Rust implementation of SR-Tree: nearest neighbor search index for high-dimensional clustered datasets, modified to support variance-based bulk-loading. This crate applies fundamental concepts presented in the paper, and the original C++ version can be found here.
This example shows how to query nearest neighbors:
use srtree::SRTree;
fn main() {
let points = vec![
vec![0., 0.],
vec![1., 1.],
vec![2., 2.],
vec![3., 3.],
vec![4., 4.],
];
let tree = SRTree::euclidean(&points).expect("Failed to build SRTree");
let (indices, distances) = tree.query(&[8., 8.], 3);
println!("{indices:?}"); // [4, 3, 2] (sorted by distance)
println!("{distances:?}");
}Copyright 2022-2023 ClumL Inc.
Licensed under Apache License, Version 2.0 (the "License"); you may not use this crate except in compliance with the License.
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