Struct nannou::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);

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

Trait Implementations

impl Debug for StandardNormal

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

Formats the value using the given formatter.

impl Distribution<f64> for StandardNormal

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

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

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

impl Copy for StandardNormal

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.