Struct ndarray_rand::rand_distr::Weibull

pub struct Weibull<N> { /* fields omitted */ }

Samples floating-point numbers according to the Weibull distribution

Example

use rand::prelude::*;
use rand_distr::Weibull;

let val: f64 = thread_rng().sample(Weibull::new(1., 10.).unwrap());
println!("{}", val);

Methods

impl<N> Weibull<N> where
    N: Float,
    OpenClosed01: Distribution<N>, 

pub fn new(scale: N, shape: N) -> Result<Weibull<N>, Error>

Construct a new Weibull distribution with given scale and shape.

Trait Implementations

impl<N> Debug for Weibull<N> where
    N: Debug, 

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

Formats the value using the given formatter.

impl<N> Copy for Weibull<N> where
    N: Copy, 

impl<N> Clone for Weibull<N> where
    N: Clone, 

fn clone(&self) -> Weibull<N>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<N> Distribution<N> for Weibull<N> where
    N: Float,
    OpenClosed01: Distribution<N>, 

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

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

Important traits for DistIter<D, R, T>

impl<D, R, T> Iterator for DistIter<D, R, T> where
    D: Distribution<T>,
    R: Rng,  type Item = T;

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.