fmt

rand_distr/src/weibull.rs

@@ -20,9 +20,9 @@ use rand::Rng;
 /// to model reliability data, life data, and accelerated life testing data.
 ///
 /// # Density function
-/// 
+///
 /// `f(x; λ, k) = (k / λ) * (x / λ)^(k - 1) * exp(-(x / λ)^k)` for `x >= 0`.
-/// 
+///
 /// # Plot
 ///
 /// The following plot shows the Weibull distribution with various values of `λ` and `k`.
@@ -37,9 +37,9 @@ use rand::Rng;
 /// let val: f64 = rand::rng().sample(Weibull::new(1., 10.).unwrap());
 /// println!("{}", val);
 /// ```
-/// 
+///
 /// # Numerics
-/// 
+///
 /// For small `k` like `< 0.005`, even with `f64` a significant number of samples will be so small that they underflow to `0.0`
 /// or so big they overflow to `inf`. This is a limitation of the floating point representation and not specific to this implementation.
 #[derive(Clone, Copy, Debug, PartialEq)]