Added serde feature flags to tests

src/algorithm/neighbour/cover_tree.rs

@@ -457,7 +457,8 @@ mod tests {
     use super::*;
     use crate::math::distance::Distances;
 
-    #[derive(Debug, Serialize, Deserialize, Clone)]
+    #[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
+    #[derive(Debug, Clone)]
     struct SimpleDistance {}
 
     impl Distance<i32, f64> for SimpleDistance {
@@ -503,6 +504,7 @@ mod tests {
     }
 
     #[test]
+    #[cfg(feature = "serde")]
     fn serde() {
         let data = vec![1, 2, 3, 4, 5, 6, 7, 8, 9];
 

src/algorithm/neighbour/linear_search.rs

@@ -140,7 +140,8 @@ mod tests {
     use super::*;
     use crate::math::distance::Distances;
 
-    #[derive(Debug, Serialize, Deserialize, Clone)]
+    #[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
+    #[derive(Debug, Clone)]
     struct SimpleDistance {}
 
     impl Distance<i32, f64> for SimpleDistance {

src/cluster/dbscan.rs

@@ -265,6 +265,7 @@ impl<T: RealNumber + Sum, D: Distance<Vec<T>, T>> DBSCAN<T, D> {
 mod tests {
     use super::*;
     use crate::linalg::naive::dense_matrix::DenseMatrix;
+    #[cfg(feature = "serde")]
     use crate::math::distance::euclidian::Euclidian;
 
     #[test]
@@ -299,6 +300,7 @@ mod tests {
     }
 
     #[test]
+    #[cfg(feature = "serde")]
     fn serde() {
         let x = DenseMatrix::from_2d_array(&[
             &[5.1, 3.5, 1.4, 0.2],

src/cluster/kmeans.rs

@@ -347,6 +347,7 @@ mod tests {
     }
 
     #[test]
+    #[cfg(feature = "serde")]
     fn serde() {
         let x = DenseMatrix::from_2d_array(&[
             &[5.1, 3.5, 1.4, 0.2],

src/decomposition/pca.rs

@@ -567,6 +567,7 @@ mod tests {
     }
 
     #[test]
+    #[cfg(feature = "serde")]
     fn serde() {
         let iris = DenseMatrix::from_2d_array(&[
             &[5.1, 3.5, 1.4, 0.2],

src/decomposition/svd.rs

@@ -228,6 +228,7 @@ mod tests {
     }
 
     #[test]
+    #[cfg(feature = "serde")]
     fn serde() {
         let iris = DenseMatrix::from_2d_array(&[
             &[5.1, 3.5, 1.4, 0.2],

src/ensemble/random_forest_classifier.rs

@@ -325,6 +325,7 @@ mod tests {
     }
 
     #[test]
+    #[cfg(feature = "serde")]
     fn serde() {
         let x = DenseMatrix::from_2d_array(&[
             &[5.1, 3.5, 1.4, 0.2],

src/ensemble/random_forest_regressor.rs

@@ -274,6 +274,7 @@ mod tests {
     }
 
     #[test]
+    #[cfg(feature = "serde")]
     fn serde() {
         let x = DenseMatrix::from_2d_array(&[
             &[234.289, 235.6, 159., 107.608, 1947., 60.323],

src/linalg/naive/dense_matrix.rs

@@ -1312,6 +1312,7 @@ mod tests {
     }
 
     #[test]
+    #[cfg(feature = "serde")]
     fn to_from_json() {
         let a = DenseMatrix::from_2d_array(&[&[0.9, 0.4, 0.7], &[0.4, 0.5, 0.3], &[0.7, 0.3, 0.8]]);
         let deserialized_a: DenseMatrix<f64> =
@@ -1320,6 +1321,7 @@ mod tests {
     }
 
     #[test]
+    #[cfg(feature = "serde")]
     fn to_from_bincode() {
         let a = DenseMatrix::from_2d_array(&[&[0.9, 0.4, 0.7], &[0.4, 0.5, 0.3], &[0.7, 0.3, 0.8]]);
         let deserialized_a: DenseMatrix<f64> =

src/linear/elastic_net.rs

@@ -401,6 +401,7 @@ mod tests {
     }
 
     #[test]
+    #[cfg(feature = "serde")]
     fn serde() {
         let x = DenseMatrix::from_2d_array(&[
             &[234.289, 235.6, 159.0, 107.608, 1947., 60.323],

src/linear/lasso.rs

@@ -275,6 +275,7 @@ mod tests {
     }
 
     #[test]
+    #[cfg(feature = "serde")]
     fn serde() {
         let x = DenseMatrix::from_2d_array(&[
             &[234.289, 235.6, 159.0, 107.608, 1947., 60.323],

