logo
 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86

// Copyright 2018 Developers of the Rand project.
//
// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
// option. This file may not be copied, modified, or distributed
// except according to those terms.
//! The triangular distribution.

use Rng;
use distributions::{Distribution, Standard};

/// The triangular distribution.
///
/// # Example
///
/// ```rust
/// use rand::distributions::{Triangular, Distribution};
///
/// let d = Triangular::new(0., 5., 2.5);
/// let v = d.sample(&mut rand::thread_rng());
/// println!("{} is from a triangular distribution", v);
/// ```
#[derive(Clone, Copy, Debug)]
pub struct Triangular {
    min: f64,
    max: f64,
    mode: f64,
}

impl Triangular {
    /// Construct a new `Triangular` with minimum `min`, maximum `max` and mode
    /// `mode`.
    ///
    /// # Panics
    ///
    /// If `max < mode`, `mode < max` or `max == min`.
    ///
    #[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);
        }
    }
}