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Distribution

nyx_space::mc

Trait Distribution 

pub trait Distribution<T> {
    // Required method
    fn sample<R>(&self, rng: &mut R) -> T
       where R: Rng + ?Sized;

    // Provided methods
    fn sample_iter<R>(self, rng: R) -> Iter<Self, R, T> ⓘ
       where R: Rng,
             Self: Sized { ... }
    fn map<F, S>(self, func: F) -> Map<Self, F, T, S>
       where F: Fn(T) -> S,
             Self: Sized { ... }
}
Expand description

Types (distributions) that can be used to create a random instance of T.

It is possible to sample from a distribution through both the Distribution and [RngExt] traits, via distr.sample(&mut rng) and rng.sample(distr). They also both offer the sample_iter method, which produces an iterator that samples from the distribution.

All implementations are expected to be immutable; this has the significant advantage of not needing to consider thread safety, and for most distributions efficient state-less sampling algorithms are available.

Implementations are typically expected to be portable with reproducible results when used with a PRNG with fixed seed; see the portability chapter of The Rust Rand Book. In some cases this does not apply, e.g. the usize type requires different sampling on 32-bit and 64-bit machines.

Required Methods§

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

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

Provided Methods§

fn sample_iter<R>(self, rng: R) -> Iter<Self, R, T> ⓘ
where R: Rng, Self: Sized,

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

Note that this function takes self by value. This works since Distribution<T> is impl’d for &D where D: Distribution<T>, however borrowing is not automatic hence distr.sample_iter(...) may need to be replaced with (&distr).sample_iter(...) to borrow or (&*distr).sample_iter(...) to reborrow an existing reference.

§Example
use rand::distr::{Distribution, Alphanumeric, Uniform, StandardUniform};

let mut rng = rand::rng();

// Vec of 16 x f32:
let v: Vec<f32> = StandardUniform.sample_iter(&mut rng).take(16).collect();

// String:
let s: String = Alphanumeric
    .sample_iter(&mut rng)
    .take(7)
    .map(char::from)
    .collect();

// Dice-rolling:
let die_range = Uniform::new_inclusive(1, 6).unwrap();
let mut roll_die = die_range.sample_iter(&mut rng);
while roll_die.next().unwrap() != 6 {
    println!("Not a 6; rolling again!");
}

fn map<F, S>(self, func: F) -> Map<Self, F, T, S>
where F: Fn(T) -> S, Self: Sized,

Map sampled values to type S

§Example
use rand::distr::{Distribution, Uniform};

let die = Uniform::new_inclusive(1, 6).unwrap();
let even_number = die.map(|num| num % 2 == 0);
while !even_number.sample(&mut rand::rng()) {
    println!("Still odd; rolling again!");
}

Dyn Compatibility§

This trait is not dyn compatible.

In older versions of Rust, dyn compatibility was called "object safety".

Implementations on Foreign Types§

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impl Distribution<bool> for Bernoulli

Available on crate feature rand only.
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fn sample<R>(&self, rng: &mut R) -> bool
where R: Rng + ?Sized,

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impl Distribution<f32> for Exp1

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fn sample<R>(&self, rng: &mut R) -> f32
where R: Rng + ?Sized,

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impl Distribution<f32> for StandardNormal

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fn sample<R>(&self, rng: &mut R) -> f32
where R: Rng + ?Sized,

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impl Distribution<f64> for Bernoulli

Available on crate feature rand only.
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fn sample<R>(&self, rng: &mut R) -> f64
where R: Rng + ?Sized,

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impl Distribution<f64> for Beta

Available on crate feature rand only.
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fn sample<R>(&self, rng: &mut R) -> f64
where R: Rng + ?Sized,

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impl Distribution<f64> for Binomial

Available on crate feature rand only.
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fn sample<R>(&self, rng: &mut R) -> f64
where R: Rng + ?Sized,

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impl Distribution<f64> for Categorical

