uncomment test

Author: Mec-iS

src/linalg/basic/vector.rs

@@ -36,6 +36,7 @@ impl<T: Debug + Display + Copy + Sized> Array<T, usize> for Vec<T> {
 
 impl<T: Debug + Display + Copy + Sized> MutArray<T, usize> for Vec<T> {
     fn set(&mut self, i: usize, x: T) {
+        // NOTE: this panics in case of out of bounds index
         self[i] = x
     }
 

src/linear/logistic_regression.rs

@@ -818,37 +818,37 @@ mod tests {
         assert!(reg_coeff_sum < coeff);
     }
 
-    // TODO: serialization for the new DenseMatrix needs to be implemented
-    // #[cfg_attr(all(target_arch = "wasm32", not(target_os = "wasi")), wasm_bindgen_test::wasm_bindgen_test)]
-    // #[test]
-    // #[cfg(feature = "serde")]
-    // fn serde() {
-    //     let x = DenseMatrix::from_2d_array(&[
-    //         &[1., -5.],
-    //         &[2., 5.],
-    //         &[3., -2.],
-    //         &[1., 2.],
-    //         &[2., 0.],
-    //         &[6., -5.],
-    //         &[7., 5.],
-    //         &[6., -2.],
-    //         &[7., 2.],
-    //         &[6., 0.],
-    //         &[8., -5.],
-    //         &[9., 5.],
-    //         &[10., -2.],
-    //         &[8., 2.],
-    //         &[9., 0.],
-    //     ]);
-    //     let y: Vec<i32> = vec![0, 0, 1, 1, 2, 1, 1, 0, 0, 2, 1, 1, 0, 0, 1];
-
-    //     let lr = LogisticRegression::fit(&x, &y, Default::default()).unwrap();
-
-    //     let deserialized_lr: LogisticRegression<f64, i32, DenseMatrix<f64>, Vec<i32>> =
-    //         serde_json::from_str(&serde_json::to_string(&lr).unwrap()).unwrap();
-
-    //     assert_eq!(lr, deserialized_lr);
-    // }
+    //TODO: serialization for the new DenseMatrix needs to be implemented
+    #[cfg_attr(all(target_arch = "wasm32", not(target_os = "wasi")), wasm_bindgen_test::wasm_bindgen_test)]
+    #[test]
+    #[cfg(feature = "serde")]
+    fn serde() {
+        let x = DenseMatrix::from_2d_array(&[
+            &[1., -5.],
+            &[2., 5.],
+            &[3., -2.],
+            &[1., 2.],
+            &[2., 0.],
+            &[6., -5.],
+            &[7., 5.],
+            &[6., -2.],
+            &[7., 2.],
+            &[6., 0.],
+            &[8., -5.],
+            &[9., 5.],
+            &[10., -2.],
+            &[8., 2.],
+            &[9., 0.],
+        ]);
+        let y: Vec<i32> = vec![0, 0, 1, 1, 2, 1, 1, 0, 0, 2, 1, 1, 0, 0, 1];
+
+        let lr = LogisticRegression::fit(&x, &y, Default::default()).unwrap();
+
+        let deserialized_lr: LogisticRegression<f64, i32, DenseMatrix<f64>, Vec<i32>> =
+            serde_json::from_str(&serde_json::to_string(&lr).unwrap()).unwrap();
+
+        assert_eq!(lr, deserialized_lr);
+    }
 
     #[cfg_attr(
         all(target_arch = "wasm32", not(target_os = "wasi")),