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authorDaniel Mueller <deso@posteo.net>2020-01-02 08:32:06 -0800
committerDaniel Mueller <deso@posteo.net>2020-01-02 08:32:06 -0800
commitfd091b04316db9dc5fafadbd6bdbe60b127408a9 (patch)
treef202270f7ae5cedc513be03833a26148d9b5e219 /rand/rand_distr/src/pert.rs
parent8161cdb26f98e65b39c603ddf7a614cc87c77a1c (diff)
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Update nitrokey crate to 0.4.0
This change finally updates the version of the nitrokey crate that we consume to 0.4.0. Along with that we update rand_core, one of its dependencies, to 0.5.1. Further more we add cfg-if in version 0.1.10 and getrandom in version 0.1.13, both of which are now new (non-development) dependencies. Import subrepo nitrokey/:nitrokey at e81057037e9b4f370b64c0a030a725bc6bdfb870 Import subrepo cfg-if/:cfg-if at 4484a6faf816ff8058088ad857b0c6bb2f4b02b2 Import subrepo getrandom/:getrandom at d661aa7e1b8cc80b47dabe3d2135b3b47d2858af Import subrepo rand/:rand at d877ed528248b52d947e0484364a4e1ae59ca502
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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 PERT distribution.
+
+use rand::Rng;
+use crate::{Distribution, Beta, StandardNormal, Exp1, Open01};
+use crate::utils::Float;
+
+/// The PERT distribution.
+///
+/// Similar to the [`Triangular`] distribution, the PERT distribution is
+/// parameterised by a range and a mode within that range. Unlike the
+/// [`Triangular`] distribution, the probability density function of the PERT
+/// distribution is smooth, with a configurable weighting around the mode.
+///
+/// # Example
+///
+/// ```rust
+/// use rand_distr::{Pert, Distribution};
+///
+/// let d = Pert::new(0., 5., 2.5).unwrap();
+/// let v = d.sample(&mut rand::thread_rng());
+/// println!("{} is from a PERT distribution", v);
+/// ```
+///
+/// [`Triangular`]: crate::Triangular
+#[derive(Clone, Copy, Debug)]
+pub struct Pert<N> {
+ min: N,
+ range: N,
+ beta: Beta<N>,
+}
+
+/// Error type returned from [`Pert`] constructors.
+#[derive(Clone, Copy, Debug, PartialEq, Eq)]
+pub enum PertError {
+ /// `max < min` or `min` or `max` is NaN.
+ RangeTooSmall,
+ /// `mode < min` or `mode > max` or `mode` is NaN.
+ ModeRange,
+ /// `shape < 0` or `shape` is NaN
+ ShapeTooSmall,
+}
+
+impl<N: Float> Pert<N>
+where StandardNormal: Distribution<N>, Exp1: Distribution<N>, Open01: Distribution<N>
+{
+ /// Set up the PERT distribution with defined `min`, `max` and `mode`.
+ ///
+ /// This is equivalent to calling `Pert::new_shape` with `shape == 4.0`.
+ #[inline]
+ pub fn new(min: N, max: N, mode: N) -> Result<Pert<N>, PertError> {
+ Pert::new_with_shape(min, max, mode, N::from(4.))
+ }
+
+ /// Set up the PERT distribution with defined `min`, `max`, `mode` and
+ /// `shape`.
+ pub fn new_with_shape(min: N, max: N, mode: N, shape: N) -> Result<Pert<N>, PertError> {
+ if !(max > min) {
+ return Err(PertError::RangeTooSmall);
+ }
+ if !(mode >= min && max >= mode) {
+ return Err(PertError::ModeRange);
+ }
+ if !(shape >= N::from(0.)) {
+ return Err(PertError::ShapeTooSmall);
+ }
+
+ let range = max - min;
+ let mu = (min + max + shape * mode) / (shape + N::from(2.));
+ let v = if mu == mode {
+ shape * N::from(0.5) + N::from(1.)
+ } else {
+ (mu - min) * (N::from(2.) * mode - min - max)
+ / ((mode - mu) * (max - min))
+ };
+ let w = v * (max - mu) / (mu - min);
+ let beta = Beta::new(v, w).map_err(|_| PertError::RangeTooSmall)?;
+ Ok(Pert{ min, range, beta })
+ }
+}
+
+impl<N: Float> Distribution<N> for Pert<N>
+where StandardNormal: Distribution<N>, Exp1: Distribution<N>, Open01: Distribution<N>
+{
+ #[inline]
+ fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> N {
+ self.beta.sample(rng) * self.range + self.min
+ }
+}
+
+#[cfg(test)]
+mod test {
+ use std::f64;
+ use super::*;
+
+ #[test]
+ fn test_pert() {
+ for &(min, max, mode) in &[
+ (-1., 1., 0.),
+ (1., 2., 1.),
+ (5., 25., 25.),
+ ] {
+ let _distr = Pert::new(min, max, mode).unwrap();
+ // TODO: test correctness
+ }
+
+ for &(min, max, mode) in &[
+ (-1., 1., 2.),
+ (-1., 1., -2.),
+ (2., 1., 1.),
+ ] {
+ assert!(Pert::new(min, max, mode).is_err());
+ }
+ }
+
+ #[test]
+ fn value_stability() {
+ let rng = crate::test::rng(860);
+ let distr = Pert::new(2., 10., 3.).unwrap(); // mean = 4, var = 12/7
+ let seq = distr.sample_iter(rng).take(5).collect::<Vec<f64>>();
+ println!("seq: {:?}", seq);
+ let expected = vec![4.631484136029422, 3.307201472321789,
+ 3.29995019556348, 3.66835483991721, 3.514246139933899];
+ assert!(seq == expected);
+ }
+}