Graphology Communities

WARNING : The content of this repository has been split and transferred to :

• graphology/graphology-communities-louvain
• graphology-metrics

Miscellaneous metrics and algorithms around community detection to be used with graphology.

Installation

npm install graphology-communities

Usage

Metrics

• Modularity

Algorithms

• Louvain

Modularity

Compute the modularity, given the graph and a partitioning

import {modularity} from 'graphology-communities';
// Alternatively, to load only the relevant code:
import modularity from 'graphology-communities/modularity';

const Q = modularity(graph, {'1': 0, '2': 0, '3': 1, '4': 1, '5': 1});

Arguments

• graph Graph: target graph.
• partitioning Object: object mapping a community index to a object.
• options ?object: options:
  • attributes ?object: attributes' names:
    • weight ?string [weight]: name of the edges' weight attribute.

Louvain

Execute the Louvain algorithm to detect a good partitioning of the graph in several communities. The original publication of the algorithm can be found there.

import {louvain} from 'graphology-communities';
// Alternatively, to load only the relevant code:
import louvain from 'graphology-communities/louvain';

const partitioning = louvain(graph); // Return a mapping object like {'1': 0, '2': 0, ..., 5: '1'}
// To directly map the result to nodes' attributes
louvain.assign(graph); // By default, assigned to the `community` attribute
lovuain.assign(graph, {attributes: {community: 'foo'}}); // Assigned to the `foo` attribute

Arguments

• graph Graph: graph to which you want to get the best partitioning.
• options ?object: options:
  • attributes ?object: attributes' names:
    • weight ?string [weight]: name of the edges' weight attribute.
    • community ?string [community]: name of the node attribute holding community information