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/triangular.rs | 125 ++++++++++++++++++++++++++++++++++++++
 1 file changed, 125 insertions(+)
 create mode 100644 rand/rand_distr/src/triangular.rs

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

diff --git a/rand/rand_distr/src/triangular.rs b/rand/rand_distr/src/triangular.rs
new file mode 100644
index 0000000..dd0bbfb
--- /dev/null
+++ b/rand/rand_distr/src/triangular.rs
@@ -0,0 +1,125 @@
+// 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 triangular distribution.
+
+use rand::Rng;
+use crate::{Distribution, Standard};
+use crate::utils::Float;
+
+/// The triangular distribution.
+/// 
+/// A continuous probability distribution parameterised by a range, and a mode
+/// (most likely value) within that range.
+///
+/// The probability density function is triangular. For a similar distribution
+/// with a smooth PDF, see the [`Pert`] distribution.
+///
+/// # Example
+///
+/// ```rust
+/// use rand_distr::{Triangular, Distribution};
+///
+/// let d = Triangular::new(0., 5., 2.5).unwrap();
+/// let v = d.sample(&mut rand::thread_rng());
+/// println!("{} is from a triangular distribution", v);
+/// ```
+///
+/// [`Pert`]: crate::Pert
+#[derive(Clone, Copy, Debug)]
+pub struct Triangular<N> {
+    min: N,
+    max: N,
+    mode: N,
+}
+
+/// Error type returned from [`Triangular::new`].
+#[derive(Clone, Copy, Debug, PartialEq, Eq)]
+pub enum TriangularError {
+    /// `max < min` or `min` or `max` is NaN.
+    RangeTooSmall,
+    /// `mode < min` or `mode > max` or `mode` is NaN.
+    ModeRange,
+}
+
+impl<N: Float> Triangular<N>
+where Standard: Distribution<N>
+{
+    /// Set up the Triangular distribution with defined `min`, `max` and `mode`.
+    #[inline]
+    pub fn new(min: N, max: N, mode: N) -> Result<Triangular<N>, TriangularError> {
+        if !(max >= min) {
+            return Err(TriangularError::RangeTooSmall);
+        }
+        if !(mode >= min && max >= mode) {
+            return Err(TriangularError::ModeRange);
+        }
+        Ok(Triangular { min, max, mode })
+    }
+}
+
+impl<N: Float> Distribution<N> for Triangular<N>
+where Standard: Distribution<N>
+{
+    #[inline]
+    fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> N {
+        let f: N = rng.sample(Standard);
+        let diff_mode_min = self.mode - self.min;
+        let range = self.max - self.min;
+        let f_range = f * range;
+        if f_range < diff_mode_min {
+            self.min + (f_range * diff_mode_min).sqrt()
+        } else {
+            self.max - ((range - f_range) * (self.max - self.mode)).sqrt()
+        }
+    }
+}
+
+#[cfg(test)]
+mod test {
+    use std::f64;
+    use rand::{Rng, rngs::mock};
+    use super::*;
+
+    #[test]
+    fn test_triangular() {
+        let mut half_rng = mock::StepRng::new(0x8000_0000_0000_0000, 0);
+        assert_eq!(half_rng.gen::<f64>(), 0.5);
+        for &(min, max, mode, median) in &[
+            (-1., 1., 0., 0.),
+            (1., 2., 1., 2. - 0.5f64.sqrt()),
+            (5., 25., 25., 5. + 200f64.sqrt()),
+            (1e-5, 1e5, 1e-3, 1e5 - 4999999949.5f64.sqrt()),
+            (0., 1., 0.9, 0.45f64.sqrt()),
+            (-4., -0.5, -2., -4.0 + 3.5f64.sqrt()),
+        ] {
+            println!("{} {} {} {}", min, max, mode, median);
+            let distr = Triangular::new(min, max, mode).unwrap();
+            // Test correct value at median:
+            assert_eq!(distr.sample(&mut half_rng), median);
+        }
+
+        for &(min, max, mode) in &[
+            (-1., 1., 2.),
+            (-1., 1., -2.),
+            (2., 1., 1.),
+        ] {
+            assert!(Triangular::new(min, max, mode).is_err());
+        }
+    }
+    
+    #[test]
+    fn value_stability() {
+        let rng = crate::test::rng(860);
+        let distr = Triangular::new(2., 10., 3.).unwrap();
+        let seq = distr.sample_iter(rng).take(5).collect::<Vec<f64>>();
+        println!("seq: {:?}", seq);
+        let expected = vec![5.74373257511361, 7.890059162791258,
+                4.7256280652553455, 2.9474808121184077, 3.058301946314053];
+        assert!(seq == expected);
+    }
+}
-- 
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