fix: renames FloatExt to RealNumber

src/math/distance/mod.rs

@@ -1,30 +1,57 @@
+//! # Collection of Distance Functions 
+//! 
+//! Many algorithms in machine learning require a measure of distance between data points. Distance metric (or metric) is a function that defines a distance between a pair of point elements of a set.
+//! Formally, the distance can be any metric measure that is defined as \\( d(x, y) \geq 0\\) and follows three conditions:
+//! 1. \\( d(x, y) = 0 \\) if and only \\( x = y \\), positive definiteness
+//! 1. \\( d(x, y) = d(y, x) \\), symmetry
+//! 1. \\( d(x, y) \leq d(x, z) + d(z, y) \\), 	subadditivity or triangle inequality
+//!
+//! for all \\(x, y, z \in Z \\)
+//! 
+//! A good distance metric helps to improve the performance of classification, clustering and information retrieval algorithms significantly.
+//! 
+//! <script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.0/MathJax.js?config=TeX-AMS_CHTML"></script>
+
+/// Euclidean Distance is the straight-line distance between two points in Euclidean spacere that presents the shortest distance between these points.
 pub mod euclidian;
+/// Hamming Distance between two strings is the number of positions at which the corresponding symbols are different.
 pub mod hamming;
+/// The Mahalanobis distance is the distance between two points in multivariate space.
 pub mod mahalanobis;
+/// Also known as rectilinear distance, city block distance, taxicab metric.
 pub mod manhattan;
+/// A generalization of both the Euclidean distance and the Manhattan distance.
 pub mod minkowski;
 
-use crate::math::num::FloatExt;
+use crate::math::num::RealNumber;
 
-pub trait Distance<T, F: FloatExt> {
+/// Distance metric, a function that calculates distance between two points
+pub trait Distance<T, F: RealNumber> {
+    /// Calculates distance between _a_ and _b_
     fn distance(&self, a: &T, b: &T) -> F;
 }
 
+/// Multitude of distance metric functions
 pub struct Distances {}
 
 impl Distances {
+    /// Euclidian distance
     pub fn euclidian() -> euclidian::Euclidian {
         euclidian::Euclidian {}
     }
 
-    pub fn minkowski<T: FloatExt>(p: T) -> minkowski::Minkowski<T> {
+    /// Minkowski distance
+    /// * `p` - function order. Should be >= 1
+    pub fn minkowski(p: u16) -> minkowski::Minkowski {
         minkowski::Minkowski { p: p }
     }
 
+    /// Manhattan distance
     pub fn manhattan() -> manhattan::Manhattan {
         manhattan::Manhattan {}
     }
 
+    /// Hamming distance
     pub fn hamming() -> hamming::Hamming {
         hamming::Hamming {}
     }