Available on crate feature rand only.
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fn sample<R>(&self, rng: &mut R) -> f64
where R: Rng + ?Sized,

§

impl Distribution<f64> for Cauchy

Available on crate feature rand only.
§

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

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impl Distribution<f64> for Chi

Available on crate feature rand only.
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fn sample<R>(&self, rng: &mut R) -> f64
where R: Rng + ?Sized,

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impl Distribution<f64> for ChiSquared

Available on crate feature rand only.
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fn sample<R>(&self, r: &mut R) -> f64
where R: Rng + ?Sized,

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impl Distribution<f64> for Dirac

Available on crate feature rand only.
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fn sample<R>(&self, _: &mut R) -> f64
where R: Rng + ?Sized,

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impl Distribution<f64> for DiscreteUniform

Available on crate feature rand only.
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fn sample<R>(&self, rng: &mut R) -> f64
where R: Rng + ?Sized,

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impl Distribution<f64> for Empirical

Available on crate feature rand only.
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fn sample<R>(&self, rng: &mut R) -> f64
where R: Rng + ?Sized,

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impl Distribution<f64> for Erlang

Available on crate feature rand only.
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fn sample<R>(&self, rng: &mut R) -> f64
where R: Rng + ?Sized,

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impl Distribution<f64> for Exp

Available on crate feature rand only.
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fn sample<R>(&self, r: &mut R) -> f64
where R: Rng + ?Sized,

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impl Distribution<f64> for Exp1

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

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impl Distribution<f64> for FisherSnedecor

Available on crate feature rand only.
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fn sample<R>(&self, rng: &mut R) -> f64
where R: Rng + ?Sized,

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impl Distribution<f64> for Gamma

Available on crate feature rand only.
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fn sample<R>(&self, rng: &mut R) -> f64
where R: Rng + ?Sized,

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impl Distribution<f64> for Geometric

Available on crate feature rand only.
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fn sample<R>(&self, r: &mut R) -> f64
where R: Rng + ?Sized,

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impl Distribution<f64> for Gumbel

Available on crate feature rand only.
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fn sample<R>(&self, r: &mut R) -> f64
where R: Rng + ?Sized,

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impl Distribution<f64> for Hypergeometric

Available on crate feature rand only.
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fn sample<R>(&self, rng: &mut R) -> f64
where R: Rng + ?Sized,

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impl Distribution<f64> for InverseGamma

Available on crate feature rand only.
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fn sample<R>(&self, r: &mut R) -> f64
where R: Rng + ?Sized,

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impl Distribution<f64> for Laplace

Available on crate feature rand only.
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fn sample<R>(&self, rng: &mut R) -> f64
where R: Rng + ?Sized,

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impl Distribution<f64> for Levy

Available on crate feature rand only.
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fn sample<R>(&self, rng: &mut R) -> f64
where R: Rng + ?Sized,

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impl Distribution<f64> for LogNormal

Available on crate feature rand only.
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fn sample<R>(&self, rng: &mut R) -> f64
where R: Rng + ?Sized,

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impl Distribution<f64> for Normal

Available on crate feature rand only.
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fn sample<R>(&self, rng: &mut R) -> f64
where R: Rng + ?Sized,

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impl Distribution<f64> for Pareto

Available on crate feature rand only.
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fn sample<R>(&self, rng: &mut R) -> f64
where R: Rng + ?Sized,

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impl Distribution<f64> for Poisson

Available on crate feature rand only.
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fn sample<R>(&self, rng: &mut R) -> f64
where R: Rng + ?Sized,

Generates one sample from the Poisson distribution either by Knuth’s method if lambda < 30.0 or Rejection method PA by A. C. Atkinson from the Journal of the Royal Statistical Society Series C (Applied Statistics) Vol. 28 No. 1. (1979) pp. 29 - 35 otherwise

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impl Distribution<f64> for StandardNormal

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

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impl Distribution<f64> for StudentsT

