chore: fix clippy (#283)
* chore: fix clippy Co-authored-by: Luis Moreno <morenol@users.noreply.github.com>
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@@ -124,7 +124,7 @@ impl<T: Debug + PartialEq, D: Distance<T>> CoverTree<T, D> {
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current_cover_set.push((d, &self.root));
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let mut heap = HeapSelection::with_capacity(k);
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heap.add(std::f64::MAX);
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heap.add(f64::MAX);
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let mut empty_heap = true;
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if !self.identical_excluded || self.get_data_value(self.root.idx) != p {
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@@ -145,7 +145,7 @@ impl<T: Debug + PartialEq, D: Distance<T>> CoverTree<T, D> {
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}
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let upper_bound = if empty_heap {
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std::f64::INFINITY
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f64::INFINITY
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} else {
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*heap.peek()
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};
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@@ -291,7 +291,7 @@ impl<T: Debug + PartialEq, D: Distance<T>> CoverTree<T, D> {
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} else {
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let max_dist = self.max(point_set);
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let next_scale = (max_scale - 1).min(self.get_scale(max_dist));
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if next_scale == std::i64::MIN {
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if next_scale == i64::MIN {
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let mut children: Vec<Node> = Vec::new();
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let mut leaf = self.new_leaf(p);
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children.push(leaf);
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@@ -435,7 +435,7 @@ impl<T: Debug + PartialEq, D: Distance<T>> CoverTree<T, D> {
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fn get_scale(&self, d: f64) -> i64 {
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if d == 0f64 {
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std::i64::MIN
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i64::MIN
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} else {
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(self.inv_log_base * d.ln()).ceil() as i64
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}
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@@ -52,10 +52,8 @@ pub struct FastPair<'a, T: RealNumber + FloatNumber, M: Array2<T>> {
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}
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impl<'a, T: RealNumber + FloatNumber, M: Array2<T>> FastPair<'a, T, M> {
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///
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/// Constructor
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/// Instantiate and inizialise the algorithm
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///
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/// Instantiate and initialize the algorithm
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pub fn new(m: &'a M) -> Result<Self, Failed> {
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if m.shape().0 < 3 {
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return Err(Failed::because(
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@@ -74,10 +72,8 @@ impl<'a, T: RealNumber + FloatNumber, M: Array2<T>> FastPair<'a, T, M> {
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Ok(init)
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}
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///
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/// Initialise `FastPair` by passing a `Array2`.
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/// Build a FastPairs data-structure from a set of (new) points.
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///
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fn init(&mut self) {
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// basic measures
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let len = self.samples.shape().0;
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@@ -158,9 +154,7 @@ impl<'a, T: RealNumber + FloatNumber, M: Array2<T>> FastPair<'a, T, M> {
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self.neighbours = neighbours;
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}
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///
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/// Find closest pair by scanning list of nearest neighbors.
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///
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#[allow(dead_code)]
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pub fn closest_pair(&self) -> PairwiseDistance<T> {
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let mut a = self.neighbours[0]; // Start with first point
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@@ -217,9 +211,7 @@ mod tests_fastpair {
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use super::*;
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use crate::linalg::basic::{arrays::Array, matrix::DenseMatrix};
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///
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/// Brute force algorithm, used only for comparison and testing
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///
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pub fn closest_pair_brute(fastpair: &FastPair<f64, DenseMatrix<f64>>) -> PairwiseDistance<f64> {
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use itertools::Itertools;
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let m = fastpair.samples.shape().0;
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@@ -61,7 +61,7 @@ impl<T, D: Distance<T>> LinearKNNSearch<T, D> {
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for _ in 0..k {
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heap.add(KNNPoint {
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distance: std::f64::INFINITY,
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distance: f64::INFINITY,
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index: None,
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});
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}
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@@ -215,7 +215,7 @@ mod tests {
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};
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let point_inf = KNNPoint {
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distance: std::f64::INFINITY,
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distance: f64::INFINITY,
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index: Some(3),
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};
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@@ -133,7 +133,7 @@ mod tests {
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#[test]
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fn test_add1() {
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let mut heap = HeapSelection::with_capacity(3);
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heap.add(std::f64::INFINITY);
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heap.add(f64::INFINITY);
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heap.add(-5f64);
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heap.add(4f64);
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heap.add(-1f64);
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@@ -151,7 +151,7 @@ mod tests {
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#[test]
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fn test_add2() {
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let mut heap = HeapSelection::with_capacity(3);
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heap.add(std::f64::INFINITY);
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heap.add(f64::INFINITY);
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heap.add(0.0);
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heap.add(8.4852);
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heap.add(5.6568);
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@@ -3,6 +3,7 @@ use num_traits::Num;
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pub trait QuickArgSort {
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fn quick_argsort_mut(&mut self) -> Vec<usize>;
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#[allow(dead_code)]
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fn quick_argsort(&self) -> Vec<usize>;
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}
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