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

1 files changed, 24 insertions, 66 deletions

diff --git a/rand/src/distributions/gamma.rs b/rand/src/distributions/gamma.rs
index 43ac2bc..b5a97f5 100644
--- a/rand/src/distributions/gamma.rs
+++ b/rand/src/distributions/gamma.rs
@@ -8,13 +8,14 @@
 // except according to those terms.
 
 //! The Gamma and derived distributions.
+#![allow(deprecated)]
 
 use self::GammaRepr::*;
 use self::ChiSquaredRepr::*;
 
-use Rng;
-use distributions::normal::StandardNormal;
-use distributions::{Distribution, Exp, Open01};
+use crate::Rng;
+use crate::distributions::normal::StandardNormal;
+use crate::distributions::{Distribution, Exp, Open01};
 
 /// The Gamma distribution `Gamma(shape, scale)` distribution.
 ///
@@ -32,20 +33,11 @@ use distributions::{Distribution, Exp, Open01};
 /// == 1`, and using the boosting technique described in that paper for
 /// `shape < 1`.
 ///
-/// # Example
-///
-/// ```
-/// use rand::distributions::{Distribution, Gamma};
-///
-/// let gamma = Gamma::new(2.0, 5.0);
-/// let v = gamma.sample(&mut rand::thread_rng());
-/// println!("{} is from a Gamma(2, 5) distribution", v);
-/// ```
-///
 /// [^1]: George Marsaglia and Wai Wan Tsang. 2000. "A Simple Method for
 ///       Generating Gamma Variables" *ACM Trans. Math. Softw.* 26, 3
 ///       (September 2000), 363-372.
 ///       DOI:[10.1145/358407.358414](https://doi.acm.org/10.1145/358407.358414)
+#[deprecated(since="0.7.0", note="moved to rand_distr crate")]
 #[derive(Clone, Copy, Debug)]
 pub struct Gamma {
     repr: GammaRepr,
@@ -174,16 +166,7 @@ impl Distribution<f64> for GammaLargeShape {
 /// of `k` independent standard normal random variables. For other
 /// `k`, this uses the equivalent characterisation
 /// `χ²(k) = Gamma(k/2, 2)`.
-///
-/// # Example
-///
-/// ```
-/// use rand::distributions::{ChiSquared, Distribution};
-///
-/// let chi = ChiSquared::new(11.0);
-/// let v = chi.sample(&mut rand::thread_rng());
-/// println!("{} is from a χ²(11) distribution", v)
-/// ```
+#[deprecated(since="0.7.0", note="moved to rand_distr crate")]
 #[derive(Clone, Copy, Debug)]
 pub struct ChiSquared {
     repr: ChiSquaredRepr,
@@ -229,16 +212,7 @@ impl Distribution<f64> for ChiSquared {
 /// This distribution is equivalent to the ratio of two normalised
 /// chi-squared distributions, that is, `F(m,n) = (χ²(m)/m) /
 /// (χ²(n)/n)`.
-///
-/// # Example
-///
-/// ```
-/// use rand::distributions::{FisherF, Distribution};
-///
-/// let f = FisherF::new(2.0, 32.0);
-/// let v = f.sample(&mut rand::thread_rng());
-/// println!("{} is from an F(2, 32) distribution", v)
-/// ```
+#[deprecated(since="0.7.0", note="moved to rand_distr crate")]
 #[derive(Clone, Copy, Debug)]
 pub struct FisherF {
     numer: ChiSquared,
@@ -270,16 +244,7 @@ impl Distribution<f64> for FisherF {
 
 /// The Student t distribution, `t(nu)`, where `nu` is the degrees of
 /// freedom.
-///
-/// # Example
-///
-/// ```
-/// use rand::distributions::{StudentT, Distribution};
-///
-/// let t = StudentT::new(11.0);
-/// let v = t.sample(&mut rand::thread_rng());
-/// println!("{} is from a t(11) distribution", v)
-/// ```
+#[deprecated(since="0.7.0", note="moved to rand_distr crate")]
 #[derive(Clone, Copy, Debug)]
 pub struct StudentT {
     chi: ChiSquared,
@@ -305,16 +270,7 @@ impl Distribution<f64> for StudentT {
 }
 
 /// The Beta distribution with shape parameters `alpha` and `beta`.
-///
-/// # Example
-///
-/// ```
-/// use rand::distributions::{Distribution, Beta};
-///
-/// let beta = Beta::new(2.0, 5.0);
-/// let v = beta.sample(&mut rand::thread_rng());
-/// println!("{} is from a Beta(2, 5) distribution", v);
-/// ```
+#[deprecated(since="0.7.0", note="moved to rand_distr crate")]
 #[derive(Clone, Copy, Debug)]
 pub struct Beta {
     gamma_a: Gamma,
@@ -345,30 +301,32 @@ impl Distribution<f64> for Beta {
 
 #[cfg(test)]
 mod test {
-    use distributions::Distribution;
+    use crate::distributions::Distribution;
     use super::{Beta, ChiSquared, StudentT, FisherF};
 
+    const N: u32 = 100;
+
     #[test]
     fn test_chi_squared_one() {
         let chi = ChiSquared::new(1.0);
-        let mut rng = ::test::rng(201);
-        for _ in 0..1000 {
+        let mut rng = crate::test::rng(201);
+        for _ in 0..N {
             chi.sample(&mut rng);
         }
     }
     #[test]
     fn test_chi_squared_small() {
         let chi = ChiSquared::new(0.5);
-        let mut rng = ::test::rng(202);
-        for _ in 0..1000 {
+        let mut rng = crate::test::rng(202);
+        for _ in 0..N {
             chi.sample(&mut rng);
         }
     }
     #[test]
     fn test_chi_squared_large() {
         let chi = ChiSquared::new(30.0);
-        let mut rng = ::test::rng(203);
-        for _ in 0..1000 {
+        let mut rng = crate::test::rng(203);
+        for _ in 0..N {
             chi.sample(&mut rng);
         }
     }
@@ -381,8 +339,8 @@ mod test {
     #[test]
     fn test_f() {
         let f = FisherF::new(2.0, 32.0);
-        let mut rng = ::test::rng(204);
-        for _ in 0..1000 {
+        let mut rng = crate::test::rng(204);
+        for _ in 0..N {
             f.sample(&mut rng);
         }
     }
@@ -390,8 +348,8 @@ mod test {
     #[test]
     fn test_t() {
         let t = StudentT::new(11.0);
-        let mut rng = ::test::rng(205);
-        for _ in 0..1000 {
+        let mut rng = crate::test::rng(205);
+        for _ in 0..N {
             t.sample(&mut rng);
         }
     }
@@ -399,8 +357,8 @@ mod test {
     #[test]
     fn test_beta() {
         let beta = Beta::new(1.0, 2.0);
-        let mut rng = ::test::rng(201);
-        for _ in 0..1000 {
+        let mut rng = crate::test::rng(201);
+        for _ in 0..N {
             beta.sample(&mut rng);
         }
     }