Struct rand_distr::Normal

pub struct Normal<F> where
    F: Float,
    StandardNormal: Distribution<F>,  { /* 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_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)

Implementations

impl<F> Normal<F> where
    F: Float,
    StandardNormal: Distribution<F>, 

pub fn new(mean: F, std_dev: F) -> Result<Normal<F>, Error>

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

Trait Implementations

impl<F: Clone> Clone for Normal<F> where
    F: Float,
    StandardNormal: Distribution<F>, 

fn clone(&self) -> Normal<F>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<F: Copy> Copy for Normal<F> where
    F: Float,
    StandardNormal: Distribution<F>, 

impl<F: Debug> Debug for Normal<F> where
    F: Float,
    StandardNormal: Distribution<F>, 

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

Formats the value using the given formatter.

impl<F> Distribution<F> for Normal<F> where
    F: Float,
    StandardNormal: Distribution<F>, 

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

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.