oxygraph

oxygraph is a Rust library to analyse bipartite graphs, and implements several algorithms along with visualisations.

There is functionality to: - Visualise bipartite graphs and their derivatives, as well as interaction matrices. - Compute basic statistics on bipartite graphs and interaction matrices. - Create random bipartite graphs through the Erdös-Rényi process. - Algorithms for computing nestedness, and modularity.

The bipartite graphs are a thin wrapper over petgraph graphs, and the interaction matrices are two dimensional ndarrays.

As the wrappers are thin, implementation of new metrics/algorithms should be straightforward.

An example which illustrates initiation of the graph from a TSV:

```rust // main bipartite graph struct use oxygraph::BipartiteGraph; // Enum for which strata there are in a bipartite graph use oxygraph::bipartite::Strata; // Interaction matrix struct use oxygraph::InteractionMatrix; // LPAWB+ algorithm use oxygraph::modularity::lpawbplus;

// read in some data // in the format: // from to weight // 0 1 1.0 // etc ... let bpgraph = BipartiteGraph::fromdsv("path/to/tsv", b'\t').unwrap(); // is the graph bipartite? let strata = bpgraph.isbipartite();

match stata { Strata::Yes(map) => println!("{:?}", map), // tell the user which nodes are the offenders. Strata::No => { panic!("Uh oh, your graph isn't bipartite!"); } }

// basic stats println!("{:?}", bpgraph.stats());

// calculate NODF let mut im = InteractionMatrix::from_bipartite(bpgraph); println!("{}", im.nodf().unwrap());

// make a random bipartite graph let randgraph = BipartiteGraph::random(80, 100, 250).unwrap(); let mut imrand = InteractionMatrix::frombipartite(randgraph); // and calculate modularity let modularity = lpawbplus(rand_graph, None); println!("{:?}", modularity);

```