Struct rand::distributions::Dirichlet

pub struct Dirichlet { /* fields omitted */ }

The dirichelet distribution Dirichlet(alpha).

The Dirichlet distribution is a family of continuous multivariate probability distributions parameterized by a vector alpha of positive reals. It is a multivariate generalization of the beta distribution.

Example

use rand::prelude::*;
use rand::distributions::Dirichlet;

let dirichlet = Dirichlet::new(vec![1.0, 2.0, 3.0]);
let samples = dirichlet.sample(&mut rand::thread_rng());
println!("{:?} is from a Dirichlet([1.0, 2.0, 3.0]) distribution", samples);

Methods

impl Dirichlet

pub fn new<V: Into<Vec<f64>>>(alpha: V) -> Dirichlet

Construct a new Dirichlet with the given alpha parameter alpha.

Panics

• if alpha.len() < 2

pub fn new_with_param(alpha: f64, size: usize) -> Dirichlet

Construct a new Dirichlet with the given shape parameter alpha and size.

Panics

• if alpha <= 0.0
• if size < 2

Trait Implementations

impl Clone for Dirichlet

fn clone(&self) -> Dirichlet

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for Dirichlet

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

Formats the value using the given formatter.

impl Distribution<Vec<f64>> for Dirichlet

Important traits for Vec<u8>

impl Write for Vec<u8>

fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Vec<f64>

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

Important traits for DistIter<'a, D, R, T>

impl<'a, D, R, T> Iterator for DistIter<'a, D, R, T> where
    D: Distribution<T>,
    R: Rng + 'a,  type Item = T;

fn sample_iter<'a, R>(&'a self, rng: &'a mut R) -> DistIter<'a, Self, R, T> where     Self: Sized,     R: Rng,

Create an iterator that generates random values of T, using rng as the source of randomness.