Struct ndarray_rand::rand_distr::Pert

pub struct Pert<F> where
    F: Float,
    StandardNormal: Distribution<F>,
    Exp1: Distribution<F>,
    Open01: Distribution<F>,  { /* fields omitted */ }

The PERT distribution.

Similar to the Triangular distribution, the PERT distribution is parameterised by a range and a mode within that range. Unlike the Triangular distribution, the probability density function of the PERT distribution is smooth, with a configurable weighting around the mode.

Example

use rand_distr::{Pert, Distribution};

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

Implementations

impl<F> Pert<F> where
    F: Float,
    StandardNormal: Distribution<F>,
    Exp1: Distribution<F>,
    Open01: Distribution<F>, 

pub fn new(min: F, max: F, mode: F) -> Result<Pert<F>, PertError>

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

This is equivalent to calling Pert::new_shape with shape == 4.0.

pub fn new_with_shape(
    min: F,
    max: F,
    mode: F,
    shape: F
) -> Result<Pert<F>, PertError>

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

Trait Implementations

impl<F> Clone for Pert<F> where
    F: Clone + Float,
    StandardNormal: Distribution<F>,
    Exp1: Distribution<F>,
    Open01: Distribution<F>, 

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

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<F> Copy for Pert<F> where
    F: Copy + Float,
    StandardNormal: Distribution<F>,
    Exp1: Distribution<F>,
    Open01: Distribution<F>, 

impl<F> Debug for Pert<F> where
    F: Debug + Float,
    StandardNormal: Distribution<F>,
    Exp1: Distribution<F>,
    Open01: Distribution<F>, 

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

Formats the value using the given formatter.

impl<F> Distribution<F> for Pert<F> where
    F: Float,
    StandardNormal: Distribution<F>,
    Exp1: Distribution<F>,
    Open01: 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.