commit af58b6fa182aabca1885cb1f6c0dd284d9e1fc9e
author Graham Dennis <graham.dennis@gmail.com> Sat Mar 21 17:43:13 2015 +1100
committer Graham Dennis <graham.dennis@gmail.com> Mon Mar 23 21:47:23 2015 +1100
tree ac698c8cafd511eb9ffeff7a61de48dfacbf3d9e
parent d2060d6af92662ad8aec78eda481a25bbba63c3e

missing `Copy` impls for distributions.

src/distributions/gamma.rs

diff --git a/src/distributions/gamma.rs b/src/distributions/gamma.rs
index 5f6aaa4..f7ee4fc 100644
--- a/src/distributions/gamma.rs
+++ b/src/distributions/gamma.rs
@@ -51,10 +51,12 @@
 /// for Generating Gamma Variables" *ACM Trans. Math. Softw.* 26, 3
 /// (September 2000),
 /// 363-372. DOI:[10.1145/358407.358414](http://doi.acm.org/10.1145/358407.358414)
+#[derive(Copy)]
 pub struct Gamma {
     repr: GammaRepr,
 }
 
+#[derive(Copy)]
 enum GammaRepr {
     Large(GammaLargeShape),
     One(Exp),
@@ -75,6 +77,7 @@
 ///
 /// See `Gamma` for sampling from a Gamma distribution with general
 /// shape parameters.
+#[derive(Copy)]
 struct GammaSmallShape {
     inv_shape: f64,
     large_shape: GammaLargeShape
@@ -84,6 +87,7 @@
 ///
 /// See `Gamma` for sampling from a Gamma distribution with general
 /// shape parameters.
+#[derive(Copy)]
 struct GammaLargeShape {
     scale: f64,
     c: f64,
@@ -192,10 +196,12 @@
 /// let v = chi.ind_sample(&mut rand::thread_rng());
 /// println!("{} is from a χ²(11) distribution", v)
 /// ```
+#[derive(Copy)]
 pub struct ChiSquared {
     repr: ChiSquaredRepr,
 }
 
+#[derive(Copy)]
 enum ChiSquaredRepr {
     // k == 1, Gamma(alpha, ..) is particularly slow for alpha < 1,
     // e.g. when alpha = 1/2 as it would be for this case, so special-
@@ -248,6 +254,7 @@
 /// let v = f.ind_sample(&mut rand::thread_rng());
 /// println!("{} is from an F(2, 32) distribution", v)
 /// ```
+#[derive(Copy)]
 pub struct FisherF {
     numer: ChiSquared,
     denom: ChiSquared,
@@ -291,6 +298,7 @@
 /// let v = t.ind_sample(&mut rand::thread_rng());
 /// println!("{} is from a t(11) distribution", v)
 /// ```
+#[derive(Copy)]
 pub struct StudentT {
     chi: ChiSquared,
     dof: f64

src/distributions/mod.rs

diff --git a/src/distributions/mod.rs b/src/distributions/mod.rs
index 703b316..571411b 100644
--- a/src/distributions/mod.rs
+++ b/src/distributions/mod.rs
@@ -58,6 +58,8 @@
     _marker: marker::PhantomData<fn() -> Sup>,
 }
 
+impl<Sup> Copy for RandSample<Sup> {}
+
 impl<Sup: Rand> Sample<Sup> for RandSample<Sup> {
     fn sample<R: Rng>(&mut self, rng: &mut R) -> Sup { self.ind_sample(rng) }
 }
@@ -75,6 +77,7 @@
 }
 
 /// A value with a particular weight for use with `WeightedChoice`.
+#[derive(Copy)]
 pub struct Weighted<T> {
     /// The numerical weight of this item
     pub weight: u32,

src/distributions/range.rs

diff --git a/src/distributions/range.rs b/src/distributions/range.rs
index 4fe281c..932bfae 100644
--- a/src/distributions/range.rs
+++ b/src/distributions/range.rs
@@ -47,6 +47,7 @@
 ///     println!("{}", sum);
 /// }
 /// ```
+#[derive(Copy)]
 pub struct Range<X> {
     low: X,
     range: X,