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Diffstat (limited to 'rand/rand_distr/src/triangular.rs')
-rw-r--r-- | rand/rand_distr/src/triangular.rs | 125 |
1 files changed, 0 insertions, 125 deletions
diff --git a/rand/rand_distr/src/triangular.rs b/rand/rand_distr/src/triangular.rs deleted file mode 100644 index dd0bbfb..0000000 --- a/rand/rand_distr/src/triangular.rs +++ /dev/null @@ -1,125 +0,0 @@ -// 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 rand::Rng; -use crate::{Distribution, Standard}; -use crate::utils::Float; - -/// The triangular distribution. -/// -/// A continuous probability distribution parameterised by a range, and a mode -/// (most likely value) within that range. -/// -/// The probability density function is triangular. For a similar distribution -/// with a smooth PDF, see the [`Pert`] distribution. -/// -/// # Example -/// -/// ```rust -/// use rand_distr::{Triangular, Distribution}; -/// -/// let d = Triangular::new(0., 5., 2.5).unwrap(); -/// let v = d.sample(&mut rand::thread_rng()); -/// println!("{} is from a triangular distribution", v); -/// ``` -/// -/// [`Pert`]: crate::Pert -#[derive(Clone, Copy, Debug)] -pub struct Triangular<N> { - min: N, - max: N, - mode: N, -} - -/// Error type returned from [`Triangular::new`]. -#[derive(Clone, Copy, Debug, PartialEq, Eq)] -pub enum TriangularError { - /// `max < min` or `min` or `max` is NaN. - RangeTooSmall, - /// `mode < min` or `mode > max` or `mode` is NaN. - ModeRange, -} - -impl<N: Float> Triangular<N> -where Standard: Distribution<N> -{ - /// Set up the Triangular distribution with defined `min`, `max` and `mode`. - #[inline] - pub fn new(min: N, max: N, mode: N) -> Result<Triangular<N>, TriangularError> { - if !(max >= min) { - return Err(TriangularError::RangeTooSmall); - } - if !(mode >= min && max >= mode) { - return Err(TriangularError::ModeRange); - } - Ok(Triangular { min, max, mode }) - } -} - -impl<N: Float> Distribution<N> for Triangular<N> -where Standard: Distribution<N> -{ - #[inline] - fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> N { - let f: N = rng.sample(Standard); - let diff_mode_min = self.mode - self.min; - let range = self.max - self.min; - let f_range = f * range; - if f_range < diff_mode_min { - self.min + (f_range * diff_mode_min).sqrt() - } else { - self.max - ((range - f_range) * (self.max - self.mode)).sqrt() - } - } -} - -#[cfg(test)] -mod test { - use std::f64; - use rand::{Rng, rngs::mock}; - use super::*; - - #[test] - fn test_triangular() { - let mut half_rng = mock::StepRng::new(0x8000_0000_0000_0000, 0); - assert_eq!(half_rng.gen::<f64>(), 0.5); - for &(min, max, mode, median) in &[ - (-1., 1., 0., 0.), - (1., 2., 1., 2. - 0.5f64.sqrt()), - (5., 25., 25., 5. + 200f64.sqrt()), - (1e-5, 1e5, 1e-3, 1e5 - 4999999949.5f64.sqrt()), - (0., 1., 0.9, 0.45f64.sqrt()), - (-4., -0.5, -2., -4.0 + 3.5f64.sqrt()), - ] { - println!("{} {} {} {}", min, max, mode, median); - let distr = Triangular::new(min, max, mode).unwrap(); - // Test correct value at median: - assert_eq!(distr.sample(&mut half_rng), median); - } - - for &(min, max, mode) in &[ - (-1., 1., 2.), - (-1., 1., -2.), - (2., 1., 1.), - ] { - assert!(Triangular::new(min, max, mode).is_err()); - } - } - - #[test] - fn value_stability() { - let rng = crate::test::rng(860); - let distr = Triangular::new(2., 10., 3.).unwrap(); - let seq = distr.sample_iter(rng).take(5).collect::<Vec<f64>>(); - println!("seq: {:?}", seq); - let expected = vec![5.74373257511361, 7.890059162791258, - 4.7256280652553455, 2.9474808121184077, 3.058301946314053]; - assert!(seq == expected); - } -} |