Struct rand::distributions::Exp1

pub struct Exp1;

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 variant¹ of the Ziggurat method. The exact description in the paper was adjusted to use tables for the exponential distribution rather than normal.

Example

use rand::prelude::*;
use rand::distributions::Exp1;

let val: f64 = SmallRng::from_entropy().sample(Exp1);
println!("{}", val);

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1. Jurgen A. Doornik (2005). An Improved Ziggurat Method to Generate Normal Random Samples. Nuffield College, Oxford ↩

Trait Implementations

impl Distribution<f64> for Exp1

fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64

Generate a random value of T, using rng as the source of randomness.

Important traits for DistIter<'a, D, R, T>

impl<'a, D, R, T> Iterator for DistIter<'a, D, R, T> where
    D: Distribution<T>,
    R: Rng + 'a,  type Item = T;

fn sample_iter<'a, R>(&'a self, rng: &'a mut R) -> DistIter<'a, Self, R, T> where     Self: Sized,     R: Rng,

Create an iterator that generates random values of T, using rng as the source of randomness.

impl Copy for Exp1

impl Clone for Exp1

fn clone(&self) -> Exp1

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for Exp1

fn fmt(&self, f: &mut Formatter) -> Result

Formats the value using the given formatter.