Replace max value, group imports by StdExternalCrate

.github/workflows/ci.yml

@@ -12,7 +12,7 @@ jobs:
         rust-version: stable
     - uses: actions/checkout@master
     - name: Check formatting
-      run: cargo fmt -- --check
+      run: cargo fmt -- --check --config group_imports=StdExternalCrate
     - name: Clippy
       run: cargo clippy -- -D warnings -W clippy::pedantic
     - name: markdownlint

benches/tests/dbscan.rs

@@ -1,10 +1,11 @@
-use super::setup::{make_blobs, CenterConfig};
 use criterion::{black_box, Criterion};
 use ndarray::{arr2, ArrayView};
 use ndarray_rand::rand::{rngs::StdRng, Rng, SeedableRng};
 use petal_clustering::{Dbscan, Fit};
 use petal_neighbors::distance::Euclidean;
 
+use super::setup::{make_blobs, CenterConfig};
+
 pub fn build(c: &mut Criterion) {
     let n = black_box(5000);
     let dim = black_box(3);

benches/tests/hdbscan.rs

@@ -1,9 +1,10 @@
-use super::setup::{make_blobs, CenterConfig};
 use criterion::{black_box, Criterion};
 use ndarray::{arr2, ArrayView};
 use ndarray_rand::rand::{rngs::StdRng, Rng, SeedableRng};
 use petal_clustering::{Fit, HDbscan};
 
+use super::setup::{make_blobs, CenterConfig};
+
 pub fn build(c: &mut Criterion) {
     let n = black_box(5000);
     let dim = black_box(3);

benches/tests/mod.rs

@@ -7,12 +7,10 @@ pub use dbscan::{
     build as dbscan_build, fixed_clusters as dbscan_fixed_clusters,
     uniform_clusters as dbscan_uniform_clusters,
 };
-
 pub use hdbscan::{
     build as hdbscan_build, fixed_clusters as hdbscan_fixed_clusters,
     uniform_clusters as hdbscan_uniform_clusters,
 };
-
 pub use optics::{
     build as optics_build, fixed_clusters as optics_fixed_clusters,
     uniform_clusters as optics_uniform_clusters,

benches/tests/optics.rs

@@ -1,10 +1,11 @@
-use super::setup::{make_blobs, CenterConfig};
 use criterion::{black_box, Criterion};
 use ndarray::{arr2, ArrayView};
 use ndarray_rand::rand::{rngs::StdRng, Rng, SeedableRng};
 use petal_clustering::{Fit, Optics};
 use petal_neighbors::distance::Euclidean;
 
+use super::setup::{make_blobs, CenterConfig};
+
 pub fn build(c: &mut Criterion) {
     let n = black_box(5000);
     let dim = black_box(3);

examples/hdbscan.rs

@@ -1,8 +1,9 @@
+use std::{env, fs::File, process::exit};
+
 use csv::ReaderBuilder;
 use ndarray::Array2;
 use petal_clustering::{Fit, HDbscan};
 use petal_neighbors::distance::Euclidean;
-use std::{env, fs::File, process::exit};
 
 fn main() {
     let (file, min_cluster_size, min_samples) = parse();

src/dbscan.rs

@@ -1,3 +1,6 @@
+use std::collections::{HashMap, HashSet};
+use std::ops::{AddAssign, DivAssign};
+
 use ndarray::{ArrayBase, Data, Ix2};
 use num_traits::{float::FloatCore, FromPrimitive};
 use petal_neighbors::{
@@ -6,8 +9,6 @@ use petal_neighbors::{
 };
 use rayon::prelude::*;
 use serde::{Deserialize, Serialize};
-use std::collections::{HashMap, HashSet};
-use std::ops::{AddAssign, DivAssign};
 
 use super::Fit;
 
@@ -148,10 +149,11 @@ fn expand_cluster(
 
 #[cfg(test)]
 mod test {
-    use super::*;
     use maplit::hashmap;
     use ndarray::{array, aview2};
 
