import { Graph } from '../../../algorithms/graph/graph.js';
import { Edge, Node } from '../../../algorithms/types/graph.js';
/**
 * Structural feature vector extracted from a single graph.
 *
 * All features are deterministic given the same graph structure.
 */
export interface GraphFeatures {
    /** Total number of nodes */
    nodeCount: number;
    /** Total number of edges */
    edgeCount: number;
    /** Mean node degree */
    meanDegree: number;
    /** Standard deviation of node degrees */
    stdDegree: number;
    /** Maximum node degree */
    maxDegree: number;
    /** Minimum node degree */
    minDegree: number;
    /** Third standardised moment of the degree distribution */
    degreeSkewness: number;
    /** Global clustering coefficient (fraction of closed triangles) */
    clusteringCoefficient: number;
    /** Edge density: 2|E| / (|V|(|V|-1)) for undirected graphs */
    density: number;
    /** Degree assortativity: Pearson correlation of degrees at edge endpoints */
    degreeAssortativity: number;
}
/** Ordered list of feature names matching the feature vector layout. */
export declare const FEATURE_NAMES: ReadonlyArray<keyof GraphFeatures>;
/**
 * Convert a GraphFeatures object to a numeric array in canonical order.
 * @param features
 */
export declare const featuresToVector: (features: GraphFeatures) => number[];
/**
 * Extract structural features from a graph.
 *
 * For clustering coefficient: for each node, counts edges between its
 * neighbours (triangles) divided by the number of possible triangles.
 *
 * For degree assortativity: computes Pearson correlation of degrees at
 * both endpoints of every edge.
 *
 * @param graph - The graph to extract features from
 * @returns A GraphFeatures object with all computed metrics
 */
export declare const extractFeatures: <N extends Node, E extends Edge>(graph: Graph<N, E>) => GraphFeatures;
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