Struct ndarray_rand::rand_distr::Exp

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

The exponential distribution Exp(lambda).

This distribution has density function: f(x) = lambda * exp(-lambda * x) for x > 0, when lambda > 0. For lambda = 0, all samples yield infinity.

Note that Exp1 is an optimised implementation for lambda = 1.

Example

use rand_distr::{Exp, Distribution};

let exp = Exp::new(2.0).unwrap();
let v = exp.sample(&mut rand::thread_rng());
println!("{} is from a Exp(2) distribution", v);

Implementations

impl<F> Exp<F> where
    F: Float,
    Exp1: Distribution<F>, 

pub fn new(lambda: F) -> Result<Exp<F>, Error>

Construct a new Exp with the given shape parameter lambda.

Remarks

For custom types N implementing the Float trait, the case lambda = 0 is handled as follows: each sample corresponds to a sample from an Exp1 multiplied by 1 / 0. Primitive types yield infinity, since 1 / 0 = infinity.

Trait Implementations

impl<F> Clone for Exp<F> where
    F: Clone + Float,
    Exp1: Distribution<F>, 

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

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<F> Copy for Exp<F> where
    F: Copy + Float,
    Exp1: Distribution<F>, 

impl<F> Debug for Exp<F> where
    F: Debug + Float,
    Exp1: Distribution<F>, 

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

Formats the value using the given formatter.

impl<F> Distribution<F> for Exp<F> where
    F: Float,
    Exp1: 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.