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-rw-r--r--rand/src/distributions/dirichlet.rs128
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-// Copyright 2018 Developers of the Rand project.
-// Copyright 2013 The Rust Project Developers.
-//
-// 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 dirichlet distribution.
-#![allow(deprecated)]
-#![allow(clippy::all)]
-
-use crate::Rng;
-use crate::distributions::Distribution;
-use crate::distributions::gamma::Gamma;
-
-/// The dirichelet distribution `Dirichlet(alpha)`.
-///
-/// The Dirichlet distribution is a family of continuous multivariate
-/// probability distributions parameterized by a vector alpha of positive reals.
-/// It is a multivariate generalization of the beta distribution.
-#[deprecated(since="0.7.0", note="moved to rand_distr crate")]
-#[derive(Clone, Debug)]
-pub struct Dirichlet {
- /// Concentration parameters (alpha)
- alpha: Vec<f64>,
-}
-
-impl Dirichlet {
- /// Construct a new `Dirichlet` with the given alpha parameter `alpha`.
- ///
- /// # Panics
- /// - if `alpha.len() < 2`
- ///
- #[inline]
- pub fn new<V: Into<Vec<f64>>>(alpha: V) -> Dirichlet {
- let a = alpha.into();
- assert!(a.len() > 1);
- for i in 0..a.len() {
- assert!(a[i] > 0.0);
- }
-
- Dirichlet { alpha: a }
- }
-
- /// Construct a new `Dirichlet` with the given shape parameter `alpha` and `size`.
- ///
- /// # Panics
- /// - if `alpha <= 0.0`
- /// - if `size < 2`
- ///
- #[inline]
- pub fn new_with_param(alpha: f64, size: usize) -> Dirichlet {
- assert!(alpha > 0.0);
- assert!(size > 1);
- Dirichlet {
- alpha: vec![alpha; size],
- }
- }
-}
-
-impl Distribution<Vec<f64>> for Dirichlet {
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Vec<f64> {
- let n = self.alpha.len();
- let mut samples = vec![0.0f64; n];
- let mut sum = 0.0f64;
-
- for i in 0..n {
- let g = Gamma::new(self.alpha[i], 1.0);
- samples[i] = g.sample(rng);
- sum += samples[i];
- }
- let invacc = 1.0 / sum;
- for i in 0..n {
- samples[i] *= invacc;
- }
- samples
- }
-}
-
-#[cfg(test)]
-mod test {
- use super::Dirichlet;
- use crate::distributions::Distribution;
-
- #[test]
- fn test_dirichlet() {
- let d = Dirichlet::new(vec![1.0, 2.0, 3.0]);
- let mut rng = crate::test::rng(221);
- let samples = d.sample(&mut rng);
- let _: Vec<f64> = samples
- .into_iter()
- .map(|x| {
- assert!(x > 0.0);
- x
- })
- .collect();
- }
-
- #[test]
- fn test_dirichlet_with_param() {
- let alpha = 0.5f64;
- let size = 2;
- let d = Dirichlet::new_with_param(alpha, size);
- let mut rng = crate::test::rng(221);
- let samples = d.sample(&mut rng);
- let _: Vec<f64> = samples
- .into_iter()
- .map(|x| {
- assert!(x > 0.0);
- x
- })
- .collect();
- }
-
- #[test]
- #[should_panic]
- fn test_dirichlet_invalid_length() {
- Dirichlet::new_with_param(0.5f64, 1);
- }
-
- #[test]
- #[should_panic]
- fn test_dirichlet_invalid_alpha() {
- Dirichlet::new_with_param(0.0f64, 2);
- }
-}