Struct rand_distr::Normal

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pub struct Normal<N> { /* 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_distr::{Normal, Distribution};

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

Methods

impl<N: Float> Normal<N> where
    StandardNormal: Distribution<N>, [−]

pub fn new(mean: N, std_dev: N) -> Result<Normal<N>, Error>[−]

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

Trait Implementations

impl<N: Clone> Clone for Normal<N>[+]

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fn clone(&self) -> Normal<N>[−]

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)[−]

Performs copy-assignment from source.

impl<N: Copy> Copy for Normal<N>

impl<N: Debug> Debug for Normal<N>[+]

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

Formats the value using the given formatter.

impl<N: Float> Distribution<N> for Normal<N> where
    StandardNormal: Distribution<N>, [+]

[+] Show hidden undocumented items

fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> N[−]

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, [−]

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