epydemic is a library for simulating epidemic (and other)
processes over complex networks (and other combinatorial structures).
Network science uses epidemic spreading processes a lot, both for the
obvious application of modelling diseases, but also for things that
are mathematically similar such as computer viruses and
rumour-spreading. Some simulations use discrete-time approaches where
lots of events happen in a single timestep; others — and this is more
common for research-grade software — use continuous-time stochastic or
Gillespie simulation, which can be significantly faster and is
statistically exact, but is also a lot harder to code up. There didn’t
seem to be a reusable simulation library that would play well with
NetworkX, so I wrote one in the
course of writing my complex networks blog/book.
this code from the book and allows it to be used stand-alone. For good
measure I integrated it with epyc
to allow for reproducible simulations at scale.
Recent articles about
- Friday 2 December, 2022 Notes on using Jupyter in the cloud
- Monday 6 December, 2021 Talk at UK Systems on unit testing stochastic code
- Thursday 10 June, 2021 Generating functions for epydemic
- Friday 14 May, 2021 New, faster, release of epydemic
- Saturday 19 December, 2020 A talk on “Exploring epidemic spreading using network models”