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Diffstat (limited to 'vendor/rand/src/distributions/normal.rs')
| -rw-r--r-- | vendor/rand/src/distributions/normal.rs | 201 |
1 files changed, 0 insertions, 201 deletions
diff --git a/vendor/rand/src/distributions/normal.rs b/vendor/rand/src/distributions/normal.rs deleted file mode 100644 index 280613d..0000000 --- a/vendor/rand/src/distributions/normal.rs +++ /dev/null @@ -1,201 +0,0 @@ -// 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 normal and derived distributions. - -use {Rng, Rand, Open01}; -use distributions::{ziggurat, ziggurat_tables, Sample, IndependentSample}; - -/// A wrapper around an `f64` to generate N(0, 1) random numbers -/// (a.k.a. a standard normal, or Gaussian). -/// -/// See `Normal` for the general normal distribution. -/// -/// Implemented via the ZIGNOR variant[1] of the Ziggurat method. -/// -/// [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::normal::StandardNormal; -/// -/// let StandardNormal(x) = rand::random(); -/// println!("{}", x); -/// ``` -#[derive(Clone, Copy, Debug)] -pub struct StandardNormal(pub f64); - -impl Rand for StandardNormal { - fn rand<R:Rng>(rng: &mut R) -> StandardNormal { - #[inline] - fn pdf(x: f64) -> f64 { - (-x*x/2.0).exp() - } - #[inline] - fn zero_case<R:Rng>(rng: &mut R, u: f64) -> f64 { - // compute a random number in the tail by hand - - // strange initial conditions, because the loop is not - // do-while, so the condition should be true on the first - // run, they get overwritten anyway (0 < 1, so these are - // good). - let mut x = 1.0f64; - let mut y = 0.0f64; - - while -2.0 * y < x * x { - let Open01(x_) = rng.gen::<Open01<f64>>(); - let Open01(y_) = rng.gen::<Open01<f64>>(); - - x = x_.ln() / ziggurat_tables::ZIG_NORM_R; - y = y_.ln(); - } - - if u < 0.0 { x - ziggurat_tables::ZIG_NORM_R } else { ziggurat_tables::ZIG_NORM_R - x } - } - - StandardNormal(ziggurat( - rng, - true, // this is symmetric - &ziggurat_tables::ZIG_NORM_X, - &ziggurat_tables::ZIG_NORM_F, - pdf, zero_case)) - } -} - -/// The normal distribution `N(mean, std_dev**2)`. -/// -/// This uses the ZIGNOR variant of the Ziggurat method, see -/// `StandardNormal` for more details. -/// -/// # Example -/// -/// ```rust -/// use rand::distributions::{Normal, IndependentSample}; -/// -/// // mean 2, standard deviation 3 -/// let normal = Normal::new(2.0, 3.0); -/// let v = normal.ind_sample(&mut rand::thread_rng()); -/// println!("{} is from a N(2, 9) distribution", v) -/// ``` -#[derive(Clone, Copy, Debug)] -pub struct Normal { - mean: f64, - std_dev: f64, -} - -impl Normal { - /// Construct a new `Normal` distribution with the given mean and - /// standard deviation. - /// - /// # Panics - /// - /// Panics if `std_dev < 0`. - #[inline] - pub fn new(mean: f64, std_dev: f64) -> Normal { - assert!(std_dev >= 0.0, "Normal::new called with `std_dev` < 0"); - Normal { - mean: mean, - std_dev: std_dev - } - } -} -impl Sample<f64> for Normal { - fn sample<R: Rng>(&mut self, rng: &mut R) -> f64 { self.ind_sample(rng) } -} -impl IndependentSample<f64> for Normal { - fn ind_sample<R: Rng>(&self, rng: &mut R) -> f64 { - let StandardNormal(n) = rng.gen::<StandardNormal>(); - self.mean + self.std_dev * n - } -} - - -/// The log-normal distribution `ln N(mean, std_dev**2)`. -/// -/// If `X` is log-normal distributed, then `ln(X)` is `N(mean, -/// std_dev**2)` distributed. -/// -/// # Example -/// -/// ```rust -/// use rand::distributions::{LogNormal, IndependentSample}; -/// -/// // mean 2, standard deviation 3 -/// let log_normal = LogNormal::new(2.0, 3.0); -/// let v = log_normal.ind_sample(&mut rand::thread_rng()); -/// println!("{} is from an ln N(2, 9) distribution", v) -/// ``` -#[derive(Clone, Copy, Debug)] -pub struct LogNormal { - norm: Normal -} - -impl LogNormal { - /// Construct a new `LogNormal` distribution with the given mean - /// and standard deviation. - /// - /// # Panics - /// - /// Panics if `std_dev < 0`. - #[inline] - pub fn new(mean: f64, std_dev: f64) -> LogNormal { - assert!(std_dev >= 0.0, "LogNormal::new called with `std_dev` < 0"); - LogNormal { norm: Normal::new(mean, std_dev) } - } -} -impl Sample<f64> for LogNormal { - fn sample<R: Rng>(&mut self, rng: &mut R) -> f64 { self.ind_sample(rng) } -} -impl IndependentSample<f64> for LogNormal { - fn ind_sample<R: Rng>(&self, rng: &mut R) -> f64 { - self.norm.ind_sample(rng).exp() - } -} - -#[cfg(test)] -mod tests { - use distributions::{Sample, IndependentSample}; - use super::{Normal, LogNormal}; - - #[test] - fn test_normal() { - let mut norm = Normal::new(10.0, 10.0); - let mut rng = ::test::rng(); - for _ in 0..1000 { - norm.sample(&mut rng); - norm.ind_sample(&mut rng); - } - } - #[test] - #[should_panic] - fn test_normal_invalid_sd() { - Normal::new(10.0, -1.0); - } - - - #[test] - fn test_log_normal() { - let mut lnorm = LogNormal::new(10.0, 10.0); - let mut rng = ::test::rng(); - for _ in 0..1000 { - lnorm.sample(&mut rng); - lnorm.ind_sample(&mut rng); - } - } - #[test] - #[should_panic] - fn test_log_normal_invalid_sd() { - LogNormal::new(10.0, -1.0); - } -} |