std::rand: move normal and exponential to their own file.

Author: huonw

src/libstd/rand/distributions/exponential.rs

@@ -0,0 +1,141 @@
+// 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 rand::{Rng, Rand};
+use rand::distributions::{ziggurat, ziggurat_tables, Sample, IndependentSample};
+
+/// A wrapper around an `f64` to generate Exp(1) random numbers.
+///
+/// See `Exp` for the general exponential distribution.Note that this
+ // has to be unwrapped before use as an `f64` (using either
+/// `*` or `cast::transmute` is safe).
+///
+/// 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
+pub struct Exp1(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 std::rand;
+/// use std::rand::distributions::{Exp, IndependentSample};
+///
+/// fn main() {
+///     let exp = Exp::new(2.0);
+///     let v = exp.ind_sample(&mut rand::task_rng());
+///     println!("{} is from a Exp(2) distribution", v);
+/// }
+/// ```
+pub struct Exp {
+    /// `lambda` stored as `1/lambda`, since this is what we scale by.
+    priv lambda_inverse: f64
+}
+
+impl Exp {
+    /// Construct a new `Exp` with the given shape parameter
+    /// `lambda`. Fails if `lambda <= 0`.
+    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 {
+        (*rng.gen::<Exp1>()) * self.lambda_inverse
+    }
+}
+
+#[cfg(test)]
+mod test {
+    use rand::*;
+    use super::*;
+    use iter::range;
+    use option::{Some, None};
+
+    #[test]
+    fn test_exp() {
+        let mut exp = Exp::new(10.0);
+        let mut rng = task_rng();
+        for _ in range(0, 1000) {
+            assert!(exp.sample(&mut rng) >= 0.0);
+            assert!(exp.ind_sample(&mut rng) >= 0.0);
+        }
+    }
+    #[test]
+    #[should_fail]
+    fn test_exp_invalid_lambda_zero() {
+        Exp::new(0.0);
+    }
+    #[test]
+    #[should_fail]
+    fn test_exp_invalid_lambda_neg() {
+        Exp::new(-10.0);
+    }
+}
+
+#[cfg(test)]
+mod bench {
+    use extra::test::BenchHarness;
+    use rand::{XorShiftRng, RAND_BENCH_N};
+    use super::*;
+    use iter::range;
+    use option::{Some, None};
+    use mem::size_of;
+
+    #[bench]
+    fn rand_exp(bh: &mut BenchHarness) {
+        let mut rng = XorShiftRng::new();
+        let mut exp = Exp::new(2.71828 * 3.14159);
+
+        bh.iter(|| {
+            for _ in range(0, RAND_BENCH_N) {
+                exp.sample(&mut rng);
+            }
+        });
+        bh.bytes = size_of::<f64>() as u64 * RAND_BENCH_N;
+    }
+}

src/libstd/rand/distributions/gamma.rs

@@ -11,7 +11,8 @@
 //! The Gamma distribution.
 
 use rand::{Rng, Open01};
-use super::{IndependentSample, Sample, StandardNormal, Exp};
+use super::{IndependentSample, Sample, Exp};
+use super::normal::StandardNormal;
 use num;
 
 /// The Gamma distribution `Gamma(shape, scale)` distribution.