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diff --git a/vendor/rand/src/distributions/exponential.rs b/vendor/rand/src/distributions/exponential.rs
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index c3c924c..0000000
--- a/vendor/rand/src/distributions/exponential.rs
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-// Copyright 2013 The Rust Project Developers. See the COPYRIGHT
-// file at the top-level directory of this distribution and at
-// http://rust-lang.org/COPYRIGHT.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// http://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or http://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The exponential distribution.
-
-use {Rng, Rand};
-use distributions::{ziggurat, ziggurat_tables, Sample, IndependentSample};
-
-/// A wrapper around an `f64` to generate Exp(1) random numbers.
-///
-/// See `Exp` for the general exponential distribution.
-///
-/// Implemented via the ZIGNOR variant[1] of the Ziggurat method. The
-/// exact description in the paper was adjusted to use tables for the
-/// exponential distribution rather than normal.
-///
-/// [1]: Jurgen A. Doornik (2005). [*An Improved Ziggurat Method to
-/// Generate Normal Random
-/// Samples*](http://www.doornik.com/research/ziggurat.pdf). Nuffield
-/// College, Oxford
-///
-/// # Example
-///
-/// ```rust
-/// use rand::distributions::exponential::Exp1;
-///
-/// let Exp1(x) = rand::random();
-/// println!("{}", x);
-/// ```
-#[derive(Clone, Copy, Debug)]
-pub struct Exp1(pub f64);
-
-// This could be done via `-rng.gen::<f64>().ln()` but that is slower.
-impl Rand for Exp1 {
-    #[inline]
-    fn rand<R:Rng>(rng: &mut R) -> Exp1 {
-        #[inline]
-        fn pdf(x: f64) -> f64 {
-            (-x).exp()
-        }
-        #[inline]
-        fn zero_case<R:Rng>(rng: &mut R, _u: f64) -> f64 {
-            ziggurat_tables::ZIG_EXP_R - rng.gen::<f64>().ln()
-        }
-
-        Exp1(ziggurat(rng, false,
-                      &ziggurat_tables::ZIG_EXP_X,
-                      &ziggurat_tables::ZIG_EXP_F,
-                      pdf, zero_case))
-    }
-}
-
-/// The exponential distribution `Exp(lambda)`.
-///
-/// This distribution has density function: `f(x) = lambda *
-/// exp(-lambda * x)` for `x > 0`.
-///
-/// # Example
-///
-/// ```rust
-/// use rand::distributions::{Exp, IndependentSample};
-///
-/// let exp = Exp::new(2.0);
-/// let v = exp.ind_sample(&mut rand::thread_rng());
-/// println!("{} is from a Exp(2) distribution", v);
-/// ```
-#[derive(Clone, Copy, Debug)]
-pub struct Exp {
-    /// `lambda` stored as `1/lambda`, since this is what we scale by.
-    lambda_inverse: f64
-}
-
-impl Exp {
-    /// Construct a new `Exp` with the given shape parameter
-    /// `lambda`. Panics if `lambda <= 0`.
-    #[inline]
-    pub fn new(lambda: f64) -> Exp {
-        assert!(lambda > 0.0, "Exp::new called with `lambda` <= 0");
-        Exp { lambda_inverse: 1.0 / lambda }
-    }
-}
-
-impl Sample<f64> for Exp {
-    fn sample<R: Rng>(&mut self, rng: &mut R) -> f64 { self.ind_sample(rng) }
-}
-impl IndependentSample<f64> for Exp {
-    fn ind_sample<R: Rng>(&self, rng: &mut R) -> f64 {
-        let Exp1(n) = rng.gen::<Exp1>();
-        n * self.lambda_inverse
-    }
-}
-
-#[cfg(test)]
-mod test {
-    use distributions::{Sample, IndependentSample};
-    use super::Exp;
-
-    #[test]
-    fn test_exp() {
-        let mut exp = Exp::new(10.0);
-        let mut rng = ::test::rng();
-        for _ in 0..1000 {
-            assert!(exp.sample(&mut rng) >= 0.0);
-            assert!(exp.ind_sample(&mut rng) >= 0.0);
-        }
-    }
-    #[test]
-    #[should_panic]
-    fn test_exp_invalid_lambda_zero() {
-        Exp::new(0.0);
-    }
-    #[test]
-    #[should_panic]
-    fn test_exp_invalid_lambda_neg() {
-        Exp::new(-10.0);
-    }
-}