Struct linfa_nn::LinearSearchIndex

pub struct LinearSearchIndex<'a, F: Float, D: Distance<F>>(/* private fields */);

Spatial indexing structure created by LinearSearch

Implementations

impl<'a, F: Float, D: Distance<F>> LinearSearchIndex<'a, F, D>

pub fn new<DT: Data<Elem = F>>( batch: &'a ArrayBase<DT, Ix2>, dist_fn: D ) -> Result<Self, BuildError>

Creates a new LinearSearchIndex

Trait Implementations

impl<'a, F: Clone + Float, D: Clone + Distance<F>> Clone for LinearSearchIndex<'a, F, D>

fn clone(&self) -> LinearSearchIndex<'a, F, D>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<'a, F: Debug + Float, D: Debug + Distance<F>> Debug for LinearSearchIndex<'a, F, D>

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

Formats the value using the given formatter.

impl<'a, F: Float, D: Distance<F>> NearestNeighbourIndex<F> for LinearSearchIndex<'a, F, D>

fn k_nearest<'b>( &self, point: ArrayView1<'b, F>, k: usize ) -> Result<Vec<(ArrayView1<'_, F>, usize)>, NnError>

Returns the k points in the index that are the closest to the provided point, along with their positions in the original dataset. Points are returned in ascending order of the distance away from the provided points, and less than k points will be returned if the index contains fewer than k.

fn within_range<'b>( &self, point: ArrayView1<'b, F>, range: F ) -> Result<Vec<(ArrayView1<'_, F>, usize)>, NnError>

Returns all the points in the index that are within the specified distance to the provided point, along with their positions in the original dataset. The points are not guaranteed to be in any order, though many algorithms return the points in order of distance.

impl<'a, F: PartialEq + Float, D: PartialEq + Distance<F>> PartialEq for LinearSearchIndex<'a, F, D>

fn eq(&self, other: &LinearSearchIndex<'a, F, D>) -> bool

This method tests for self and other values to be equal, and is used by ==.

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

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

impl<'a, F: Float, D: Distance<F>> StructuralPartialEq for LinearSearchIndex<'a, F, D>