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// 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.);
}
}
}
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