src/linear/linear_regression.rs

@@ -251,6 +251,7 @@ mod tests {
     }
 
     #[test]
+    #[cfg(feature = "serde")]
     fn serde() {
         let x = DenseMatrix::from_2d_array(&[
             &[234.289, 235.6, 159.0, 107.608, 1947., 60.323],

src/linear/logistic_regression.rs

@@ -543,6 +543,7 @@ mod tests {
     }
 
     #[test]
+    #[cfg(feature = "serde")]
     fn serde() {
         let x = DenseMatrix::from_2d_array(&[
             &[1., -5.],

src/linear/ridge_regression.rs

@@ -330,6 +330,7 @@ mod tests {
     }
 
     #[test]
+    #[cfg(feature = "serde")]
     fn serde() {
         let x = DenseMatrix::from_2d_array(&[
             &[234.289, 235.6, 159.0, 107.608, 1947., 60.323],

src/naive_bayes/bernoulli.rs

@@ -351,6 +351,7 @@ mod tests {
     }
 
     #[test]
+    #[cfg(feature = "serde")]
     fn serde() {
         let x = DenseMatrix::<f64>::from_2d_array(&[
             &[1., 1., 0., 0., 0., 0.],

src/naive_bayes/categorical.rs

@@ -349,6 +349,7 @@ mod tests {
     }
 
     #[test]
+    #[cfg(feature = "serde")]
     fn serde() {
         let x = DenseMatrix::<f64>::from_2d_array(&[
             &[3., 4., 0., 1.],

src/naive_bayes/gaussian.rs

@@ -281,6 +281,7 @@ mod tests {
     }
 
     #[test]
+    #[cfg(feature = "serde")]
     fn serde() {
         let x = DenseMatrix::<f64>::from_2d_array(&[
             &[-1., -1.],

src/naive_bayes/multinomial.rs

@@ -324,6 +324,7 @@ mod tests {
         ));
     }
     #[test]
+    #[cfg(feature = "serde")]
     fn serde() {
         let x = DenseMatrix::<f64>::from_2d_array(&[
             &[1., 1., 0., 0., 0., 0.],

src/neighbors/knn_classifier.rs

@@ -280,6 +280,7 @@ mod tests {
     }
 
     #[test]
+    #[cfg(feature = "serde")]
     fn serde() {
         let x =
             DenseMatrix::from_2d_array(&[&[1., 2.], &[3., 4.], &[5., 6.], &[7., 8.], &[9., 10.]]);

src/neighbors/knn_regressor.rs

@@ -269,6 +269,7 @@ mod tests {
     }
 
     #[test]
+    #[cfg(feature = "serde")]
     fn serde() {
         let x =
             DenseMatrix::from_2d_array(&[&[1., 2.], &[3., 4.], &[5., 6.], &[7., 8.], &[9., 10.]]);

src/svm/svc.rs

@@ -726,6 +726,7 @@ mod tests {
     use super::*;
     use crate::linalg::naive::dense_matrix::*;
     use crate::metrics::accuracy;
+    #[cfg(feature = "serde")]
     use crate::svm::*;
 
     #[test]
@@ -814,6 +815,7 @@ mod tests {
     }
 
     #[test]
+    #[cfg(feature = "serde")]
     fn svc_serde() {
         let x = DenseMatrix::from_2d_array(&[
             &[5.1, 3.5, 1.4, 0.2],

src/svm/svr.rs

@@ -533,6 +533,7 @@ mod tests {
     use super::*;
     use crate::linalg::naive::dense_matrix::*;
     use crate::metrics::mean_squared_error;
+    #[cfg(feature = "serde")]
     use crate::svm::*;
 
     #[test]
@@ -569,6 +570,7 @@ mod tests {
     }
 
     #[test]
+    #[cfg(feature = "serde")]
     fn svr_serde() {
         let x = DenseMatrix::from_2d_array(&[
             &[234.289, 235.6, 159.0, 107.608, 1947., 60.323],

src/tree/decision_tree_classifier.rs

@@ -745,6 +745,7 @@ mod tests {
     }
 
     #[test]
+    #[cfg(feature = "serde")]
     fn serde() {
         let x = DenseMatrix::from_2d_array(&[
             &[1., 1., 1., 0.],

src/tree/decision_tree_regressor.rs

@@ -581,6 +581,7 @@ mod tests {
     }
 
     #[test]
+    #[cfg(feature = "serde")]
     fn serde() {
         let x = DenseMatrix::from_2d_array(&[
             &[234.289, 235.6, 159., 107.608, 1947., 60.323],