Available on crate feature rand only.
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fn sample<R>(&self, r: &mut R) -> f64
where R: Rng + ?Sized,

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impl Distribution<f64> for Triangular

Available on crate feature rand only.
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fn sample<R>(&self, rng: &mut R) -> f64
where R: Rng + ?Sized,

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impl Distribution<f64> for Uniform

Available on crate feature rand only.
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fn sample<R>(&self, rng: &mut R) -> f64
where R: Rng + ?Sized,

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impl Distribution<f64> for Weibull

Available on crate feature rand only.
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fn sample<R>(&self, rng: &mut R) -> f64
where R: Rng + ?Sized,

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impl Distribution<i64> for DiscreteUniform

Available on crate feature rand only.
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fn sample<R>(&self, rng: &mut R) -> i64
where R: Rng + ?Sized,

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impl Distribution<u64> for Binomial

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fn sample<R>(&self, rng: &mut R) -> u64
where R: Rng + ?Sized,

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impl Distribution<u64> for Binomial

Available on crate feature rand only.
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fn sample<R>(&self, rng: &mut R) -> u64
where R: Rng + ?Sized,

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impl Distribution<u64> for Categorical

Available on crate feature rand only.
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fn sample<R>(&self, rng: &mut R) -> u64
where R: Rng + ?Sized,

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impl Distribution<u64> for Geometric

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fn sample<R>(&self, rng: &mut R) -> u64
where R: Rng + ?Sized,

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impl Distribution<u64> for Geometric

Available on crate feature rand only.
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fn sample<R>(&self, r: &mut R) -> u64
where R: Rng + ?Sized,

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impl Distribution<u64> for Hypergeometric

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fn sample<R>(&self, rng: &mut R) -> u64
where R: Rng + ?Sized,

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impl Distribution<u64> for Hypergeometric

Available on crate feature rand only.
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fn sample<R>(&self, rng: &mut R) -> u64
where R: Rng + ?Sized,

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impl Distribution<u64> for NegativeBinomial

Available on crate feature rand only.
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fn sample<R>(&self, r: &mut R) -> u64
where R: Rng + ?Sized,

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impl Distribution<u64> for Poisson

Available on crate feature rand only.
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fn sample<R>(&self, rng: &mut R) -> u64
where R: Rng + ?Sized,

Generates one sample from the Poisson distribution either by Knuth’s method if lambda < 30.0 or Rejection method PA by A. C. Atkinson from the Journal of the Royal Statistical Society Series C (Applied Statistics) Vol. 28 No. 1. (1979) pp. 29 - 35 otherwise

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impl Distribution<u64> for StandardGeometric

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fn sample<R>(&self, rng: &mut R) -> u64
where R: Rng + ?Sized,

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impl Distribution<usize> for Categorical

Available on crate feature rand only.
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fn sample<R>(&self, rng: &mut R) -> usize
where R: Rng + ?Sized,

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impl<D> Distribution<Matrix<f64, D, Const<1>, <DefaultAllocator as Allocator<D>>::Buffer<f64>>> for Dirichlet<D>
where D: Dim, DefaultAllocator: Allocator<D>,

Available on crate feature rand only.
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fn sample<R>( &self, rng: &mut R, ) -> Matrix<f64, D, Const<1>, <DefaultAllocator as Allocator<D>>::Buffer<f64>>
where R: Rng + ?Sized,

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impl<D> Distribution<Matrix<f64, D, Const<1>, <DefaultAllocator as Allocator<D>>::Buffer<f64>>> for Multinomial<D>
where D: Dim, DefaultAllocator: Allocator<D>,

Available on crate feature rand only.
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fn sample<R>( &self, rng: &mut R, ) -> Matrix<f64, D, Const<1>, <DefaultAllocator as Allocator<D>>::Buffer<f64>>
where R: Rng + ?Sized,

§Numerical stability

Each category’s count is drawn from a Binomial conditioned on the categories already sampled, using a probability renormalized against the probability mass not yet assigned (p_i / remaining_mass). As sampling proceeds and fewer categories remain unprocessed, remaining_mass shrinks towards zero, which can amplify floating-point error in that renormalized ratio. The ratio is clamped to [0.0, 1.0] so this can never panic, but for distributions with many categories, or a long tail of very small probabilities, this may introduce a small bias in the last-processed categories’ counts.

