Make linear_fitting function generic

russell_lab/README.md

@@ -308,12 +308,12 @@ Fit a line through a set of points. The line has slope `m` and intercepts the y
 
 ```rust
 use russell_lab::algo::linear_fitting;
-use russell_lab::{approx_eq, StrError, Vector};
+use russell_lab::{approx_eq, StrError};
 
 fn main() -> Result<(), StrError> {
     // model: c is the y value @ x = 0; m is the slope
-    let x = Vector::from(&[0.0, 1.0, 3.0, 5.0]);
-    let y = Vector::from(&[1.0, 0.0, 2.0, 4.0]);
+    let x = [0.0, 1.0, 3.0, 5.0];
+    let y = [1.0, 0.0, 2.0, 4.0];
     let (c, m) = linear_fitting(&x, &y, false)?;
     println!("c = {}, m = {}", c, m);
     approx_eq(c, 0.1864406779661015, 1e-15);

russell_lab/examples/algo_linear_fitting.rs

@@ -11,8 +11,8 @@ const OUT_DIR: &str = "/tmp/russell_lab/";
 
 fn main() -> Result<(), StrError> {
     // model: c is the y value @ x = 0; m is the slope
-    let x = Vector::from(&[0.0, 1.0, 3.0, 5.0]);
-    let y = Vector::from(&[1.0, 0.0, 2.0, 4.0]);
+    let x = [0.0, 1.0, 3.0, 5.0];
+    let y = [1.0, 0.0, 2.0, 4.0];
     let (c, m) = linear_fitting(&x, &y, false)?;
     println!("c = {}, m = {}", c, m);
     approx_eq(c, 0.1864406779661015, 1e-15);
@@ -28,7 +28,7 @@ fn main() -> Result<(), StrError> {
         .set_marker_line_color("red")
         .set_marker_color("red");
     curve_fit.draw_ray(0.0, c, RayEndpoint::Slope(m));
-    curve_dat.draw(x.as_data(), y.as_data());
+    curve_dat.draw(&x, &y);
     let mut plot = Plot::new();
     let path = format!("{}/algo_linear_fitting_1.svg", OUT_DIR);
     plot.add(&curve_dat)

russell_lab/src/algo/linear_fitting.rs

@@ -1,4 +1,6 @@
-use crate::{StrError, Vector};
+use crate::StrError;
+use num_traits::{cast, Num, NumCast};
+use std::ops::{AddAssign, Mul};
 
 /// Calculates the parameters of a linear model using least squares fitting
 ///
@@ -19,42 +21,55 @@ use crate::{StrError, Vector};
 /// * If `pass_through_zero == True` and `sum(X) == 0`
 /// * If `pass_through_zero == False` and the line is vertical (null denominator)
 ///
+/// # Panics
+///
+/// This function may panic if the number type cannot be converted to `f64`.
+///
 /// # Examples
 ///
 /// ![Linear fitting](https://raw.githubusercontent.com/cpmech/russell/main/russell_lab/data/figures/algo_linear_fitting_1.svg)
 ///
 /// ```
-/// use russell_lab::{approx_eq, linear_fitting, StrError, Vector};
+/// use russell_lab::{approx_eq, linear_fitting, StrError};
 ///
 /// fn main() -> Result<(), StrError> {
 ///     // model: c is the y value @ x = 0; m is the slope
-///     let x = Vector::from(&[0.0, 1.0, 3.0, 5.0]);
-///     let y = Vector::from(&[1.0, 0.0, 2.0, 4.0]);
+///     let x = [0.0, 1.0, 3.0, 5.0];
+///     let y = [1.0, 0.0, 2.0, 4.0];
 ///     let (c, m) = linear_fitting(&x, &y, false)?;
 ///     approx_eq(c, 0.1864406779661015, 1e-15);
 ///     approx_eq(m, 0.6949152542372882, 1e-15);
 ///     Ok(())
 /// }
 /// ```
-pub fn linear_fitting(x: &Vector, y: &Vector, pass_through_zero: bool) -> Result<(f64, f64), StrError> {
+pub fn linear_fitting<T>(x: &[T], y: &[T], pass_through_zero: bool) -> Result<(f64, f64), StrError>
+where
+    T: AddAssign + Copy + Mul + Num + NumCast,
+{
     // dimension
-    let nn = x.dim();
-    if y.dim() != nn {
-        return Err("vectors must have the same dimension");
+    let nn = x.len();
+    if y.len() != nn {
+        return Err("arrays must have the same lengths");
