Struct rand_distr::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_distr::StandardNormal;

let val: f64 = thread_rng().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 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 Debug for StandardNormal

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

Formats the value using the given formatter.

impl Distribution<f32> for StandardNormal

fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f32

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

fn sample_iter<R>(self, rng: R) -> DistIter<Self, R, T>

where R: Rng, Self: Sized,

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

fn map<F, S>(self, func: F) -> DistMap<Self, F, T, S>

where F: Fn(T) -> S, Self: Sized,

Create a distribution of values of ‘S’ by mapping the output of Self through the closure F

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.

fn sample_iter<R>(self, rng: R) -> DistIter<Self, R, T>

where R: Rng, Self: Sized,

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

fn map<F, S>(self, func: F) -> DistMap<Self, F, T, S>

where F: Fn(T) -> S, Self: Sized,

Create a distribution of values of ‘S’ by mapping the output of Self through the closure F

impl Copy for StandardNormal