An EventGraph with tests

[vineetbansal]

Introduced an EventGraph class with tests to illustrate basic functionality. EventGraph is a pathpyG Graph so in addition to being constructed from a TemporalGraph, it is capable of being constructed directly from a torch_geometric.data.Data object.

Essentially the usage might be:

  tg = TemporalGraph.from_edge_list([
      ("a", "b", 1),
      ("b", "c", 2),
      ("b", "d", 5),
      ("c", "e", 3),
  ])

  eg = EventGraph.from_temporal_graph(tg, delta=2)

  print(eg)                    # EventGraph (delta=2) ... one line per event, like a->b@1
  print(eg.num_events)         # 4  (one per temporal edge)
  print(eg.num_fo_nodes)       # 5  (a, b, c, d, e)

  print(eg.event_endpoints(0)) # ('a', 'b', 1)
  print(eg[0])                 # same thing
  print(eg.continuations(0))   # [(1, 1)]  -> event 1, with a time gap of 1

  dist, pred = eg.shortest_paths()
  print(dist[eg.fo_mapping.to_idx("a"), eg.fo_mapping.to_idx("e")])  # 3.0

  tg_back = eg.to_temporal_graph()
  
  # This is not part of this PR, but can be added easily.
  model = MultiOrderModel.from_event_graph(event_graph, max_order=2)

A couple of things to discuss:

• If an EventGraph is constructed from a TemporalGraph and the TemporalGraph is later changed by the caller, should the EventGraph change as well? Right now we don't - eg._temporal_graph = TemporalGraph(g.data.clone(), mapping=g.mapping). This seems to me like the right thing to do.

• eg.shortest_paths works, but creates a TemporalGraph (if it doesn't exist) to pass on to temporal_shortest_paths. This seems wasteful if EventGraph was constructed from Data and doesn't need all the TemporalGraph machinery. Perhaps temporal_shortest_paths can be tweaked to work with a pre-computed edge-index (as would be the case if EventGraph is constructed directly from torch_geometric.data.Data).

  • Change signature to temporal_shortest_paths(g: TemporalGraph | None, eg: "EventGraph" | None, delta: int). Add methods to EventGraph/TemporalGraph that call this function under the hood.

Some changes in other files were for my understanding of the code by adding comments, and are unrelated to the PR.

[vineetbansal]

Closing this in favor of an upcoming PR originating from this repo.