//! # Minkowski Distance //! //! The Minkowski distance of order _p_ (where _p_ is an integer) is a metric in a normed vector space which can be considered as a generalization of both the Euclidean distance and the Manhattan distance. //! The Manhattan distance between two points \\(x \in ℝ^n \\) and \\( y \in ℝ^n \\) in n-dimensional space is defined as: //! //! \\[ d(x, y) = \left(\sum_{i=0}^n \lvert x_i - y_i \rvert^p\right)^{1/p} \\] //! //! Example: //! //! ``` //! use smartcore::metrics::distance::Distance; //! use smartcore::metrics::distance::minkowski::Minkowski; //! //! let x = vec![1., 1.]; //! let y = vec![2., 2.]; //! //! let l1: f64 = Minkowski::new(1).distance(&x, &y); //! let l2: f64 = Minkowski::new(2).distance(&x, &y); //! //! ``` //! //! #[cfg(feature = "serde")] use serde::{Deserialize, Serialize}; use std::marker::PhantomData; use crate::linalg::basic::arrays::ArrayView1; use crate::numbers::basenum::Number; use super::Distance; /// Defines the Minkowski distance of order `p` #[cfg_attr(feature = "serde", derive(Serialize, Deserialize))] #[derive(Debug, Clone)] pub struct Minkowski { /// order, integer pub p: u16, _t: PhantomData, } impl Minkowski { /// instatiate the initial structure pub fn new(p: u16) -> Minkowski { Minkowski { p, _t: PhantomData } } } impl> Distance for Minkowski { fn distance(&self, x: &A, y: &A) -> f64 { if x.shape() != y.shape() { panic!("Input vector sizes are different"); } if self.p < 1 { panic!("p must be at least 1"); } let p_t = self.p as f64; let dist: f64 = x .iterator(0) .zip(y.iterator(0)) .map(|(&a, &b)| (a - b).to_f64().unwrap().abs().powf(p_t)) .sum(); dist.powf(1f64 / p_t) } } #[cfg(test)] mod tests { use super::*; #[cfg_attr( all(target_arch = "wasm32", not(target_os = "wasi")), wasm_bindgen_test::wasm_bindgen_test )] #[test] fn minkowski_distance() { let a = vec![1., 2., 3.]; let b = vec![4., 5., 6.]; let l1: f64 = Minkowski::new(1).distance(&a, &b); let l2: f64 = Minkowski::new(2).distance(&a, &b); let l3: f64 = Minkowski::new(3).distance(&a, &b); assert!((l1 - 9.0).abs() < 1e-8); assert!((l2 - 5.19615242).abs() < 1e-8); assert!((l3 - 4.32674871).abs() < 1e-8); } #[test] #[should_panic(expected = "p must be at least 1")] fn minkowski_distance_negative_p() { let a = vec![1., 2., 3.]; let b = vec![4., 5., 6.]; let _: f64 = Minkowski::new(0).distance(&a, &b); } }