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-rw-r--r--rand/src/distributions/exponential.rs108
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diff --git a/rand/src/distributions/exponential.rs b/rand/src/distributions/exponential.rs
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-// Copyright 2018 Developers of the Rand project.
-// Copyright 2013 The Rust Project Developers.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-
-//! The exponential distribution.
-#![allow(deprecated)]
-
-use crate::{Rng};
-use crate::distributions::{ziggurat_tables, Distribution};
-use crate::distributions::utils::ziggurat;
-
-/// Samples floating-point numbers according to the exponential distribution,
-/// with rate parameter `λ = 1`. This is equivalent to `Exp::new(1.0)` or
-/// sampling with `-rng.gen::<f64>().ln()`, but faster.
-///
-/// 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*](
-/// https://www.doornik.com/research/ziggurat.pdf).
-/// Nuffield College, Oxford
-#[deprecated(since="0.7.0", note="moved to rand_distr crate")]
-#[derive(Clone, Copy, Debug)]
-pub struct Exp1;
-
-// This could be done via `-rng.gen::<f64>().ln()` but that is slower.
-impl Distribution<f64> for Exp1 {
- #[inline]
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64 {
- #[inline]
- fn pdf(x: f64) -> f64 {
- (-x).exp()
- }
- #[inline]
- fn zero_case<R: Rng + ?Sized>(rng: &mut R, _u: f64) -> f64 {
- ziggurat_tables::ZIG_EXP_R - rng.gen::<f64>().ln()
- }
-
- 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`.
-///
-/// Note that [`Exp1`](crate::distributions::Exp1) is an optimised implementation for `lambda = 1`.
-#[deprecated(since="0.7.0", note="moved to rand_distr crate")]
-#[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 Distribution<f64> for Exp {
- fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64 {
- let n: f64 = rng.sample(Exp1);
- n * self.lambda_inverse
- }
-}
-
-#[cfg(test)]
-mod test {
- use crate::distributions::Distribution;
- use super::Exp;
-
- #[test]
- fn test_exp() {
- let exp = Exp::new(10.0);
- let mut rng = crate::test::rng(221);
- for _ in 0..1000 {
- assert!(exp.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);
- }
-}