Struct rand::distributions::Normal  [−][src]
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[src] 
impl Normalpub fn new(mean: f64, std_dev: f64) -> Normal[src] 
pub fn new(mean: f64, std_dev: f64) -> NormalConstruct a new Normal distribution with the given mean and
standard deviation.
Panics
Panics if std_dev < 0.
Trait Implementations
impl Clone for Normal[src] 
impl Clone for Normalfn clone(&self) -> Normal[src] 
fn clone(&self) -> NormalReturns a copy of the value. Read more
fn clone_from(&mut self, source: &Self)1.0.0[src] 
fn clone_from(&mut self, source: &Self)1.0.0
[src]Performs copy-assignment from source. Read more
impl Copy for Normal[src] 
impl Copy for Normalimpl Debug for Normal[src] 
impl Debug for Normalfn fmt(&self, f: &mut Formatter) -> Result[src] 
fn fmt(&self, f: &mut Formatter) -> ResultFormats the value using the given formatter. Read more
impl Distribution<f64> for Normal[src] 
impl Distribution<f64> for Normalfn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64[src] 
fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64Generate a random value of T, using rng as the source of randomness.
ⓘImportant traits for DistIter<'a, D, R, T>fn sample_iter<'a, R>(&'a self, rng: &'a mut R) -> DistIter<'a, Self, R, T> where
    Self: Sized,
    R: Rng, [src] 
ⓘImportant traits for DistIter<'a, D, R, 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. Read more
impl Sample<f64> for Normal[src] 
impl Sample<f64> for Normalfn sample<R: Rng>(&mut self, rng: &mut R) -> f64[src] 
fn sample<R: Rng>(&mut self, rng: &mut R) -> f64Deprecated since 0.5.0
: use Distribution instead
Generate a random value of Support, using rng as the source of randomness. Read more
impl IndependentSample<f64> for Normal[src] 
impl IndependentSample<f64> for Normalfn ind_sample<R: Rng>(&self, rng: &mut R) -> f64[src] 
fn ind_sample<R: Rng>(&self, rng: &mut R) -> f64Deprecated since 0.5.0
: use Distribution instead
Generate a random value.