Struct space::LinearKnn

pub struct LinearKnn<M, I> {
    pub metric: M,
    pub iter: I,
}

Performs a linear knn search by iterating over everything in the space and performing a binary search on running set of neighbors.

Example

use space::{Knn, LinearKnn, Metric, Neighbor};

struct Hamming;

impl Metric<u8> for Hamming {
    type Unit = u8;

    fn distance(&self, &a: &u8, &b: &u8) -> Self::Unit {
        (a ^ b).count_ones() as u8
    }
}

let data = [
    0b1010_1010,
    0b1111_1111,
    0b0000_0000,
    0b1111_0000,
    0b0000_1111,
];

let search = LinearKnn {
    metric: Hamming,
    iter: data.iter(),
};

assert_eq!(
    &search.knn(&0b0101_0000, 3),
    &[
        Neighbor { index: 2, distance: 2 },
        Neighbor { index: 3, distance: 2 },
        Neighbor { index: 0, distance: 6 },
    ]
);

Fields

metric: M

iter: I

Trait Implementations

impl<'a, M, P: 'a, I> Knn for LinearKnn<M, I> where
    M: Metric<P>,
    I: Clone + Iterator<Item = &'a P>, 

type Ix = usize

type Metric = M

type Point = P

type KnnIter = Vec<Neighbor<M::Unit>>

fn knn(&self, query: &P, num: usize) -> Self::KnnIter

Get num nearest neighbors of target.

fn nn(&self, query: &P) -> Option<Neighbor<M::Unit>>

Get the nearest neighbor of target.