Run: cargo clippy --fix -Z unstable-options and cargo fmt

src/dataset/boston.rs

@@ -38,8 +38,8 @@ pub fn load_dataset() -> Dataset<f32, f32> {
     Dataset {
         data: x,
         target: y,
-        num_samples: num_samples,
-        num_features: num_features,
+        num_samples,
+        num_features,
         feature_names: vec![
             "CRIM", "ZN", "INDUS", "CHAS", "NOX", "RM", "AGE", "DIS", "RAD", "TAX", "PTRATIO", "B",
             "LSTAT",

src/dataset/breast_cancer.rs

@@ -40,8 +40,8 @@ pub fn load_dataset() -> Dataset<f32, f32> {
     Dataset {
         data: x,
         target: y,
-        num_samples: num_samples,
-        num_features: num_features,
+        num_samples,
+        num_features,
         feature_names: vec![
             "mean radius", "mean texture", "mean perimeter", "mean area",
             "mean smoothness", "mean compactness", "mean concavity",

src/dataset/diabetes.rs

@@ -33,8 +33,8 @@ pub fn load_dataset() -> Dataset<f32, f32> {
     Dataset {
         data: x,
         target: y,
-        num_samples: num_samples,
-        num_features: num_features,
+        num_samples,
+        num_features,
         feature_names: vec![
             "Age", "Sex", "BMI", "BP", "S1", "S2", "S3", "S4", "S5", "S6",
         ]

src/dataset/digits.rs

@@ -23,8 +23,8 @@ pub fn load_dataset() -> Dataset<f32, f32> {
     Dataset {
         data: x,
         target: y,
-        num_samples: num_samples,
-        num_features: num_features,
+        num_samples,
+        num_features,
         feature_names: vec![
             "sepal length (cm)",
             "sepal width (cm)",

src/dataset/generator.rs

@@ -39,8 +39,8 @@ pub fn make_blobs(
     Dataset {
         data: x,
         target: y,
-        num_samples: num_samples,
-        num_features: num_features,
+        num_samples,
+        num_features,
         feature_names: (0..num_features).map(|n| n.to_string()).collect(),
         target_names: vec!["label".to_string()],
         description: "Isotropic Gaussian blobs".to_string(),
@@ -82,7 +82,7 @@ pub fn make_circles(num_samples: usize, factor: f32, noise: f32) -> Dataset<f32,
     Dataset {
         data: x,
         target: y,
-        num_samples: num_samples,
+        num_samples,
         num_features: 2,
         feature_names: (0..2).map(|n| n.to_string()).collect(),
         target_names: vec!["label".to_string()],

src/dataset/iris.rs

@@ -28,8 +28,8 @@ pub fn load_dataset() -> Dataset<f32, f32> {
     Dataset {
         data: x,
         target: y,
-        num_samples: num_samples,
-        num_features: num_features,
+        num_samples,
+        num_features,
         feature_names: vec![
             "sepal length (cm)",
             "sepal width (cm)",

src/dataset/mod.rs

@@ -61,14 +61,14 @@ pub(crate) fn serialize_data<X: RealNumber, Y: RealNumber>(
             let x: Vec<u8> = dataset
                 .data
                 .iter()
-                .map(|v| *v)
+                .copied()
                 .flat_map(|f| f.to_f32_bits().to_le_bytes().to_vec().into_iter())
                 .collect();
             file.write_all(&x)?;
             let y: Vec<u8> = dataset
                 .target
                 .iter()
-                .map(|v| *v)
+                .copied()
                 .flat_map(|f| f.to_f32_bits().to_le_bytes().to_vec().into_iter())
                 .collect();
             file.write_all(&y)?;