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impl<D> Distribution<Matrix<f64, D, Const<1>, <DefaultAllocator as Allocator<D>>::Buffer<f64>>> for MultivariateNormal<D>
where D: Dim, DefaultAllocator: Allocator<D> + Allocator<D, D>,

Available on crate feature rand only.
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fn sample<R>( &self, rng: &mut R, ) -> Matrix<f64, D, Const<1>, <DefaultAllocator as Allocator<D>>::Buffer<f64>>
where R: Rng + ?Sized,

Samples from the multivariate normal distribution

§Formula
L * Z + μ

where L is the Cholesky decomposition of the covariance matrix, Z is a vector of normally distributed random variables, and μ is the mean vector

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impl<D> Distribution<Matrix<f64, D, Const<1>, <DefaultAllocator as Allocator<D>>::Buffer<f64>>> for MultivariateStudent<D>
where D: Dim, DefaultAllocator: Allocator<D> + Allocator<D, D>,

Available on crate feature rand only.
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fn sample<R>( &self, rng: &mut R, ) -> Matrix<f64, D, Const<1>, <DefaultAllocator as Allocator<D>>::Buffer<f64>>
where R: Rng + ?Sized,

Samples from the multivariate student distribution

§Formula
W ⋅ L ⋅ Z + μ

where W has √(ν/Sν) distribution, Sν has Chi-squared distribution with ν degrees of freedom, L is the Cholesky decomposition of the scale matrix, Z is a vector of normally distributed random variables, and μ is the location vector

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impl<D> Distribution<Matrix<u64, D, Const<1>, <DefaultAllocator as Allocator<D>>::Buffer<u64>>> for Multinomial<D>
where D: Dim, DefaultAllocator: Allocator<D>,

Available on crate feature rand only.
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fn sample<R>( &self, rng: &mut R, ) -> Matrix<u64, D, Const<1>, <DefaultAllocator as Allocator<D>>::Buffer<u64>>
where R: Rng + ?Sized,

§Numerical stability

Each category’s count is drawn from a Binomial conditioned on the categories already sampled, using a probability renormalized against the probability mass not yet assigned (p_i / remaining_mass). As sampling proceeds and fewer categories remain unprocessed, remaining_mass shrinks towards zero, which can amplify floating-point error in that renormalized ratio. The ratio is clamped to [0.0, 1.0] so this can never panic, but for distributions with many categories, or a long tail of very small probabilities, this may introduce a small bias in the last-processed categories’ counts.

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impl<D> Distribution<f64> for Data<D>
where D: AsRef<[f64]>,

Available on crate feature rand only.
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fn sample<R>(&self, rng: &mut R) -> f64
where R: Rng + ?Sized,

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impl<F> Distribution<F> for Beta<F>
where F: Float, Open01: Distribution<F>,

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

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impl<F> Distribution<F> for Cauchy<F>
where F: Float + FloatConst, StandardUniform: Distribution<F>,

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

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

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

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

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

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

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

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impl<F> Distribution<F> for Frechet<F>
where F: Float, OpenClosed01: Distribution<F>,

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

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

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

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impl<F> Distribution<F> for Gumbel<F>
where F: Float, OpenClosed01: Distribution<F>,

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

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impl<F> Distribution<F> for InverseGaussian<F>
where F: Float, StandardNormal: Distribution<F>, StandardUniform: Distribution<F>,

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

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impl<F> Distribution<F> for LogNormal<F>
where F: Float, StandardNormal: Distribution<F>,