     }
 
     // sums
-    let mut sum_x = 0.0;
-    let mut sum_y = 0.0;
-    let mut sum_xy = 0.0;
-    let mut sum_xx = 0.0;
+    let mut t_sum_x = T::zero();
+    let mut t_sum_y = T::zero();
+    let mut t_sum_xy = T::zero();
+    let mut t_sum_xx = T::zero();
     for i in 0..nn {
-        sum_x += x[i];
-        sum_y += y[i];
-        sum_xy += x[i] * y[i];
-        sum_xx += x[i] * x[i];
+        t_sum_x += x[i];
+        t_sum_y += y[i];
+        t_sum_xy += x[i] * y[i];
+        t_sum_xx += x[i] * x[i];
     }
 
+    // cast sums to f64
+    let sum_x: f64 = cast(t_sum_x).unwrap();
+    let sum_y: f64 = cast(t_sum_y).unwrap();
+    let sum_xy: f64 = cast(t_sum_xy).unwrap();
+    let sum_xx: f64 = cast(t_sum_xx).unwrap();
+
     // calculate parameters
     let c;
     let m;
@@ -83,22 +98,37 @@ pub fn linear_fitting(x: &Vector, y: &Vector, pass_through_zero: bool) -> Result
 #[cfg(test)]
 mod tests {
     use super::linear_fitting;
-    use crate::{approx_eq, Vector};
+    use crate::approx_eq;
 
     #[test]
     fn linear_fitting_handles_errors() {
-        let x = Vector::from(&[1.0, 2.0]);
-        let y = Vector::from(&[6.0, 5.0, 7.0, 10.0]);
+        let x = [1.0, 2.0];
+        let y = [6.0, 5.0, 7.0, 10.0];
         assert_eq!(
             linear_fitting(&x, &y, false).err(),
-            Some("vectors must have the same dimension")
+            Some("arrays must have the same lengths")
         );
     }
 
     #[test]
     fn linear_fitting_works() {
-        let x = Vector::from(&[1.0, 2.0, 3.0, 4.0]);
-        let y = Vector::from(&[6.0, 5.0, 7.0, 10.0]);
+        // f64 (heap)
+
+        let x = vec![1.0, 2.0, 3.0, 4.0];
+        let y = vec![6.0, 5.0, 7.0, 10.0];
+
+        let (c, m) = linear_fitting(&x, &y, false).unwrap();
+        assert_eq!(c, 3.5);
+        assert_eq!(m, 1.4);
+
+        let (c, m) = linear_fitting(&x, &y, true).unwrap();
+        assert_eq!(c, 0.0);
+        approx_eq(m, 2.566666666666667, 1e-16);
+
+        // usize (stack)
+
+        let x = [1, 2, 3, 4_usize];
+        let y = [6, 5, 7, 10_usize];
 
         let (c, m) = linear_fitting(&x, &y, false).unwrap();
         assert_eq!(c, 3.5);
@@ -107,19 +137,32 @@ mod tests {
         let (c, m) = linear_fitting(&x, &y, true).unwrap();
         assert_eq!(c, 0.0);
         approx_eq(m, 2.566666666666667, 1e-16);
+
+        // i32 (slice)
+
+        let x = &[1, 2, 3, 4_i32];
+        let y = &[6, 5, 7, 10_i32];
+
+        let (c, m) = linear_fitting(x, y, false).unwrap();
+        assert_eq!(c, 3.5);
+        assert_eq!(m, 1.4);
+
+        let (c, m) = linear_fitting(x, y, true).unwrap();
+        assert_eq!(c, 0.0);
+        approx_eq(m, 2.566666666666667, 1e-16);
     }
 
     #[test]
     fn linear_fitting_handles_division_by_zero() {
-        let x = Vector::from(&[1.0, 1.0, 1.0, 1.0]);
-        let y = Vector::from(&[1.0, 2.0, 3.0, 4.0]);
+        let x = [1.0, 1.0, 1.0, 1.0];
+        let y = [1.0, 2.0, 3.0, 4.0];
 
         let (c, m) = linear_fitting(&x, &y, false).unwrap();
         assert_eq!(c, 0.0);
         assert_eq!(m, f64::INFINITY);
 
-        let x = Vector::from(&[0.0, 0.0, 0.0, 0.0]);
-        let y = Vector::from(&[1.0, 2.0, 3.0, 4.0]);
+        let x = [0.0, 0.0, 0.0, 0.0];
+        let y = [1.0, 2.0, 3.0, 4.0];
         let (c, m) = linear_fitting(&x, &y, true).unwrap();
         assert_eq!(c, 0.0);
         assert_eq!(m, f64::INFINITY);