From fd091b04316db9dc5fafadbd6bdbe60b127408a9 Mon Sep 17 00:00:00 2001
From: Daniel Mueller <deso@posteo.net>
Date: Thu, 2 Jan 2020 08:32:06 -0800
Subject: 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
---
 rand/rand_distr/src/exponential.rs | 145 +++++++++++++++++++++++++++++++++++++
 1 file changed, 145 insertions(+)
 create mode 100644 rand/rand_distr/src/exponential.rs

(limited to 'rand/rand_distr/src/exponential.rs')

diff --git a/rand/rand_distr/src/exponential.rs b/rand/rand_distr/src/exponential.rs
new file mode 100644
index 0000000..8322489
--- /dev/null
+++ b/rand/rand_distr/src/exponential.rs
@@ -0,0 +1,145 @@
+// 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 exponential distribution.
+
+use rand::Rng;
+use crate::{ziggurat_tables, Distribution};
+use crate::utils::{ziggurat, Float};
+
+/// Samples floating-point numbers according to the exponential distribution,
+/// with rate parameter `λ = 1`. This is equivalent to `Exp::new(1.0)` or
+/// sampling with `-rng.gen::<f64>().ln()`, but faster.
+///
+/// See `Exp` for the general exponential distribution.
+///
+/// Implemented via the ZIGNOR variant[^1] of the Ziggurat method. The exact
+/// description in the paper was adjusted to use tables for the exponential
+/// distribution rather than normal.
+///
+/// [^1]: Jurgen A. Doornik (2005). [*An Improved Ziggurat Method to
+///       Generate Normal Random Samples*](
+///       https://www.doornik.com/research/ziggurat.pdf).
+///       Nuffield College, Oxford
+///
+/// # Example
+/// ```
+/// use rand::prelude::*;
+/// use rand_distr::Exp1;
+///
+/// let val: f64 = thread_rng().sample(Exp1);
+/// println!("{}", val);
+/// ```
+#[derive(Clone, Copy, Debug)]
+pub struct Exp1;
+
+impl Distribution<f32> for Exp1 {
+    #[inline]
+    fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f32 {
+        // TODO: use optimal 32-bit implementation
+        let x: f64 = self.sample(rng);
+        x as f32
+    }
+}
+
+// This could be done via `-rng.gen::<f64>().ln()` but that is slower.
+impl Distribution<f64> for Exp1 {
+    #[inline]
+    fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64 {
+        #[inline]
+        fn pdf(x: f64) -> f64 {
+            (-x).exp()
+        }
+        #[inline]
+        fn zero_case<R: Rng + ?Sized>(rng: &mut R, _u: f64) -> f64 {
+            ziggurat_tables::ZIG_EXP_R - rng.gen::<f64>().ln()
+        }
+
+        ziggurat(rng, false,
+                 &ziggurat_tables::ZIG_EXP_X,
+                 &ziggurat_tables::ZIG_EXP_F,
+                 pdf, zero_case)
+    }
+}
+
+/// The exponential distribution `Exp(lambda)`.
+///
+/// This distribution has density function: `f(x) = lambda * exp(-lambda * x)`
+/// for `x > 0`.
+/// 
+/// Note that [`Exp1`](crate::Exp1) is an optimised implementation for `lambda = 1`.
+///
+/// # Example
+///
+/// ```
+/// use rand_distr::{Exp, Distribution};
+///
+/// let exp = Exp::new(2.0).unwrap();
+/// let v = exp.sample(&mut rand::thread_rng());
+/// println!("{} is from a Exp(2) distribution", v);
+/// ```
+#[derive(Clone, Copy, Debug)]
+pub struct Exp<N> {
+    /// `lambda` stored as `1/lambda`, since this is what we scale by.
+    lambda_inverse: N
+}
+
+/// Error type returned from `Exp::new`.
+#[derive(Clone, Copy, Debug, PartialEq, Eq)]
+pub enum Error {
+    /// `lambda <= 0` or `nan`.
+    LambdaTooSmall,
+}
+
+impl<N: Float> Exp<N>
+where Exp1: Distribution<N>
+{
+    /// Construct a new `Exp` with the given shape parameter
+    /// `lambda`.
+    #[inline]
+    pub fn new(lambda: N) -> Result<Exp<N>, Error> {
+        if !(lambda > N::from(0.0)) {
+            return Err(Error::LambdaTooSmall);
+        }
+        Ok(Exp { lambda_inverse: N::from(1.0) / lambda })
+    }
+}
+
+impl<N: Float> Distribution<N> for Exp<N>
+where Exp1: Distribution<N>
+{
+    fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> N {
+        rng.sample(Exp1) * self.lambda_inverse
+    }
+}
+
+#[cfg(test)]
+mod test {
+    use crate::Distribution;
+    use super::Exp;
+
+    #[test]
+    fn test_exp() {
+        let exp = Exp::new(10.0).unwrap();
+        let mut rng = crate::test::rng(221);
+        for _ in 0..1000 {
+            assert!(exp.sample(&mut rng) >= 0.0);
+        }
+    }
+    #[test]
+    #[should_panic]
+    fn test_exp_invalid_lambda_zero() {
+        Exp::new(0.0).unwrap();
+    }
+    #[test]
+    #[should_panic]
+    fn test_exp_invalid_lambda_neg() {
+        Exp::new(-10.0).unwrap();
+    }
+}
-- 
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