cdlib.algorithms.tiles

tiles(dg: object, obs: int = 1) → cdlib.classes.temporal_clustering.TemporalClustering

TILES is designed to incrementally identify and update communities in stream graphs. This implementation assume an explicit edge removal when pairwise interactions cease to exist.

Supported Graph Types

Undirected Directed Weighted
Yes No No
Parameters:
  • dg – dynetx graph object
  • obs – community observation interval (default=1)
Returns:

TemporalClustering object

Example:
>>> from cdlib import algorithms
>>> import dynetx as dn
>>> dg = dn.DynGraph()
>>> for x in range(10):
>>>     g = nx.erdos_renyi_graph(200, 0.05)
>>>     dg.add_interactions_from(list(g.edges()), t=x)
>>> coms = algorithms.tiles(dg, 2)
References:

Rossetti, Giulio; Pappalardo, Luca; Pedreschi, Dino, and Giannotti, Fosca. `Tiles: an online algorithm for community discovery in dynamic social networks.<https://link.springer.com/article/10.1007/s10994-016-5582-8>`_ Machine Learning (2016), 106(8), 1213-1241.