2 files changed, 21 insertions, 28 deletions
diff --git a/rand/examples/monte-carlo.rs b/rand/examples/monte-carlo.rs
index 9162996..39c779f 100644
--- a/rand/examples/monte-carlo.rs
+++ b/rand/examples/monte-carlo.rs
@@ -11,7 +11,7 @@
 //!
 //! Imagine that we have a square with sides of length 2 and a unit circle
 //! (radius = 1), both centered at the origin. The areas are:
-//! 
+//!
 //! ```text
 //!     area of circle  = πr² = π * r * r = π
 //!     area of square  = 2² = 4
@@ -24,28 +24,25 @@
 //! the square at random, calculate the fraction that fall within the circle,
 //! and multiply this fraction by 4.
 
-#![cfg(feature="std")]
-
-
-extern crate rand;
+#![cfg(feature = "std")]
 
 use rand::distributions::{Distribution, Uniform};
 
 fn main() {
-   let range = Uniform::new(-1.0f64, 1.0);
-   let mut rng = rand::thread_rng();
-
-   let total = 1_000_000;
-   let mut in_circle = 0;
-
-   for _ in 0..total {
-       let a = range.sample(&mut rng);
-       let b = range.sample(&mut rng);
-       if a*a + b*b <= 1.0 {
-           in_circle += 1;
-       }
-   }
-
-   // prints something close to 3.14159...
-   println!("π is approximately {}", 4. * (in_circle as f64) / (total as f64));
+    let range = Uniform::new(-1.0f64, 1.0);
+    let mut rng = rand::thread_rng();
+
+    let total = 1_000_000;
+    let mut in_circle = 0;
+
+    for _ in 0..total {
+        let a = range.sample(&mut rng);
+        let b = range.sample(&mut rng);
+        if a*a + b*b <= 1.0 {
+            in_circle += 1;
+        }
+    }
+
+    // prints something close to 3.14159...
+    println!("π is approximately {}", 4. * (in_circle as f64) / (total as f64));
 }
diff --git a/rand/examples/monty-hall.rs b/rand/examples/monty-hall.rs
index 0932c5e..9fe5839 100644
--- a/rand/examples/monty-hall.rs
+++ b/rand/examples/monty-hall.rs
@@ -26,13 +26,10 @@
 //!
 //! [Monty Hall Problem]: https://en.wikipedia.org/wiki/Monty_Hall_problem
 
-#![cfg(feature="std")]
+#![cfg(feature = "std")]
 
-
-extern crate rand;
-
-use rand::Rng;
 use rand::distributions::{Distribution, Uniform};
+use rand::Rng;
 
 struct SimulationResult {
     win: bool,
@@ -40,8 +37,7 @@ struct SimulationResult {
 }
 
 // Run a single simulation of the Monty Hall problem.
-fn simulate<R: Rng>(random_door: &Uniform<u32>, rng: &mut R)
-                    -> SimulationResult {
+fn simulate<R: Rng>(random_door: &Uniform<u32>, rng: &mut R) -> SimulationResult {
     let car = random_door.sample(rng);
 
     // This is our initial choice