Function parallel_louvain_communities_result 

pub fn parallel_louvain_communities_result<N, E, Ix>(
    graph: &Graph<N, E, Ix>,
    max_iterations: usize,
) -> CommunityResult<N>
where
    N: Node + Send + Sync + Clone + Hash + Eq + Debug,
    E: EdgeWeight + Into<f64> + Send + Sync + Copy,
    Ix: IndexType + Send + Sync,

Detects communities using parallel Louvain method (modern API)

This function returns the standardized CommunityResult type that provides multiple ways to access the community structure. Uses parallel processing to accelerate community detection on large graphs.

Arguments

• graph - The undirected graph to analyze
• max_iterations - Maximum number of optimization iterations

Returns

• A CommunityResult with community structure from parallel Louvain

Time Complexity

O(m * log n / p) where m is the number of edges, n is the number of nodes, and p is the number of parallel threads. Actual speedup depends on graph structure.

Space Complexity

O(n) for storing community assignments and auxiliary data structures.

Example

// This requires the "parallel" feature to be enabled
use scirs2_graph::{Graph, parallel_louvain_communities_result};

let mut graph: Graph<i32, f64> = Graph::new();
// ... add nodes and edges ...
let result = parallel_louvain_communities_result(&graph, 50);

println!("Parallel Louvain modularity: {:.4}", result.quality_score.unwrap_or(0.0));
println!("Found {} communities", result.num_communities);