fix: renames FloatExt to RealNumber

src/algorithm/neighbour/bbd_tree.rs

@@ -2,17 +2,17 @@ use std::fmt::Debug;
 
 use crate::linalg::Matrix;
 use crate::math::distance::euclidian::*;
-use crate::math::num::FloatExt;
+use crate::math::num::RealNumber;
 
 #[derive(Debug)]
-pub struct BBDTree<T: FloatExt> {
+pub struct BBDTree<T: RealNumber> {
     nodes: Vec<BBDTreeNode<T>>,
     index: Vec<usize>,
     root: usize,
 }
 
 #[derive(Debug)]
-struct BBDTreeNode<T: FloatExt> {
+struct BBDTreeNode<T: RealNumber> {
     count: usize,
     index: usize,
     center: Vec<T>,
@@ -23,7 +23,7 @@ struct BBDTreeNode<T: FloatExt> {
     upper: Option<usize>,
 }
 
-impl<T: FloatExt> BBDTreeNode<T> {
+impl<T: RealNumber> BBDTreeNode<T> {
     fn new(d: usize) -> BBDTreeNode<T> {
         BBDTreeNode {
             count: 0,
@@ -38,7 +38,7 @@ impl<T: FloatExt> BBDTreeNode<T> {
     }
 }
 
-impl<T: FloatExt> BBDTree<T> {
+impl<T: RealNumber> BBDTree<T> {
     pub fn new<M: Matrix<T>>(data: &M) -> BBDTree<T> {
         let nodes = Vec::new();
 

src/algorithm/neighbour/cover_tree.rs

@@ -30,11 +30,11 @@ use serde::{Deserialize, Serialize};
 
 use crate::algorithm::sort::heap_select::HeapSelect;
 use crate::math::distance::Distance;
-use crate::math::num::FloatExt;
+use crate::math::num::RealNumber;
 
 /// Implements Cover Tree algorithm
 #[derive(Serialize, Deserialize, Debug)]
-pub struct CoverTree<T, F: FloatExt, D: Distance<T, F>> {
+pub struct CoverTree<T, F: RealNumber, D: Distance<T, F>> {
     base: F,
     max_level: i8,
     min_level: i8,
@@ -42,7 +42,7 @@ pub struct CoverTree<T, F: FloatExt, D: Distance<T, F>> {
     nodes: Vec<Node<T>>,
 }
 
-impl<T: Debug, F: FloatExt, D: Distance<T, F>> CoverTree<T, F, D> {
+impl<T: Debug, F: RealNumber, D: Distance<T, F>> CoverTree<T, F, D> {
     /// Construct a cover tree.
     /// * `data` - vector of data points to search for.
     /// * `distance` - distance metric to use for searching. This function should extend [`Distance`](../algorithm/neighbour/index.html) interface.

src/algorithm/neighbour/linear_search.rs

@@ -27,17 +27,17 @@ use std::marker::PhantomData;
 
 use crate::algorithm::sort::heap_select::HeapSelect;
 use crate::math::distance::Distance;
-use crate::math::num::FloatExt;
+use crate::math::num::RealNumber;
 
 /// Implements Linear Search algorithm, see [KNN algorithms](../index.html)
 #[derive(Serialize, Deserialize, Debug)]
-pub struct LinearKNNSearch<T, F: FloatExt, D: Distance<T, F>> {
+pub struct LinearKNNSearch<T, F: RealNumber, D: Distance<T, F>> {
     distance: D,
     data: Vec<T>,
     f: PhantomData<F>,
 }
 
-impl<T, F: FloatExt, D: Distance<T, F>> LinearKNNSearch<T, F, D> {
+impl<T, F: RealNumber, D: Distance<T, F>> LinearKNNSearch<T, F, D> {
     /// Initializes algorithm.
     /// * `data` - vector of data points to search for.
     /// * `distance` - distance metric to use for searching. This function should extend [`Distance`](../algorithm/neighbour/index.html) interface.
@@ -86,24 +86,24 @@ impl<T, F: FloatExt, D: Distance<T, F>> LinearKNNSearch<T, F, D> {
 }
 
 #[derive(Debug)]
-struct KNNPoint<F: FloatExt> {
+struct KNNPoint<F: RealNumber> {
     distance: F,
     index: Option<usize>,
 }
 
-impl<F: FloatExt> PartialOrd for KNNPoint<F> {
+impl<F: RealNumber> PartialOrd for KNNPoint<F> {
     fn partial_cmp(&self, other: &Self) -> Option<Ordering> {
         self.distance.partial_cmp(&other.distance)
     }
 }
 
-impl<F: FloatExt> PartialEq for KNNPoint<F> {
+impl<F: RealNumber> PartialEq for KNNPoint<F> {
     fn eq(&self, other: &Self) -> bool {
         self.distance == other.distance
     }
 }
 
-impl<F: FloatExt> Eq for KNNPoint<F> {}
+impl<F: RealNumber> Eq for KNNPoint<F> {}
 
 #[cfg(test)]
 mod tests {