Struct rand::distributions::Normal

pub struct Normal { /* fields omitted */ }

The normal distribution N(mean, std_dev**2).

This uses the ZIGNOR variant of the Ziggurat method, see StandardNormal for more details.

Note that StandardNormal is an optimised implementation for mean 0, and standard deviation 1.

Example

use rand::distributions::{Normal, Distribution};

// mean 2, standard deviation 3
let normal = Normal::new(2.0, 3.0);
let v = normal.sample(&mut rand::thread_rng());
println!("{} is from a N(2, 9) distribution", v)

Methods

impl Normal

pub fn new(mean: f64, std_dev: f64) -> Normal

Construct a new Normal distribution with the given mean and standard deviation.

Panics

Panics if std_dev < 0.

Trait Implementations

impl Clone for Normal

fn clone(&self) -> Normal

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Copy for Normal

impl Debug for Normal

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

Formats the value using the given formatter.

impl Distribution<f64> for Normal

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.