single-clustering

A Rust library for community detection and graph clustering algorithms.

Features

• Network Analysis: Efficient graph representation and manipulation for clustering tasks
• Community Detection: Implementation of state-of-the-art algorithms
  • Louvain method for community detection
  • Leiden algorithm (enhanced version of Louvain)
• Flexible Grouping: Abstract trait system for creating and managing node clusters
• Performance: Parallel computation support via Rayon
• K-NN Graph Creation: Build networks from high-dimensional data points

Usage

use single_clustering::network::Network;
use single_clustering::network::grouping::VectorGrouping;
use single_clustering::community_search::leiden::Leiden;

// Create a network from your data
let network = Network::new_from_graph(graph);

// Initialize clustering (each node in its own cluster)
let mut clustering = VectorGrouping::create_isolated(network.nodes());

// Run Leiden algorithm (resolution parameter, randomness parameter, optional seed)
let mut leiden = Leiden::new(1.0, 0.01, Some(42));
leiden.iterate(&network, &mut clustering);

// Access clustering results
for node in 0..network.nodes() {
    println!("Node {} belongs to cluster {}", node, clustering.get_group(node));
}

Installation

Add this to your Cargo.toml:

[dependencies]
single-clustering = "0.1.0"

Performance Considerations

The library offers multiple implementations optimized for different scenarios:

• StandardLocalMoving: Basic implementation of the moving algorithm
• FastLocalMoving: Optimized version with better memory usage
• Parallel implementations of various operations for large networks

License

This crate is licensed under the MIT License.