Struct CompositeDistance 

pub struct CompositeDistance<A: DistanceMetric, B: DistanceMetric> { /* private fields */ }

Weighted combination of two distance metrics.

Computes weight_a * A::distance(a, b) + weight_b * B::distance(a, b).

This lets callers express composite similarity notions such as “0.6 * string_similarity + 0.4 * embedding_distance” as a single metric that plugs into any clustering algorithm.

use clump::cluster::distance::{CompositeDistance, SquaredEuclidean, Euclidean, DistanceMetric};

let metric = CompositeDistance::new(SquaredEuclidean, Euclidean, 0.5, 0.5);
let d = metric.distance(&[0.0, 0.0], &[3.0, 4.0]);
// 0.5 * 25.0 + 0.5 * 5.0 = 15.0
assert!((d - 15.0).abs() < 1e-6);

Implementations

impl<A: DistanceMetric, B: DistanceMetric> CompositeDistance<A, B>

pub fn new(a: A, b: B, weight_a: f32, weight_b: f32) -> Self

Create a new composite distance from two metrics and their weights.

Weights are not required to sum to 1 – they are used as-is.

Trait Implementations

impl<A: Clone + DistanceMetric, B: Clone + DistanceMetric> Clone for CompositeDistance<A, B>

fn clone(&self) -> CompositeDistance<A, B>

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<A: Debug + DistanceMetric, B: Debug + DistanceMetric> Debug for CompositeDistance<A, B>

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

Formats the value using the given formatter.

impl<A: DistanceMetric, B: DistanceMetric> DistanceMetric for CompositeDistance<A, B>

fn distance(&self, a: &[f32], b: &[f32]) -> f32

Compute the distance between two vectors of equal length.