Thanks to Guido van Rossum for the idea of using Python for implementing a graph data structure http://www.python.org/doc/essays/graphs.html
Thanks to David Eppstein for the idea of representing a graph G so that “for n in G” loops over the nodes in G and G[n] are node n’s neighbors.
Thanks to the following people who have made contributions to NetworkX:
- Katy Bold contributed the Karate Club graph
- Hernan Rozenfeld added dorogovtsev_goltsev_mendes_graph and did stress testing
- Brendt Wohlberg added examples from the Stanford GraphBase
- Jim Bagrow reported bugs in the search methods
- Holly Johnsen helped fix the path based centrality measures
- Arnar Flatberg fixed the graph laplacian routines
- Chris Myers suggested using None as a default datatype, suggested improvements for the IO routines, added grid generator index tuple labeling and associated routines, and reported bugs
- Joel Miller tested and improved the connected components methods and bugs and typos in the graph generators
- Keith Briggs sorted out naming issues for random graphs and wrote dense_gnm_random_graph
- Ignacio Rozada provided the Krapivsky-Redner graph generator
- Phillipp Pagel helped fix eccentricity etc. for disconnected graphs
- Sverre Sundsdal contributed bidirectional shortest path and Dijkstra routines, s-metric computation and graph generation
- Ross M. Richardson contributed the expected degree graph generator and helped test the pygraphviz interface
- Christopher Ellison implemented the VF2 isomorphism algorithm
- Eben Kennah contributed the strongly connected components and DFS functions.
- Sasha Gutfriend contributed edge betweenness algorithms