hannoy 0.1.3

HNSW Approximate Nearest Neighbors in Rust, based on LMDB and optimized for memory usage
Documentation 
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use std::fmt;

pub use binary_quantized_cosine::{BinaryQuantizedCosine, NodeHeaderBinaryQuantizedCosine};
pub use binary_quantized_euclidean::BinaryQuantizedEuclidean;
pub use binary_quantized_manhattan::BinaryQuantizedManhattan;
use bytemuck::{Pod, Zeroable};
pub use cosine::{Cosine, NodeHeaderCosine};
pub use euclidean::{Euclidean, NodeHeaderEuclidean};
pub use hamming::Hamming;
pub use manhattan::Manhattan;

use crate::node::Item;
use crate::unaligned_vector::{UnalignedVector, UnalignedVectorCodec};

mod binary_quantized_cosine;
mod binary_quantized_euclidean;
mod binary_quantized_manhattan;
mod cosine;
mod euclidean;
mod hamming;
mod manhattan;

/// A trait used by hannoy to compute the distances,
/// compute the split planes, and normalize user vectors.
#[allow(missing_docs)]
pub trait Distance: Send + Sync + Sized + Clone + fmt::Debug + 'static {
    /// A header structure with informations related to the
    type Header: Pod + Zeroable + fmt::Debug;
    type VectorCodec: UnalignedVectorCodec;

    /// The name of the distance.
    ///
    /// Note that the name is used to identify the distance and will help some performance improvements.
    /// For example, the "cosine" distance is matched against the "binary quantized cosine" to avoid
    /// recomputing links when moving from the former to the latter distance.
    fn name() -> &'static str;

    fn new_header(vector: &UnalignedVector<Self::VectorCodec>) -> Self::Header;

    /// Returns a non-normalized distance.
    fn distance(p: &Item<Self>, q: &Item<Self>) -> f32;

    fn norm(item: &Item<Self>) -> f32 {
        Self::norm_no_header(&item.vector)
    }

    fn norm_no_header(v: &UnalignedVector<Self::VectorCodec>) -> f32;
}