NetworkZ is a library of graph algorithms in Python. It is an extension of the NetworkX. It contains (by import) everything that is in NetworkX, plus some additional algorithms that were submitted into NetworkX but not merged yet. Currently, NetworkZ contains the following additional algorithms:
- Rank-maximal matching: by Oriya Alperin, Liel Vaknin and Amiel Lejzor.
- Social-aware coalition formation - by Victor Kushnir.
pip install networkz
This installs the latest version of networkx, and the new algorithms added in networkz.
A rank-maximal matching is a matching that maximizes the number of agents who are matched to their 1st priority; subject to that, it maximizes the number of agents matched to their 2nd priority; and so on.
import networkz as nx
G = nx.Graph()
G.add_nodes_from(["agent1", "agent2"], bipartite=0)
G.add_nodes_from(["product1", "product2"], bipartite=1)
G.add_weighted_edges_from([("agent1", "product1", 1), ("agent1", "product2", 1), ("agent2", "product2", 2)])
matching = nx.rank_maximal_matching(G, rank="weight")
print(matching)
See demo website for more information.
Maximum-weight fractional matching is a graph optimization problem where the goal is to find a set of edges with maximum total weight, allowing for fractional inclusion of edges.
import networkz as nx
G = nx.Graph()
G.add_nodes_from(["a1", "a2"])
G.add_edge("a1", "a2", weight=3)
F = nx.maximum_weight_fractional_matching(G)
print(F)
(TODO)
Any additions or bug-fixes to networkx should first be submitted there, according to the NetworkX Contributor Guide.
If the pull-request is not handled, you are welcome to submit it here too.