kernel_density_estimation/kernel/
normal.rs

1//! Normal (Gaussian) kernel function.
2
3use crate::float::{float, KDEFloat};
4use crate::kernel::Kernel;
5
6use std::f64::consts::PI;
7
8/// Normal (Gaussian) kernel function.
9#[derive(Clone, Copy, Debug)]
10pub struct Normal;
11
12impl<F: KDEFloat> Kernel<F> for Normal {
13    fn pdf(&self, x: F) -> F {
14        let frac_sqrt2pi = F::one() / F::sqrt(float!(2.0) * float!(PI));
15        let exponent = float!(-1.0 / 2.0) * x.powi(2);
16        frac_sqrt2pi * exponent.exp()
17    }
18}
19
20#[cfg(test)]
21mod tests {
22    use super::Normal;
23    use crate::kernel::Kernel;
24    use approx::*;
25
26    #[test]
27    fn normal() {
28        let kernel = Normal;
29
30        let x = 0.0;
31        let res = kernel.pdf(x);
32        assert_relative_eq!(res, 0.39894, epsilon = 1.0e-5);
33
34        let x = -1.0;
35        let res = kernel.pdf(x);
36        assert_relative_eq!(res, 0.24197, epsilon = 1.0e-5);
37
38        let x = 1.0;
39        let res = kernel.pdf(x);
40        assert_relative_eq!(res, 0.24197, epsilon = 1.0e-5);
41    }
42}