feat: serialization/deserialization with Serde

src/linear/linear_regression.rs

@@ -1,22 +1,31 @@
 use std::fmt::Debug;
 
+use serde::{Serialize, Deserialize};
+
 use crate::math::num::FloatExt;
 use crate::linalg::Matrix;
 
-#[derive(Debug)]
+#[derive(Serialize, Deserialize, Debug)]
 pub enum LinearRegressionSolver {
     QR,
     SVD
 }
 
-#[derive(Debug)]
-pub struct LinearRegression<T: FloatExt + Debug, M: Matrix<T>> {    
+#[derive(Serialize, Deserialize, Debug)]
+pub struct LinearRegression<T: FloatExt, M: Matrix<T>> {    
     coefficients: M,
     intercept: T,
     solver: LinearRegressionSolver
 }
 
-impl<T: FloatExt + Debug, M: Matrix<T>> LinearRegression<T, M> {
+impl<T: FloatExt, M: Matrix<T>> PartialEq for LinearRegression<T, M> {
+    fn eq(&self, other: &Self) -> bool {
+        self.coefficients == other.coefficients &&
+        self.intercept == other.intercept        
+    }
+}
+
+impl<T: FloatExt, M: Matrix<T>> LinearRegression<T, M> {
 
     pub fn fit(x: &M, y: &M, solver: LinearRegressionSolver) -> LinearRegression<T, M>{
 
@@ -90,4 +99,33 @@ mod tests {
 
 
     }
+
+    #[test]
+    fn serde(){
+        let x = DenseMatrix::from_array(&[
+            &[234.289, 235.6, 159.0, 107.608, 1947., 60.323],
+            &[259.426, 232.5, 145.6, 108.632, 1948., 61.122],
+            &[258.054, 368.2, 161.6, 109.773, 1949., 60.171],
+            &[284.599, 335.1, 165.0, 110.929, 1950., 61.187],
+            &[328.975, 209.9, 309.9, 112.075, 1951., 63.221],
+            &[346.999, 193.2, 359.4, 113.270, 1952., 63.639],
+            &[365.385, 187.0, 354.7, 115.094, 1953., 64.989],
+            &[363.112, 357.8, 335.0, 116.219, 1954., 63.761],
+            &[397.469, 290.4, 304.8, 117.388, 1955., 66.019],
+            &[419.180, 282.2, 285.7, 118.734, 1956., 67.857],
+            &[442.769, 293.6, 279.8, 120.445, 1957., 68.169],
+            &[444.546, 468.1, 263.7, 121.950, 1958., 66.513],
+            &[482.704, 381.3, 255.2, 123.366, 1959., 68.655],
+            &[502.601, 393.1, 251.4, 125.368, 1960., 69.564],
+            &[518.173, 480.6, 257.2, 127.852, 1961., 69.331],
+            &[554.894, 400.7, 282.7, 130.081, 1962., 70.551]]);
+    
+        let y = DenseMatrix::from_array(&[&[83.0,  88.5,  88.2,  89.5,  96.2,  98.1,  99.0, 100.0, 101.2, 104.6, 108.4, 110.8, 112.6, 114.2, 115.7, 116.9]]);  
+
+        let lr = LinearRegression::fit(&x, &y, LinearRegressionSolver::QR);
+        
+        let deserialized_lr: LinearRegression<f64, DenseMatrix<f64>> = serde_json::from_str(&serde_json::to_string(&lr).unwrap()).unwrap();
+
+        assert_eq!(lr, deserialized_lr);        
+    }
 }