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mod hash; use hash::{Hash, HashTableKey, Hyperlanes, QueryResult, Point, HashTableBucket, HashTable}; use core::borrow::Borrow; use std::collections::HashMap; fn euclidean_dist_square(p1: &[f64], p2: &[f64]) -> f64 { p1.iter().zip(p2). fold(0.0, |acc, (i, j)| acc + (j - i). powi(2)) } struct CosineLshParam { dim: i64, l: i64, m: i64, h: i64, hyperplanes: Hyperlanes, } impl CosineLshParam { fn new(dim: i64, l: i64, m: i64, h: i64, hyperplanes: Hyperlanes) -> CosineLshParam { CosineLshParam{dim, l, m, hyperplanes, h} } fn hash(&self, point: &[f64]) -> Vec<HashTableKey> { let simhash = Hash::new(self.hyperplanes.borrow(), point); let mut hvs :Vec<HashTableKey> = Vec::with_capacity(self.l as usize); for i in 0..hvs.capacity() { let mut s = Vec::with_capacity(self.m as usize); for j in 0..self.m { s.push(simhash.sig.0[i*self.m as usize+j as usize]); } hvs.push(s); }; hvs } } pub struct CosineLSH<T> { tables: Vec<HashTable<T>>, next_id: u64, param: CosineLshParam } impl<T> CosineLSH<T> where T: Clone + Copy { pub fn new(dim: i64, l: i64, m: i64) -> Self { CosineLSH { tables: vec![HashTable::new(); l as usize], next_id: 0, param: CosineLshParam::new(dim, l, m, m * l, Hyperlanes::new(m * l, dim)) } } pub fn insert(&mut self, point: Vec<f64>, extra_data: T) -> Option<()> { if let Some(hvs) = self.to_basic_hash_table_keys(self.param.hash(point.as_slice())) { for (a, b) in self.tables.iter_mut().enumerate() { let j = hvs[a]; self.next_id += 1; b.entry(j). or_insert_with(HashTableBucket::new). push(Point { vector: point.clone(), id: self.next_id, extra_data }); }; } else { return None } Some(()) } pub fn query(&self, q: Vec<f64>, max_result: usize) -> Option<Vec<QueryResult<T>>> { let mut seen :HashMap<u64,&Point<T>> = HashMap::new(); if let Some(hvs) = self.to_basic_hash_table_keys(self.param.hash(&q)) { self.tables.iter().enumerate().for_each(|(i, table)| { if let Some(candidates) = table.get(hvs[i].borrow()) { candidates.iter(). for_each(|p| { seen.entry(p.id).or_insert(p); }); } } ) } let mut distances :Vec<QueryResult<T>> = Vec::with_capacity(seen.len()); for (_, value) in seen { let distance = euclidean_dist_square(&q, &value.vector); distances.push(QueryResult{ distance, vector: &value.vector, id: value.id, extra_data: value.extra_data}); } if distances.is_empty() { return None } distances.sort_by(|a, b| a.distance.partial_cmp(&b.distance).unwrap()); if max_result> 0 && distances.len() > max_result as usize { Some(distances[0..max_result].to_vec()) } else { Some(distances) } } fn to_basic_hash_table_keys(&self, keys: Vec<HashTableKey>) -> Option<Vec<u64>> { let mut basic_keys :Vec<u64> = Vec::with_capacity(self.param.l as usize); for key in keys { let mut s = "".to_string(); for (_, hash_val) in key.iter().enumerate() { match hash_val { 0 => s.push_str("0"), 1 => s.push_str("1"), _ => return None } } basic_keys.push(s.parse().unwrap()); } Some(basic_keys) } } #[cfg(test)] mod tests { use super::*; #[test] fn euclidian_test() { let a = vec![34.0,12.0,65.0,29.0]; let b = vec![2.0,3.0,4.0]; assert_eq!(euclidean_dist_square(a.as_slice(), b.as_slice()), 4826.0); } }