamped with other obligations and have been unable to find a week in the last year where I can spend my free time fixing this as currently teneto is not supported under any research grant.

If critical, downgrade to the version where the algorithm runs quicker (I think 0.3.5 is the latest version), whenever betweenness centrality was added then the alg was made slower.

There are different network representations allowed. Array form and edgelist. See documentation.

[wiheto]

It is 0.3.5 when the alg is quicker. So I recommend using that if you need it. Again, I am sorry. When I have time to fix it, I will.