Idea: a generalization of the SIR functions

This is just an idea (I won’t be working on it due to other priorities).

igraph has some very basic stochastic SIR modelling functionality.

It would be a cool extension to have a function which runs a similar stochastic model on an arbitrary network, but with an arbitrary number of species (instead of S, I, R) and arbitrary transitions between them, which can also be encoded as a weighted directed network (now we have S --beta--> I and I --gamma--> R). It should allow retrieving individual node states.

Of course, there should be similar (and much more flexible) tools already. Perhaps this? https://github.com/biomathman/pycellerator But I expect they don’t work on a network. They probably consider all-to-all interactions.