anndists

This crate provides distances computations used in some related crates hnsw_rs, annembed and coreset

All distances implement the trait Distance:

pub trait Distance<T: Send + Sync> {  
    fn eval(&self, va: &[T], vb: &[T]) -> f32;
}

Functionalities

The crate provides:

• usual distances as L1, L2, Cosine, Jaccard, Hamming for vectors of standard numeric types, Levenshtein distance on u16.

• Hellinger distance and Jeffreys divergence between probability distributions (f32 and f64). It must be noted that the Jeffreys divergence (a symetrized Kullback-Leibler divergence) do not satisfy the triangle inequality. (Neither Cosine distance !).

• Jensen-Shannon distance between probability distributions (f32 and f64). It is defined as the square root of the Jensen-Shannon divergence and is a bounded metric. See Nielsen F. in Entropy 2019, 21(5), 485.

• A Trait to enable the user to implement its own distances. It takes as data slices of types T satisfying T:Serialize+Clone+Send+Sync. It is also possible to use C extern functions or closures.

• Simd implementation is provided for the most often used case.

Implementation

Simd support is provided with the simdeez crate on Intel and partial implementation with std::simd for general case.

Building

Simd

• The simd provided by the simdeez crate is accessible with the feature "simdeez_f" for x86_64 processors. Compile with cargo build --release --features "simdeez_f" .... To compile this crate on a M1 chip just do not activate this feature.

• It is nevertheless possible to experiment with std::simd. Compiling with the feature stdsimd (cargo build --release --features "stdsimd"), activates the portable_simd feature on rust nightly. This requires nightly compiler. Only the Hamming distance with the u32x16 and u64x8 types and DistL1,DistL2 and DistDot on f32*16 are provided for now.

Benchmarks and Examples

The speed is illustated in the hnsw_rs, annembed crates

Changes

Version 0.1.3: switched to edition=2024

Version 0.1.4: simdeez switched to 2.0.0. Added distance_jaccard_u16_32_simd (contribution from Jianshu Zhao)

Contributions

Petter Egesund added the DistLevenshtein distance.

License

Licensed under either of

• Apache License, Version 2.0, LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0
• MIT license LICENSE-MIT or http://opensource.org/licenses/MIT

at your option.