Struct SparseDistanceMatrix 

pub struct SparseDistanceMatrix { /* private fields */ }

Sparse dissimilarities: only listed pairs have finite distance. An unlisted pair is an absent edge (+inf). No metric assumptions, same entry rules as DistanceMatrix.

The neighbor lists live in one compressed block: an offset for each vertex, then the neighbor vertices as u32 and their distances in two arrays of the same length. A list is sorted by neighbor vertex. The cofacet merge then walks four bytes an entry and reads a distance only where two lists meet.

Implementations

impl SparseDistanceMatrix

pub fn from_triplets(n: usize, triplets: &[(usize, usize, f64)]) -> Result<Self>

Build from (i, j, d) triplets over n points. A repeated unordered pair must carry an identical distance. Entries must be finite and non-negative. Omit a pair to make it absent. n must be at or below u32::MAX.

pub fn len(&self) -> usize

Number of points.

pub fn is_empty(&self) -> bool

True when there are no points.

pub fn num_edges(&self) -> usize

Number of stored edges.

pub fn get(&self, i: usize, j: usize) -> f64

Distance between i and j; +inf when the pair is not listed.

pub fn edges(&self) -> impl Iterator<Item = (usize, usize, f64)> + '_

Visit every stored edge once, as (u, v, value) with u < v, in ascending u then v order.

Trait Implementations

impl Clone for SparseDistanceMatrix

fn clone(&self) -> SparseDistanceMatrix

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for SparseDistanceMatrix

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.