Struct rand_distr::Triangular

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

The triangular distribution.

A continuous probability distribution parameterised by a range, and a mode (most likely value) within that range.

The probability density function is triangular. For a similar distribution with a smooth PDF, see the Pert distribution.

Example

use rand_distr::{Triangular, Distribution};

let d = Triangular::new(0., 5., 2.5).unwrap();
let v = d.sample(&mut rand::thread_rng());
println!("{} is from a triangular distribution", v);

Methods

impl<N: Float> Triangular<N> where
    Standard: Distribution<N>, 

pub fn new(min: N, max: N, mode: N) -> Result<Triangular<N>, TriangularError>

Set up the Triangular distribution with defined min, max and mode.

Trait Implementations

impl<N: Clone> Clone for Triangular<N>

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

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<N: Copy> Copy for Triangular<N>

impl<N: Debug> Debug for Triangular<N>

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

Formats the value using the given formatter.

impl<N: Float> Distribution<N> for Triangular<N> where
    Standard: Distribution<N>, 

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

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.