Struct LinearSearch

pub struct LinearSearch;

Implementation of linear search, which is the simplest nearest neighbour algorithm. All queries are implemented by scanning through every point, so all of them are O(N). Calling from_batch returns a LinearSearchIndex.

Implementations

impl LinearSearch

pub fn new() -> Self

Creates an instance of LinearSearch

Trait Implementations

impl Clone for LinearSearch

fn clone(&self) -> LinearSearch

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for LinearSearch

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for LinearSearch

fn default() -> LinearSearch

Returns the “default value” for a type.

impl NearestNeighbour for LinearSearch

fn from_batch_with_leaf_size<'a, F: Float, DT: Data<Elem = F>, D: 'a + Distance<F>>( &self, batch: &'a ArrayBase<DT, Ix2>, leaf_size: usize, dist_fn: D, ) -> Result<Box<dyn Send + Sync + NearestNeighbourIndex<F> + 'a>, BuildError>

Builds a spatial index using a MxN two-dimensional array representing M points with N dimensions. Also takes leaf_size, which specifies the number of elements in the leaf nodes of tree-like index structures.

fn from_batch<'a, F: Float, DT: Data<Elem = F>, D: 'a + Distance<F>>( &self, batch: &'a ArrayBase<DT, Ix2>, dist_fn: D, ) -> Result<Box<dyn Send + Sync + NearestNeighbourIndex<F> + 'a>, BuildError>

Builds a spatial index using a default leaf size. See from_batch_with_leaf_size for more information.

impl PartialEq for LinearSearch

fn eq(&self, other: &LinearSearch) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Eq for LinearSearch

impl StructuralPartialEq for LinearSearch