Struct rand::distributions::StandardNormal

pub struct StandardNormal;

Samples floating-point numbers according to the normal distribution N(0, 1) (a.k.a. a standard normal, or Gaussian). This is equivalent to Normal::new(0.0, 1.0) but faster.

See Normal for the general normal distribution.

Implemented via the ZIGNOR variant¹ of the Ziggurat method.

Example

use rand::prelude::*;
use rand::distributions::StandardNormal;

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

---

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

Trait Implementations

impl Distribution<f64> for StandardNormal

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 Clone for StandardNormal

fn clone(&self) -> StandardNormal

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Copy for StandardNormal

impl Debug for StandardNormal

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

Formats the value using the given formatter.