Package Guide

The idea is to define some jumps (discrete state, continuous time, stochastic variables) for the vertices and for edges of an arbitrary Graph, and the package functionality returns a JumpSet which can be solved with JumpProcesses.jl and DifferentialEquations.jl.

The important functions are:

1. network_jump_set: creates the JumpSet given a Graph, the jumps defined for vertices (vertex_reactions), and the jumps defined for edges, (edge_reactions). These last two can be each a vector of jumps, in which case all vertices or edges behave according to to the same reactions. An other option is that one or both is a vector of vectors. In this case the outer vector should have the same number of elements as vertices (vertex_reactions) or edges (edge_reactions) in the graph.
2. dependency_graph, vartojumps, jumptovars: these create the dependency graphs necessary for some aggregators.

As in JumpProcesses.jl, the jumps are defined by a rate and affect! function. The rate returns a single number, while affect! modifies the arguments directly. In the case of a vertex the input arguments for both are

• v: state of the vertex itself
• nhgbs: state of the neighbours
• p: model parameter values
• t: current time step

In case of an edge the arguments are (vs, vd, p, t) where vs resp. vd are the source and destination vertex states.