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

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impl<F> Distribution<F> for NormalInverseGaussian<F>
where F: Float, StandardNormal: Distribution<F>, StandardUniform: Distribution<F>,

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

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impl<F> Distribution<F> for Pareto<F>
where F: Float, OpenClosed01: Distribution<F>,

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

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

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

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impl<F> Distribution<F> for Poisson<F>
where F: Float + FloatConst, StandardUniform: Distribution<F>, StandardNormal: Distribution<F>, Exp1: Distribution<F>,

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

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impl<F> Distribution<F> for SkewNormal<F>
where F: Float, StandardNormal: Distribution<F>,

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

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

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

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

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

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impl<F> Distribution<F> for Weibull<F>
where F: Float, OpenClosed01: Distribution<F>,

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

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impl<F> Distribution<F> for Zeta<F>
where F: Float, StandardUniform: Distribution<F>, OpenClosed01: Distribution<F>,

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

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impl<F> Distribution<F> for Zipf<F>
where F: Float, StandardUniform: Distribution<F>,

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

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impl<F> Distribution<Vec<F>> for Dirichlet<F>
where F: Float + Default, StandardNormal: Distribution<F>, Exp1: Distribution<F>, Open01: Distribution<F>,

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

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impl<F> Distribution<[F; 2]> for UnitCircle
where F: Float + SampleUniform,

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fn sample<R>(&self, rng: &mut R) -> [F; 2]
where R: Rng + ?Sized,

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impl<F> Distribution<[F; 2]> for UnitDisc
where F: Float + SampleUniform,

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fn sample<R>(&self, rng: &mut R) -> [F; 2]
where R: Rng + ?Sized,

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impl<F> Distribution<[F; 3]> for UnitBall
where F: Float + SampleUniform,

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fn sample<R>(&self, rng: &mut R) -> [F; 3]
where R: Rng + ?Sized,

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impl<F> Distribution<[F; 3]> for UnitSphere
where F: Float + SampleUniform,

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fn sample<R>(&self, rng: &mut R) -> [F; 3]
where R: Rng + ?Sized,

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impl<T, D> Distribution<T> for &D
where D: Distribution<T> + ?Sized,

§

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

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impl<W> Distribution<usize> for WeightedAliasIndex<W>
where W: AliasableWeight,

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

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impl<W> Distribution<usize> for WeightedTreeIndex<W>
where W: Clone + PartialEq + PartialOrd + SampleUniform + SubAssign + Weight,

Samples a randomly selected index from the weighted distribution.

Caution: This method panics if there are no elements or all weights are zero. However, it is guaranteed that this method will not panic if a call to [WeightedTreeIndex::is_valid] returns true.

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

Implementors§

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impl Distribution<()> for StandardUniform

Source§

impl Distribution<DispersedState<Spacecraft>> for MvnSpacecraft

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impl Distribution<NonZero<i8>> for StandardUniform

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impl Distribution<NonZero<i16>> for StandardUniform

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impl Distribution<NonZero<i32>> for StandardUniform

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impl Distribution<NonZero<i64>> for StandardUniform

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impl Distribution<NonZero<i128>> for StandardUniform

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impl Distribution<NonZero<u8>> for StandardUniform

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impl Distribution<NonZero<u16>> for StandardUniform

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impl Distribution<NonZero<u32>> for StandardUniform

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impl Distribution<NonZero<u64>> for StandardUniform

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impl Distribution<NonZero<u128>> for StandardUniform

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impl Distribution<__m128i> for StandardUniform

Available on x86 or x86-64 only.
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impl Distribution<__m256i> for StandardUniform

Available on x86 or x86-64 only.
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impl Distribution<bool> for Bernoulli

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impl Distribution<bool> for StandardUniform

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impl Distribution<char> for StandardUniform

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impl Distribution<f32> for Open01

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impl Distribution<f32> for OpenClosed01

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impl Distribution<f32> for StandardUniform

