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use Rng;
use distributions::{Distribution, Standard};
#[derive(Clone, Copy, Debug)]
pub struct Triangular {
min: f64,
max: f64,
mode: f64,
}
impl Triangular {
#[inline]
pub fn new(min: f64, max: f64, mode: f64) -> Triangular {
assert!(max >= mode);
assert!(mode >= min);
assert!(max != min);
Triangular { min, max, mode }
}
}
impl Distribution<f64> for Triangular {
#[inline]
fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64 {
let f: f64 = rng.sample(Standard);
let diff_mode_min = self.mode - self.min;
let diff_max_min = self.max - self.min;
if f * diff_max_min < diff_mode_min {
self.min + (f * diff_max_min * diff_mode_min).sqrt()
} else {
self.max - ((1. - f) * diff_max_min * (self.max - self.mode)).sqrt()
}
}
}
#[cfg(test)]
mod test {
use distributions::Distribution;
use super::Triangular;
#[test]
fn test_new() {
for &(min, max, mode) in &[
(-1., 1., 0.), (1., 2., 1.), (5., 25., 25.), (1e-5, 1e5, 1e-3),
(0., 1., 0.9), (-4., -0.5, -2.), (-13.039, 8.41, 1.17),
] {
println!("{} {} {}", min, max, mode);
let _ = Triangular::new(min, max, mode);
}
}
#[test]
fn test_sample() {
let norm = Triangular::new(0., 1., 0.5);
let mut rng = ::test::rng(1);
for _ in 0..1000 {
norm.sample(&mut rng);
}
}
}