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.

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.