Struct ndarray_rand::rand_distr::Triangular

pub struct Triangular<F> where
    F: Float,
    Standard: Distribution<F>,  { /* 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);

Implementations

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

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

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

Trait Implementations

impl<F> Clone for Triangular<F> where
    F: Clone + Float,
    Standard: Distribution<F>, 

pub fn clone(&self) -> Triangular<F>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<F> Copy for Triangular<F> where
    F: Copy + Float,
    Standard: Distribution<F>, 

impl<F> Debug for Triangular<F> where
    F: Debug + Float,
    Standard: Distribution<F>, 

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

Formats the value using the given formatter.

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

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

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

pub 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.