| // 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 Weibull distribution. |
| |
| use Rng; |
| use distributions::{Distribution, OpenClosed01}; |
| |
| /// Samples floating-point numbers according to the Weibull distribution |
| /// |
| /// # Example |
| /// ``` |
| /// use rand::prelude::*; |
| /// use rand::distributions::Weibull; |
| /// |
| /// let val: f64 = SmallRng::from_entropy().sample(Weibull::new(1., 10.)); |
| /// println!("{}", val); |
| /// ``` |
| #[derive(Clone, Copy, Debug)] |
| pub struct Weibull { |
| inv_shape: f64, |
| scale: f64, |
| } |
| |
| impl Weibull { |
| /// Construct a new `Weibull` distribution with given `scale` and `shape`. |
| /// |
| /// # Panics |
| /// |
| /// `scale` and `shape` have to be non-zero and positive. |
| pub fn new(scale: f64, shape: f64) -> Weibull { |
| assert!((scale > 0.) & (shape > 0.)); |
| Weibull { inv_shape: 1./shape, scale } |
| } |
| } |
| |
| impl Distribution<f64> for Weibull { |
| fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64 { |
| let x: f64 = rng.sample(OpenClosed01); |
| self.scale * (-x.ln()).powf(self.inv_shape) |
| } |
| } |
| |
| #[cfg(test)] |
| mod tests { |
| use distributions::Distribution; |
| use super::Weibull; |
| |
| #[test] |
| #[should_panic] |
| fn invalid() { |
| Weibull::new(0., 0.); |
| } |
| |
| #[test] |
| fn sample() { |
| let scale = 1.0; |
| let shape = 2.0; |
| let d = Weibull::new(scale, shape); |
| let mut rng = ::test::rng(1); |
| for _ in 0..1000 { |
| let r = d.sample(&mut rng); |
| assert!(r >= 0.); |
| } |
| } |
| } |