class _tacoma.edge_trajectories

Instead of getting lists of edges ordered in time, this description of a temporal network consists of a list of _tacoma.edge_trajectory_entry. Each entry contains the edge and a list of time pairs denoting the times the edge exists.

Optionally, dependent on the function which created this object, this object can contain edge similarities, which are defined as follows. Each edge \(i\), where \(i\) is the edge’s index in the trajectory list, is considered similar to edge \(j\) if both are connected to the same node at the same time. Hence, if both \(i=(u,v)\) and \(j=(u,w)\) have node \(u\) in common, their similarity is

\[E_{ij} = \int\limits_0^{t_{\mathrm{max}}}dt\ A_{uv}(t)A_{uw}(t)\]
__init__(self: _tacoma.edge_trajectories) → None




N Number of nodes
edge_similarities Each entry of this list is a triple (i, j, w), where i is the i-th edge in trajectories (similarly for j) and w is their similarity.
int_to_node A dictionary int -> string which keeps the original node names.
notes A string containing additional notes for this network.
t0 The initial time
time_unit A string containing the unit of time for this network.
tmax The final time
trajectories Each entry of this list has properties .edge containing its nodes and .time_pairs containing the time intervals when the edge was active.