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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)]

    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);
        }
    }

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