a1c56a859e
* initial fastpair implementation * FastPair initial implementation * implement fastpair * Add random test * Add bench for fastpair * Refactor with constructor for FastPair * Add serialization for PairwiseDistance * Add fp_bench feature for fastpair bench
49 lines
1.6 KiB
Rust
49 lines
1.6 KiB
Rust
//!
|
|
//! Dissimilarities for vector-vector distance
|
|
//!
|
|
//! Representing distances as pairwise dissimilarities, so to build a
|
|
//! graph of closest neighbours. This representation can be reused for
|
|
//! different implementations (initially used in this library for FastPair).
|
|
use std::cmp::{Eq, Ordering, PartialOrd};
|
|
|
|
#[cfg(feature = "serde")]
|
|
use serde::{Deserialize, Serialize};
|
|
|
|
use crate::math::num::RealNumber;
|
|
|
|
///
|
|
/// The edge of the subgraph is defined by `PairwiseDistance`.
|
|
/// The calling algorithm can store a list of distsances as
|
|
/// a list of these structures.
|
|
///
|
|
#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
|
|
#[derive(Debug, Clone, Copy)]
|
|
pub struct PairwiseDistance<T: RealNumber> {
|
|
/// index of the vector in the original `Matrix` or list
|
|
pub node: usize,
|
|
|
|
/// index of the closest neighbor in the original `Matrix` or same list
|
|
pub neighbour: Option<usize>,
|
|
|
|
/// measure of distance, according to the algorithm distance function
|
|
/// if the distance is None, the edge has value "infinite" or max distance
|
|
/// each algorithm has to match
|
|
pub distance: Option<T>,
|
|
}
|
|
|
|
impl<T: RealNumber> Eq for PairwiseDistance<T> {}
|
|
|
|
impl<T: RealNumber> PartialEq for PairwiseDistance<T> {
|
|
fn eq(&self, other: &Self) -> bool {
|
|
self.node == other.node
|
|
&& self.neighbour == other.neighbour
|
|
&& self.distance == other.distance
|
|
}
|
|
}
|
|
|
|
impl<T: RealNumber> PartialOrd for PairwiseDistance<T> {
|
|
fn partial_cmp(&self, other: &Self) -> Option<Ordering> {
|
|
self.distance.partial_cmp(&other.distance)
|
|
}
|
|
}
|