angel(g_original: object, threshold: float, min_community_size: int = 3) → cdlib.classes.node_clustering.NodeClustering¶
Angel is a node-centric bottom-up community discovery algorithm. It leverages ego-network structures and overlapping label propagation to identify micro-scale communities that are subsequently merged in mesoscale ones. Angel is the, faster, successor of Demon.
Supported Graph Types
Undirected Directed Weighted Yes No No Parameters:
- g_original – a networkx/igraph object
- threshold – merging threshold in [0,1].
- min_community_size – minimum community size, default 3.
>>> from cdlib import algorithms >>> import networkx as nx >>> G = nx.karate_club_graph() >>> coms = algorithms.angel(G, min_com_size=3, threshold=0.25)
- Rossetti, Giulio. “Exorcising the Demon: Angel, Efficient Node-Centric Community Discovery.” International Conference on Complex Networks and Their Applications. Springer, Cham, 2019.
Reference implementation: https://github.com/GiulioRossetti/ANGEL