Struct rand::distributions::Normal

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pub struct Normal { /* fields omitted */ }

[−] Expand description

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 Distribution<f64> for Normal[+]

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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[+]

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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[+]

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

Formats the value using the given formatter.