Changes from v 1.0

New in v 1.0.1

Returning transmission chains

When simulations have return_full_data=True, the returned object now includes information on who infected whom at each time. This can be accessed through:

transmissions which returns a list of tuples (t,u,v) stating that node u infected node v at time t.

transmission_tree which returns a directed multi graph where an edge from u to v with attribute ‘time’ equal to t means u infected v at time t.

(note that in an SIS epidemic, this “tree” may have cycles and repeated edges)

(addresses issue 21 )

Non-SIS/SIR processes

It is now possible to run a wide range of non-SIS/SIR processes spreading in a network. These processes include competing diseases, SIRS disease, SEIR disease, and quite a few other options. This is done using:

Gillespie_Arbitrary.

Examples are here.

Currently this does not accept return_full_data=True, and it requires that the events all occur as Poisson processes (that is, it makes sense to say that there is a rate at which things happen, and that rate depends on the status of the nodes and perhaps some property of the node or the partnership, but nothing else).

(addresses issues 13 & 17)

New in v 1.0.2

No changes (I accidentally made a typo just before uploading v1.0.1 to pypi and I can’t reupload with the same name).

New in v 1.0.3

No changes to package, but a small change attempting to get readthedocs to correctly build.

New in v 1.0.4rc2

No changes to package, but fixing a problem I had missed with readthedocs failing to provide documentation for each function.