Update rand crate and usage

Cargo.toml

@@ -18,11 +18,7 @@ Backed by a generic k-means implementation offered as a standalone library."""
 default = ["app"]
 
 # Features required for building the binary
-app = [
-        "image",
-        "palette_color",
-        "structopt",
-    ]
+app = ["image", "palette_color", "structopt"]
 
 # Enable `palette` color types
 palette_color = ["palette", "num-traits", "fxhash"]
@@ -51,12 +47,12 @@ features = ["std"]
 optional = true
 
 [dependencies.rand]
-version = "0.8.5"
+version = "0.9.0"
 default-features = false
-features = ["std"]
+features = ["thread_rng"]
 
 [dependencies.rand_chacha]
-version = "0.3.1"
+version = "0.9.0"
 default-features = false
 
 [dependencies.structopt]

rustfmt.toml

@@ -0,0 +1,5 @@
+format_strings = true
+reorder_imports = true
+imports_granularity = "Module"
+group_imports = "StdExternalCrate"
+max_width = 100

src/colors/kmeans.rs

@@ -2,7 +2,6 @@
 use num_traits::{Float, FromPrimitive, Zero};
 #[cfg(feature = "palette_color")]
 use palette::{rgb::Rgb, rgb::Rgba, Lab};
-
 use rand::Rng;
 
 use crate::kmeans::{Calculate, Hamerly, HamerlyCentroids, HamerlyPoint};
@@ -18,7 +17,7 @@ where
         for color in lab.iter() {
             let mut index = 0;
             let mut diff;
-            let mut min = core::f32::MAX;
+            let mut min = f32::MAX;
             for (idx, cent) in centroids.iter().enumerate() {
                 diff = Self::difference(color, cent);
                 if diff < min {
@@ -68,9 +67,9 @@ where
     #[inline]
     fn create_random(rng: &mut impl Rng) -> Lab<Wp, T> {
         Lab::<Wp, T>::new(
-            T::from_f64(rng.gen_range(0.0..=100.0)).unwrap(),
-            T::from_f64(rng.gen_range(-128.0..=127.0)).unwrap(),
-            T::from_f64(rng.gen_range(-128.0..=127.0)).unwrap(),
+            T::from_f64(rng.random_range(0.0..=100.0)).unwrap(),
+            T::from_f64(rng.random_range(-128.0..=127.0)).unwrap(),
+            T::from_f64(rng.random_range(-128.0..=127.0)).unwrap(),
         )
     }
 
@@ -95,7 +94,7 @@ where
         for color in rgb.iter() {
             let mut index = 0;
             let mut diff;
-            let mut min = core::f32::MAX;
+            let mut min = f32::MAX;
             for (idx, cent) in centroids.iter().enumerate() {
                 diff = Self::difference(color, cent);
                 if diff < min {
@@ -145,9 +144,9 @@ where
     #[inline]
     fn create_random(rng: &mut impl Rng) -> Rgb<S, T> {
         Rgb::<S, T>::new(
-            T::from_f64(rng.gen_range(0.0..=1.0)).unwrap(),
-            T::from_f64(rng.gen_range(0.0..=1.0)).unwrap(),
-            T::from_f64(rng.gen_range(0.0..=1.0)).unwrap(),
+            T::from_f64(rng.random_range(0.0..=1.0)).unwrap(),
+            T::from_f64(rng.random_range(0.0..=1.0)).unwrap(),
+            T::from_f64(rng.random_range(0.0..=1.0)).unwrap(),
         )
     }
 
@@ -222,7 +221,7 @@ where
                 continue;
             }
 
-            let mut min1 = Self::difference(val, centers.centroids.get(0).unwrap());
+            let mut min1 = Self::difference(val, centers.centroids.first().unwrap());
             let mut min2 = f32::MAX;
             let mut c1 = 0;
             for j in 1..centers.centroids.len() {
@@ -355,7 +354,7 @@ where
                 continue;
             }
 
-            let mut min1 = Self::difference(val, centers.centroids.get(0).unwrap());
+            let mut min1 = Self::difference(val, centers.centroids.first().unwrap());
             let mut min2 = f32::MAX;
             let mut c1 = 0;
             for j in 1..centers.centroids.len() {

src/kmeans.rs

@@ -42,7 +42,7 @@ impl<C: Calculate> Kmeans<C> {
     /// Create a new `Kmeans` struct to contain k-means results.
     pub fn new() -> Self {
         Kmeans {
-            score: core::f32::MAX,
+            score: f32::MAX,
             centroids: Vec::new(),
             indices: Vec::new(),
         }

src/plus_plus.rs

@@ -1,4 +1,5 @@
-use rand::distributions::{Distribution, WeightedIndex};
+use rand::distr::weighted::WeightedIndex;
+use rand::distr::Distribution;
 use rand::Rng;
 
 /// k-means++ centroid initialization.
@@ -26,7 +27,7 @@ pub fn init_plus_plus<C: crate::Calculate + Clone>(
     let mut weights: Vec<f32> = (0..len).map(|_| 0.0).collect();
 
     // Choose first centroid at random, uniform sampling from input buffer
-    centroids.push(buf.get(rng.gen_range(0..len)).unwrap().to_owned());
+    centroids.push(buf.get(rng.random_range(0..len)).unwrap().to_owned());
 
     // Pick a new centroid with weighted probability of `D(x)^2 / sum(D(x)^2)`,
     // where `D(x)^2` is the distance to the closest centroid
@@ -35,7 +36,7 @@ pub fn init_plus_plus<C: crate::Calculate + Clone>(
         let mut sum = 0.0;
         for (b, dist) in buf.iter().zip(weights.iter_mut()) {
             let mut diff;
-            let mut min = core::f32::MAX;
+            let mut min = f32::MAX;
             for cent in centroids.iter() {
                 diff = C::difference(b, cent);
                 if diff < min {