Struct LpDist 

pub struct LpDist<F: Float>(pub F);

L-p or Minkowsky distance

Tuple Fields

0: F

Implementations

impl<F: Float> LpDist<F>

pub fn new(p: F) -> Self

Trait Implementations

impl<F: Clone + Float> Clone for LpDist<F>

fn clone(&self) -> LpDist<F>

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<F: Debug + Float> Debug for LpDist<F>

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

Formats the value using the given formatter.

impl<F: Float> Distance<F> for LpDist<F>

fn distance<D: Dimension>( &self, a: ArrayView<'_, F, D>, b: ArrayView<'_, F, D>, ) -> F

Computes the distance between two points. For most spatial algorithms to work correctly, this metric must satisfy the Triangle Inequality.

fn rdistance<D: Dimension>( &self, a: ArrayView<'_, F, D>, b: ArrayView<'_, F, D>, ) -> F

A faster version of the distance metric that keeps the order of the distance function. That is, dist(a, b) > dist(c, d) implies rdist(a, b) > rdist(c, d). For most algorithms this is the same as distance. Unlike distance, this function does not need to satisfy the Triangle Inequality.

fn rdist_to_dist(&self, rdist: F) -> F

Converts the result of rdistance to distance

fn dist_to_rdist(&self, dist: F) -> F

Converts the result of distance to rdistance

impl<F: PartialEq + Float> PartialEq for LpDist<F>

fn eq(&self, other: &LpDist<F>) -> 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<F: Float> StructuralPartialEq for LpDist<F>