This is an implementation of the Gómez-Gardeñes & Moreno network model, intended for general-purpose usage.
Feel free to use and/or contribute to this repository. In the near future, we should have a Python interface and routines to export the resulting network into several different formats.
You can simply run the following. Suppose you want 10000 nodes, with increasing 10 connections per iteration and mixing probability of 1.0 (pure Erdos-Renyi).
make
time ./ggmModel $RANDOM 10000 10 1.0 output.dat
This will construct a network and output all degrees in output.dat.
Sample output:
[user@PC C++]$ time ./ggmModel $RANDOM 10000 10 1.0 output.dat
real 0m0.418s
user 0m0.102s
sys 0m0.316s
This is a free software under a somewhat permissive license (MIT). Please refer to LICENSE file in this repository for details.