Moved activations module and update imports in dense_nn and logreg

src/compute/models/activations.rs

@@ -0,0 +1,135 @@
+use crate::matrix::{Matrix, SeriesOps};
+
+pub fn sigmoid(x: &Matrix<f64>) -> Matrix<f64> {
+    x.map(|v| 1.0 / (1.0 + (-v).exp()))
+}
+
+pub fn dsigmoid(y: &Matrix<f64>) -> Matrix<f64> {
+    // derivative w.r.t. pre-activation; takes y = sigmoid(x)
+    y.map(|v| v * (1.0 - v))
+}
+
+pub fn relu(x: &Matrix<f64>) -> Matrix<f64> {
+    x.map(|v| if v > 0.0 { v } else { 0.0 })
+}
+
+pub fn drelu(x: &Matrix<f64>) -> Matrix<f64> {
+    x.map(|v| if v > 0.0 { 1.0 } else { 0.0 })
+}
+
+pub fn leaky_relu(x: &Matrix<f64>) -> Matrix<f64> {
+    x.map(|v| if v > 0.0 { v } else { 0.01 * v })
+}
+
+pub fn dleaky_relu(x: &Matrix<f64>) -> Matrix<f64> {
+    x.map(|v| if v > 0.0 { 1.0 } else { 0.01 })
+}
+
+mod tests {
+    use super::*;
+
+    // Helper function to round all elements in a matrix to n decimal places
+    fn _round_matrix(mat: &Matrix<f64>, decimals: u32) -> Matrix<f64> {
+        let factor = 10f64.powi(decimals as i32);
+        let rounded: Vec<f64> = mat
+            .to_vec()
+            .iter()
+            .map(|v| (v * factor).round() / factor)
+            .collect();
+        Matrix::from_vec(rounded, mat.rows(), mat.cols())
+    }
+
+    #[test]
+    fn test_sigmoid() {
+        let x = Matrix::from_vec(vec![-1.0, 0.0, 1.0], 3, 1);
+        let expected = Matrix::from_vec(vec![0.26894142, 0.5, 0.73105858], 3, 1);
+        let result = sigmoid(&x);
+        assert_eq!(_round_matrix(&result, 6), _round_matrix(&expected, 6));
+    }
+
+    #[test]
+    fn test_sigmoid_edge_case() {
+        let x = Matrix::from_vec(vec![-1000.0, 0.0, 1000.0], 3, 1);
+        let expected = Matrix::from_vec(vec![0.0, 0.5, 1.0], 3, 1);
+        let result = sigmoid(&x);
+
+        for (r, e) in result.data().iter().zip(expected.data().iter()) {
+            assert!((r - e).abs() < 1e-6);
+        }
+    }
+
+    #[test]
+    fn test_relu() {
+        let x = Matrix::from_vec(vec![-1.0, 0.0, 1.0], 3, 1);
+        let expected = Matrix::from_vec(vec![0.0, 0.0, 1.0], 3, 1);
+        assert_eq!(relu(&x), expected);
+    }
+
+    #[test]
+    fn test_relu_edge_case() {
+        let x = Matrix::from_vec(vec![-1e-10, 0.0, 1e10], 3, 1);
+        let expected = Matrix::from_vec(vec![0.0, 0.0, 1e10], 3, 1);
+        assert_eq!(relu(&x), expected);
+    }
+
+    #[test]
+    fn test_dsigmoid() {
+        let y = Matrix::from_vec(vec![0.26894142, 0.5, 0.73105858], 3, 1);
+        let expected = Matrix::from_vec(vec![0.19661193, 0.25, 0.19661193], 3, 1);
+        let result = dsigmoid(&y);
+        assert_eq!(_round_matrix(&result, 6), _round_matrix(&expected, 6));
+    }
+
+    #[test]
+    fn test_dsigmoid_edge_case() {
+        let y = Matrix::from_vec(vec![0.0, 0.5, 1.0], 3, 1); // Assume these are outputs from sigmoid(x)
+        let expected = Matrix::from_vec(vec![0.0, 0.25, 0.0], 3, 1);
+        let result = dsigmoid(&y);
+
+        for (r, e) in result.data().iter().zip(expected.data().iter()) {
+            assert!((r - e).abs() < 1e-6);
+        }
+    }
+
+    #[test]
+    fn test_drelu() {
+        let x = Matrix::from_vec(vec![-1.0, 0.0, 1.0], 3, 1);
+        let expected = Matrix::from_vec(vec![0.0, 0.0, 1.0], 3, 1);
+        assert_eq!(drelu(&x), expected);
+    }
+
+    #[test]
+    fn test_drelu_edge_case() {
+        let x = Matrix::from_vec(vec![-1e-10, 0.0, 1e10], 3, 1);
+        let expected = Matrix::from_vec(vec![0.0, 0.0, 1.0], 3, 1);
+        assert_eq!(drelu(&x), expected);
+    }
+
+    #[test]
+    fn test_leaky_relu() {
+        let x = Matrix::from_vec(vec![-1.0, 0.0, 1.0], 3, 1);
+        let expected = Matrix::from_vec(vec![-0.01, 0.0, 1.0], 3, 1);
+        assert_eq!(leaky_relu(&x), expected);
+    }
+
+    #[test]
+    fn test_leaky_relu_edge_case() {
+        let x = Matrix::from_vec(vec![-1e-10, 0.0, 1e10], 3, 1);
+        let expected = Matrix::from_vec(vec![-1e-12, 0.0, 1e10], 3, 1);
+        assert_eq!(leaky_relu(&x), expected);
+    }
+
+    #[test]
+    fn test_dleaky_relu() {
+        let x = Matrix::from_vec(vec![-1.0, 0.0, 1.0], 3, 1);
+        let expected = Matrix::from_vec(vec![0.01, 0.01, 1.0], 3, 1);
+        assert_eq!(dleaky_relu(&x), expected);
+    }
+
+    #[test]
+    fn test_dleaky_relu_edge_case() {
+        let x = Matrix::from_vec(vec![-1e-10, 0.0, 1e10], 3, 1);
+        let expected = Matrix::from_vec(vec![0.01, 0.01, 1.0], 3, 1);
+        assert_eq!(dleaky_relu(&x), expectewd);
+    }
+}

src/compute/models/dense_nn.rs

@@ -1,4 +1,4 @@
-use crate::compute::activations::{drelu, relu, sigmoid};
+use crate::compute::models::activations::{drelu, relu, sigmoid};
 use crate::matrix::{Matrix, SeriesOps};
 use rand::prelude::*;
 

src/compute/models/logreg.rs

@@ -1,4 +1,4 @@
-use crate::compute::activations::sigmoid;
+use crate::compute::models::activations::sigmoid;
 use crate::matrix::{Matrix, SeriesOps};
 
 pub struct LogReg {

src/compute/models/mod.rs

@@ -3,4 +3,5 @@ pub mod logreg;
 pub mod dense_nn;
 pub mod k_means;    
 pub mod pca;
-pub mod gaussian_nb;
+pub mod gaussian_nb;
+pub mod activations;