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[igraph] Understanding Barabasi Function and how to simulate a scale fre

From: Daniele Capocefalo
Subject: [igraph] Understanding Barabasi Function and how to simulate a scale free()
Date: Mon, 24 Apr 2017 12:13:18 +0200
User-agent: Mozilla/5.0 (X11; Linux x86_64; rv:45.0) Gecko/20100101 Thunderbird/45.8.0

Hello Everone,

(I'll try to send this mail again since I'm not sure whether has been received by the mailing list or not)

I have one question regarding the Barabasi Function in GraphBase (python). The "m" parameter states

"either the number of outgoing edges generated for each vertex or a list containing the number of outgoing edges for each vertex explicitly"

It isn't clear whether this m implies the average degree of the scale free network or something else. Additionally, since it clearly states "outgoing edges", do I need to convert the network to undirect after calling the Barabasi() method?

Moreover, I need to simulate several scale free networks that "mirrors" real networks I'm studying. To this extent, I was searching for a function or an algorithm to infer the exponential parameter for the power law. does igraph for python offer something like this? Alternatively, could I use the average degree of the real networks and give it to the Barabasi() function when defining "m"?

Thanks a lot for your time!



Daniele Capocefalo
Bioinformatics unit
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