Struct mix_distribution::Mix

pub struct Mix<T, U, X>where
    T: Distribution<U>,
    X: SampleUniform + PartialOrd,{ /* private fields */ }

Mixture distributions.

Examples

extern crate rand;
extern crate mix_distribution;

use rand::distributions::{Distribution, Normal};
use mix_distribution::Mix;

let mut rng = rand::thread_rng();

// Mixture of two distributions
let mix = {
    let dists = vec![Normal::new(0.0, 1.0), Normal::new(1.0, 2.0)];
    let weights = &[2, 1];
    Mix::new(dists, weights).unwrap()
};

mix.sample(&mut rng);

// Mixture of three distributions
let mix = {
    let dists = vec![Normal::new(0.0, 1.0), Normal::new(1.0, 2.0), Normal::new(-1.0, 1.0)];
    let weights = &[2, 1, 3];
    Mix::new(dists, weights).unwrap()
};

mix.sample(&mut rng);

Implementations

impl<T, U, X> Mix<T, U, X>where
    T: Distribution<U>,
    X: SampleUniform + PartialOrd,

pub fn new<I, J>(dists: I, weights: J) -> Result<Self, WeightedError>where
    I: IntoIterator<Item = T>,
    J: IntoIterator,
    J::Item: SampleBorrow<X>,
    X: for<'a> AddAssign<&'a X> + Clone + Default,

Creates a new Mix. dists and weights must have the same length.

Propagates errors from WeightedIndex::new().

Trait Implementations

impl<T, U, X> Clone for Mix<T, U, X>where
    T: Distribution<U> + Clone,
    X: SampleUniform + PartialOrd + Clone,
    X::Sampler: Clone,

fn clone(&self) -> Self

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<T, U, X> Debug for Mix<T, U, X>where
    T: Distribution<U> + Debug,
    X: SampleUniform + PartialOrd + Debug,
    X::Sampler: Debug,

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

Formats the value using the given formatter.

impl<T, U, X> Distribution<U> for Mix<T, U, X>where
    T: Distribution<U>,
    X: SampleUniform + PartialOrd,

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

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

fn sample_iter<R, 'a>(&'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.