Struct SimilaritySearch 

pub struct SimilaritySearch { /* private fields */ }

Similarity search engine for chess positions with production-optimized caching

Implementations

impl SimilaritySearch

pub fn new(vector_size: usize) -> Self

Create a new similarity search engine with default caching settings

pub fn with_cache_config( vector_size: usize, max_cache_size: usize, cache_ttl_secs: u64, ) -> Self

Create a new similarity search engine with custom cache configuration

pub fn add_position(&mut self, vector: Array1<f32>, evaluation: f32)

Add a position to the search index

pub fn search_ref( &self, query: &Array1<f32>, k: usize, ) -> Vec<(&Array1<f32>, f32, f32)>

Search for k most similar positions with references (memory efficient)

pub fn search( &mut self, query: &Array1<f32>, k: usize, ) -> Vec<(Array1<f32>, f32, f32)>

Search for k most similar positions with comprehensive caching (automatically chooses best method)

pub fn gpu_accelerated_search( &self, query: &Array1<f32>, k: usize, ) -> Result<Vec<(Array1<f32>, f32, f32)>, Box<dyn Error>>

GPU-accelerated similarity search for large datasets

pub fn sequential_search_ref( &self, query: &Array1<f32>, k: usize, ) -> Vec<(&Array1<f32>, f32, f32)>

Sequential search implementation with references (memory efficient)

pub fn sequential_search( &self, query: &Array1<f32>, k: usize, ) -> Vec<(Array1<f32>, f32, f32)>

Sequential search implementation (for small datasets)

pub fn parallel_search_ref( &self, query: &Array1<f32>, k: usize, ) -> Vec<(&Array1<f32>, f32, f32)>

Parallel search implementation with references (memory efficient)

pub fn parallel_search( &self, query: &Array1<f32>, k: usize, ) -> Vec<(Array1<f32>, f32, f32)>

Parallel search implementation (for larger datasets)

pub fn brute_force_search( &self, query: &Array1<f32>, k: usize, ) -> Vec<(Array1<f32>, f32, f32)>

Brute force search (for small datasets or comparison)

pub fn search_by_distance( &self, query: &Array1<f32>, k: usize, ) -> Vec<(Array1<f32>, f32, f32)>

Search using Euclidean distance (alternative to cosine similarity)

pub fn size(&self) -> usize

Get number of positions in the index

pub fn is_empty(&self) -> bool

Check if the index is empty

pub fn clear(&mut self)

Clear all positions

pub fn statistics(&self) -> SimilaritySearchStats

Get statistics about the stored vectors

pub fn get_all_positions(&self) -> Vec<(Array1<f32>, f32)>

Get all stored positions (for LSH indexing)

pub fn get_position_ref(&self, index: usize) -> Option<(&Array1<f32>, f32)>

Get position vector by reference to avoid cloning

pub fn iter_positions(&self) -> impl Iterator<Item = (&Array1<f32>, f32)>

Get all positions as references (memory efficient iterator)

pub fn build_cluster_tree(&mut self)

Build hierarchical clustering tree for improved search performance

pub fn rebuild_cluster_tree(&mut self)

Force rebuild of cluster tree (useful after adding many positions)

pub fn cluster_tree_stats(&self) -> Option<ClusterTreeStats>

Get cluster tree statistics

pub fn get_cache_stats(&self) -> SimilarityCacheStats

Get comprehensive cache statistics for performance monitoring

pub fn clear_caches(&mut self)

Clear all caches (useful for benchmarking or memory management)

pub fn reset_cache_stats(&mut self)

Reset cache statistics while preserving cached data

impl SimilaritySearch

pub fn search_optimized( &self, query: &Array1<f32>, k: usize, ) -> Vec<(Array1<f32>, f32, f32)>

Optimized search with early termination and cached computations

pub fn batch_search_optimized( &self, queries: &[Array1<f32>], k: usize, ) -> Vec<Vec<(Array1<f32>, f32, f32)>>

Batch search optimization for multiple queries

Trait Implementations

impl Clone for SimilaritySearch

fn clone(&self) -> SimilaritySearch

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.