Bipartite network generator
Generates a random bipartite network with prescribed degree distribution for both sets. Both distributions must be provided to the program and be consistent (number of top links=number of bottom links). Typical use of the generator (using distributions generator) might be:
./distributions -u -m 1 -M 10 -n 100 -s 500 > top_distrib
./distributions -p -2.2 -m 1 -M 100 -n 200 -s 500 > bottom_distrib
./random_bipartite -t top_distrib -b bottom_distrib > bn_test
Which generates a random bipartite network with a top uniform degree distribution and a bottom power law distribution.
As described in the paper Bipartite Graphs as Models of Complex Networks., this model is particularly well suited to the modeling of most complex network. In particular if one choose a top degree distribution to be a Poisson law, and the bottom one to be a power law, the generated network have a small average distance, a high clustering and a power law distribution of degrees.
Erdos-Renyi network generator
Generates a random Erdos-Renyi network, with either a given connection probability or a given number of links.
Configuration model network generator
Generates a random network with a prescribed degree distribution using the configuration model.
Albert-Barabasi network generator
Generates a random Albert-Barabasi network with a given core size and a given number of links per new node.