图匹配算法

Question

I've been searching for graph matching algorithms written in Python but I haven't been able to find much.

I'm currently trying to match two different graphs that derive from two distinct sets of character sequences. I know that there is an underlying connection between the two graphs, more precisely a one-to-one mapping between the nodes. But the graphs don't have the same labels and as such I need graph matching algorithms that return nodes mappings just by comparing topology and/or attributes. By testing, I hope to maximize correct matches.

I've been using Blondel and Heymans from the graphsim package and intend to also use Tacsim from the same package. I would like to test other options, probably more standard, like maximum subgraph isomorphism or finding subgraphs with very good matchings between the two graphs. Graph edit distance might also help if it manages to give a matching.

The problem is that I can't find anything implemented, even in Networkx that I'm using. Does anyone know of any Python implementations? Would be a plus if those options used Networkx.

Answer 1

I found this implementation of Graph Edit Distance algorithms which uses NetworkX in Python.

https://github.com/Jacobe2169/GMatch4py

"GMatch4py is a library dedicated to graph matching. Graph structure are stored in NetworkX graph objects. GMatch4py algorithms were implemented with Cython to enhance performance."