complete revise the architecture

Author: hnlearndev

src/model_points.rs

@@ -41,9 +41,8 @@ pub fn generate_model_points(mp_size: usize, seed: usize) -> PolarsResult<DataFr
     let policy_count = Array1::<f64>::ones(mp_size);
 
     // Sum insured (Float): Random values between 100,000 and 1,000,000 (multiple of 1000)
-    let sum_insured =
-        Array1::random_using(mp_size, Uniform::new(0.0f64, 1.0f64), &mut rng) // Random floats between 0 and 1
-            .mapv(|x| (((900_000.0 * x + 100_000.0) / 1000.0).round() * 1000.0));
+    let sum_insured = Array1::random_using(mp_size, Uniform::new(0.0f64, 1.0f64), &mut rng) // Random floats between 0 and 1
+        .mapv(|x| (((900_000.0 * x + 100_000.0) / 1000.0).round() * 1000.0));
 
     // Create a DataFrame with the generated data
     let model_points_df = df![

src/projections/projection_mp.rs

@@ -3,7 +3,6 @@ use crate::model_points::ModelPoint;
 use ndarray::prelude::*;
 use polars::prelude::*;
 
-
 //---------------------------------------------------------------------------------------------------------
 // PRIVATE
 //---------------------------------------------------------------------------------------------------------