Update nitrokey crate to 0.2.3

This change updates the nitrokey crate to version 0.2.3. This version
bumps the rand crate used to 0.6.1, which in turn requires an additional
set of dependencies.

Import subrepo nitrokey/:nitrokey at b3e2adc5bb1300441ca74cc7672617c042f3ea31
Import subrepo rand/:rand at 73613ff903512e9503e41cc8ba9eae76269dc598
Import subrepo rustc_version/:rustc_version at 0294f2ba2018bf7be672abd53db351ce5055fa02
Import subrepo semver-parser/:semver-parser at 750da9b11a04125231b1fb293866ca036845acee
Import subrepo semver/:semver at 5eb6db94fa03f4d5c64a625a56188f496be47598

1 files changed, 137 insertions, 0 deletions

diff --git a/rand/src/distributions/dirichlet.rs b/rand/src/distributions/dirichlet.rs
new file mode 100644
index 0000000..19384b8
--- /dev/null
+++ b/rand/src/distributions/dirichlet.rs
@@ -0,0 +1,137 @@
+// 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.
+
+use Rng;
+use distributions::Distribution;
+use 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.
+///
+/// # Example
+///
+/// ```
+/// use rand::prelude::*;
+/// use rand::distributions::Dirichlet;
+///
+/// let dirichlet = Dirichlet::new(vec![1.0, 2.0, 3.0]);
+/// let samples = dirichlet.sample(&mut rand::thread_rng());
+/// println!("{:?} is from a Dirichlet([1.0, 2.0, 3.0]) distribution", samples);
+/// ```
+
+#[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 distributions::Distribution;
+
+    #[test]
+    fn test_dirichlet() {
+        let d = Dirichlet::new(vec![1.0, 2.0, 3.0]);
+        let mut rng = ::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 = ::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);
+    }
+}