+    use super::*;
+
     #[test]
     fn default() {
         let dbscan = Dbscan::<f32, Euclidean>::default();

src/hdbscan.rs

@@ -1,18 +1,19 @@
-use ndarray::{Array1, ArrayBase, ArrayView1, ArrayView2, Data, Ix2};
-use num_traits::{float::FloatCore, FromPrimitive};
-use rayon::prelude::*;
-use serde::{Deserialize, Serialize};
 use std::cmp::Ordering;
 use std::collections::{HashMap, HashSet};
 use std::convert::TryFrom;
 use std::fmt::Debug;
 use std::mem::MaybeUninit;
 use std::ops::{AddAssign, Div, DivAssign, Sub};
-use succinct::{BitVecMut, BitVector};
 
-use super::Fit;
+use ndarray::{Array1, ArrayBase, ArrayView1, ArrayView2, Data, Ix2};
+use num_traits::{float::FloatCore, FromPrimitive};
 use petal_neighbors::distance::{Euclidean, Metric};
 use petal_neighbors::BallTree;
+use rayon::prelude::*;
+use serde::{Deserialize, Serialize};
+use succinct::{BitVecMut, BitVector};
+
+use super::Fit;
 
 #[derive(Debug, Deserialize, Serialize)]
 pub struct HDbscan<A, M> {
@@ -831,9 +832,9 @@ struct Candidates<A> {
 impl<A: FloatCore> Candidates<A> {
     fn new(n: usize) -> Self {
         // define max_value as NULL
-        let neighbors = vec![u32::max_value(); n];
+        let neighbors = vec![u32::MAX; n];
         // define max_value as NULL
-        let points = vec![u32::max_value(); n];
+        let points = vec![u32::MAX; n];
         // define max_value as infinite far
         let distances = vec![A::max_value(); n];
         Self {
@@ -862,13 +863,13 @@ impl<A: FloatCore> Candidates<A> {
     }
 
     fn reset(&mut self, i: usize) {
-        self.points[i] = u32::max_value();
-        self.neighbors[i] = u32::max_value();
+        self.points[i] = u32::MAX;
+        self.neighbors[i] = u32::MAX;
         self.distances[i] = A::max_value();
     }
 
     fn is_undefined(&self, i: usize) -> bool {
-        self.points[i] == u32::max_value() || self.neighbors[i] == u32::max_value()
+        self.points[i] == u32::MAX || self.neighbors[i] == u32::MAX
     }
 }
 
@@ -920,10 +921,11 @@ mod test {
 
     #[test]
     fn hdbscan() {
-        use crate::Fit;
         use ndarray::array;
         use petal_neighbors::distance::Euclidean;
 
+        use crate::Fit;
+
         let data = array![
             [1.0, 2.0],
             [1.1, 2.2],
@@ -1147,9 +1149,10 @@ mod test {
 
     #[test]
     fn get_stability() {
-        use ndarray::arr1;
         use std::collections::HashMap;
 
+        use ndarray::arr1;
+
         let condensed = arr1(&[
             (7, 6, 1. / 9., 1),
             (7, 4, 1. / 7., 1),

src/optics.rs

@@ -1,3 +1,6 @@
+use std::collections::HashMap;
+use std::ops::{AddAssign, DivAssign};
+
 use ndarray::{Array, ArrayBase, Data, Ix2};
 use num_traits::{float::FloatCore, FromPrimitive};
 use petal_neighbors::{
@@ -6,8 +9,6 @@ use petal_neighbors::{
 };
 use rayon::prelude::*;
 use serde::{Deserialize, Serialize};
-use std::collections::HashMap;
-use std::ops::{AddAssign, DivAssign};
 
 use super::Fit;
 
@@ -299,10 +300,11 @@ where
 
 #[cfg(test)]
 mod test {
-    use super::*;
     use maplit::hashmap;
     use ndarray::{array, aview2};
 
+    use super::*;
+
     #[test]
     fn default() {
         let optics = Optics::<f32, Euclidean>::default();