Struct LinkStream 

pub struct LinkStream {
    pub edges: Vec<TemporalEdge>,
    pub nodes: Vec<usize>,
    pub time_start: f64,
    pub time_end: f64,
}

A continuous-time temporal network represented as a link stream.

Fields

edges: Vec<TemporalEdge>

All temporal edges in the stream.

nodes: Vec<usize>

All node identifiers present in the stream.

time_start: f64

Start of the observation window.

time_end: f64

End of the observation window.

Implementations

impl LinkStream

pub fn new(time_start: f64, time_end: f64) -> Self

Create an empty link stream over the interval [time_start, time_end].

pub fn add_edge(&mut self, src: usize, dst: usize, start: f64, end: f64)

Add a temporal edge; both endpoints are registered as nodes if absent.

pub fn degree_at(&self, u: usize, t: f64) -> usize

Instantaneous degree of node u at time t.

pub fn average_degree(&self, u: usize, n_samples: usize) -> f64

Time-averaged degree of node u, estimated by uniform sampling.

n_samples controls accuracy; higher values reduce discretisation error.

pub fn contact_duration(&self, u: usize, v: usize) -> f64

Total contact time between nodes u and v.

pub fn inter_contact_times(&self, u: usize, v: usize) -> Vec<f64>

Vector of gap durations between successive contacts of u and v.

Contacts are sorted by start time; the gap is the time between the end of one contact and the start of the next. Negative gaps (overlapping contacts) are excluded.

pub fn clustering_coefficient_at(&self, u: usize, t: f64) -> f64

Local temporal clustering coefficient of node u at time t.

Defined as the fraction of pairs among u’s neighbours that are themselves connected at time t.

pub fn n_nodes(&self) -> usize

Number of distinct nodes.

pub fn n_edges(&self) -> usize

Number of temporal edges.

pub fn total_interaction_time(&self) -> f64

Sum of all edge durations.

pub fn stream_density(&self) -> f64

Stream density: fraction of (node-pair × time) space that is active.

Defined as total_interaction_time / (|V|*(|V|-1)/2 * T) for undirected streams.