communities 2.1.0

Library of algorithms for detecting communities in graphs

communities

communities is a collection of community detection algorithms for graphs. It provides the following algorithms:

1. Louvain's modularity
2. Girvan-Newman
3. Hierarchical clustering (TODO)
4. Minimum cut (TODO)

Installation

communities can be installed with pip:

$ pip install communities

Getting Started

Each algorithm expects an adjacency matrix representing an undirected graph. This matrix can either be left-triangular or symmetric. To get started, just import the algorithm you want to use from communities.algorithms, like so:

from communities.algorithms import girvan_newman

adj_matrix = [...]
communities = girvan_newman(adj_matrix)

The output of each algorithm is a list of communities, where each community is a set of nodes.

API

communities.algorithms

louvain_modularity(adj_matrix : list, size : int = None) -> list

girvan_newman(adj_matrix : list, size : int = None) -> list

communities.utilities

is_left_triangular(adj_matrix : list) -> bool

`symmetrize_matrix(adj_matrix : list) -> list

`binarize_matrix(adj_matrix : list, threshold : float = 0.0) -> list

`create_intercommunity_graph(adj_matrix : list, communities : list, aggr : Callable = sum) -> list