Struct MemoryMappedDistanceMatrix 

pub struct MemoryMappedDistanceMatrix { /* private fields */ }

Memory-mapped distance matrix for large-scale distance computation

Implementations

impl MemoryMappedDistanceMatrix

pub fn new(n_samples: usize, config: MemoryMappedConfig) -> Result<Self>

Create a new memory-mapped distance matrix

Arguments

• n_samples - Number of samples in the dataset
• config - Configuration for memory mapping

pub fn compute_distances(&mut self, data: &Array2<Float>) -> Result<()>

Compute distance matrix in chunks and store in memory-mapped file

Arguments

• data - Input data matrix (n_samples × n_features)

pub fn get_distance(&self, i: usize, j: usize) -> Result<Float>

Get distance value at position (i, j)

pub fn get_k_nearest_neighbors( &self, sample_idx: usize, k: usize, ) -> Result<Vec<(usize, Float)>>

Get k-nearest neighbors for a specific sample

Arguments

• sample_idx - Index of the sample
• k - Number of nearest neighbors to find

Returns

Vector of (neighbor_index, distance) pairs sorted by distance

pub fn get_neighbors_within_radius( &self, sample_idx: usize, radius: Float, ) -> Result<Vec<(usize, Float)>>

Get all neighbors within a specific radius

Arguments

• sample_idx - Index of the sample
• radius - Maximum distance for neighbors

Returns

Vector of (neighbor_index, distance) pairs within radius

pub fn memory_stats(&self) -> MemoryStats

Get memory usage statistics

pub fn to_array(&self) -> Result<Array2<Float>>

Export distance matrix to a standard format

This method exports the distance matrix as a regular Array2 for smaller datasets or when you need to integrate with other algorithms that expect in-memory matrices.

Warning: This will load the entire distance matrix into memory.

pub fn sync(&mut self) -> Result<()>

Flush any pending writes to disk