Function degree_correlation_vector 

pub fn degree_correlation_vector(
    graph: &Graph,
    from_mode: DegreeMode,
    to_mode: DegreeMode,
    directed_neighbors: bool,
    weights: Option<&[f64]>,
) -> IgraphResult<Vec<f64>>

Compute the degree correlation function k_nn(k).

For each degree value d, computes the weighted average degree of vertices connected to by vertices of degree d. The result vector is indexed by degree: result[d] = mean neighbor degree for source degree d.

• from_mode: how to measure source vertex degree (Out/In/All).
• to_mode: how to measure target vertex degree (Out/In/All).
• directed_neighbors: if true, only follow edge direction (u→v). If false, treat edges as reciprocal (both u→v and v→u counted). Ignored for undirected graphs.
• weights: optional edge weights. If None, all weights are 1.

Returns a vector of length max_from_degree + 1. Entries for degrees with no edges will be f64::NAN.

Examples

use rust_igraph::{Graph, DegreeMode, degree_correlation_vector};

// Star graph: center has degree 4, leaves have degree 1
let mut g = Graph::with_vertices(5);
g.add_edge(0, 1).unwrap();
g.add_edge(0, 2).unwrap();
g.add_edge(0, 3).unwrap();
g.add_edge(0, 4).unwrap();
let knnk = degree_correlation_vector(
    &g, DegreeMode::All, DegreeMode::All, false, None,
).unwrap();
// k_nn(1) = 4.0 (leaves connect to center with deg 4)
assert!((knnk[1] - 4.0).abs() < 1e-10);
// k_nn(4) = 1.0 (center connects to leaves with deg 1)
assert!((knnk[4] - 1.0).abs() < 1e-10);