@graphty/algorithms/dist/src/clustering/spectral.d.ts

Graph algorithms library for browser environments implemented in TypeScript

import type { Graph } from "../core/graph.js";
import type { NodeId } from "../types/index.js";
/**
 * Spectral Clustering implementation
 *
 * Uses eigenvalues and eigenvectors of the graph Laplacian matrix to perform clustering.
 * Particularly effective for finding non-convex clusters and communities in graphs.
 *
 * Time complexity: O(V³) for eigendecomposition
 * Space complexity: O(V²)
 */
export interface SpectralClusteringOptions {
    k: number;
    laplacianType?: "unnormalized" | "normalized" | "randomWalk";
    maxIterations?: number;
    tolerance?: number;
}
export interface SpectralClusteringResult {
    communities: NodeId[][];
    clusterAssignments: Map<NodeId, number>;
    eigenvalues?: number[];
    eigenvectors?: number[][];
}
/**
 * Perform spectral clustering on a graph
 *
 * @warning This implementation uses simplified power iteration for eigenvector
 * computation with approximate eigenvalues. For production use cases requiring
 * precise clustering, consider using a proper linear algebra library like ml-matrix.
 *
 * The approximate eigenvalues (0.1, 0.2 for second and third eigenvectors) work
 * well for most graph structures but may produce suboptimal results for graphs
 * with unusual spectral properties.
 */
export declare function spectralClustering(graph: Graph, options: SpectralClusteringOptions): SpectralClusteringResult;
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