---

yaml
---
r: 55222
b: refs/heads/snap-stage3
c: 0c34cab
h: refs/heads/master
v: v3

Author: sanxiyn

[refs]

@@ -1,7 +1,7 @@
 ---
 refs/heads/master: 5f13e9ccc2e3328d4cd8ca49f84e6840dd998346
 refs/heads/snap-stage1: e33de59e47c5076a89eadeb38f4934f58a3618a6
-refs/heads/snap-stage3: d3e7c746dddf24935bd55330d20b692fb0e691a6
+refs/heads/snap-stage3: 0c34cab3db76d100ea7bbe4cd776f27b5f971d2c
 refs/heads/try: 8eb2bab100b42f0ba751552d8eff00eb2134c55a
 refs/tags/release-0.1: 1f5c5126e96c79d22cb7862f75304136e204f105
 refs/heads/ndm: f3868061cd7988080c30d6d5bf352a5a5fe2460b

branches/snap-stage3/src/etc/ziggurat_tables.py

@@ -16,9 +16,6 @@ and so can be used to generate any type that implements `Rand`. Type inference
 means that often a simple call to `rand::random()` or `rng.gen()` will
 suffice, but sometimes an annotation is required, e.g. `rand::random::<float>()`.
 
-See the `distributions` submodule for sampling random numbers from
-distributions like normal and exponential.
-
 # Examples
 ~~~
 use core::rand::RngUtil;
@@ -50,9 +47,6 @@ use util;
 use vec;
 use libc::size_t;
 
-#[path="rand/distributions.rs"]
-pub mod distributions;
-
 /// A type that can be randomly generated using an Rng
 pub trait Rand {
     fn rand<R: Rng>(rng: &R) -> Self;