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.

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 Sample<f64> for Normal

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

Deprecated since 0.5.0

: use Distribution instead

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

impl IndependentSample<f64> for Normal

fn ind_sample<R: Rng>(&self, rng: &mut R) -> f64

Deprecated since 0.5.0

: use Distribution instead

Generate a random value.

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.

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.