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impl Distribution<f64> for Open01

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impl Distribution<f64> for OpenClosed01

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impl Distribution<f64> for StandardUniform

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impl Distribution<i8> for StandardUniform

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impl Distribution<i16> for StandardUniform

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impl Distribution<i32> for StandardUniform

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impl Distribution<i64> for StandardUniform

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impl Distribution<i128> for StandardUniform

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impl Distribution<u8> for Alphabetic

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impl Distribution<u8> for Alphanumeric

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impl Distribution<u8> for StandardUniform

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impl Distribution<u16> for StandardUniform

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impl Distribution<u32> for StandardUniform

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impl Distribution<u64> for StandardUniform

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impl Distribution<u128> for StandardUniform

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impl<'a, T> Distribution<&'a T> for Choose<'a, T>

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impl<A, B, C, D, E, F, G, H, I, J, K, L> Distribution<(A, B, C, D, E, F, G, H, I, J, K, L)> for StandardUniform
where StandardUniform: Distribution<A> + Distribution<B> + Distribution<C> + Distribution<D> + Distribution<E> + Distribution<F> + Distribution<G> + Distribution<H> + Distribution<I> + Distribution<J> + Distribution<K> + Distribution<L>,

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impl<A, B, C, D, E, F, G, H, I, J, K> Distribution<(A, B, C, D, E, F, G, H, I, J, K)> for StandardUniform
where StandardUniform: Distribution<A> + Distribution<B> + Distribution<C> + Distribution<D> + Distribution<E> + Distribution<F> + Distribution<G> + Distribution<H> + Distribution<I> + Distribution<J> + Distribution<K>,

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impl<A, B, C, D, E, F, G, H, I, J> Distribution<(A, B, C, D, E, F, G, H, I, J)> for StandardUniform
where StandardUniform: Distribution<A> + Distribution<B> + Distribution<C> + Distribution<D> + Distribution<E> + Distribution<F> + Distribution<G> + Distribution<H> + Distribution<I> + Distribution<J>,

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impl<A, B, C, D, E, F, G, H, I> Distribution<(A, B, C, D, E, F, G, H, I)> for StandardUniform
where StandardUniform: Distribution<A> + Distribution<B> + Distribution<C> + Distribution<D> + Distribution<E> + Distribution<F> + Distribution<G> + Distribution<H> + Distribution<I>,

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impl<A, B, C, D, E, F, G, H> Distribution<(A, B, C, D, E, F, G, H)> for StandardUniform
where StandardUniform: Distribution<A> + Distribution<B> + Distribution<C> + Distribution<D> + Distribution<E> + Distribution<F> + Distribution<G> + Distribution<H>,

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impl<A, B, C, D, E, F, G> Distribution<(A, B, C, D, E, F, G)> for StandardUniform
where StandardUniform: Distribution<A> + Distribution<B> + Distribution<C> + Distribution<D> + Distribution<E> + Distribution<F> + Distribution<G>,

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impl<A, B, C, D, E, F> Distribution<(A, B, C, D, E, F)> for StandardUniform
where StandardUniform: Distribution<A> + Distribution<B> + Distribution<C> + Distribution<D> + Distribution<E> + Distribution<F>,

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impl<A, B, C, D, E> Distribution<(A, B, C, D, E)> for StandardUniform
where StandardUniform: Distribution<A> + Distribution<B> + Distribution<C> + Distribution<D> + Distribution<E>,

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impl<A, B, C, D> Distribution<(A, B, C, D)> for StandardUniform
where StandardUniform: Distribution<A> + Distribution<B> + Distribution<C> + Distribution<D>,

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impl<A, B, C> Distribution<(A, B, C)> for StandardUniform
where StandardUniform: Distribution<A> + Distribution<B> + Distribution<C>,

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impl<A, B> Distribution<(A, B)> for StandardUniform
where StandardUniform: Distribution<A> + Distribution<B>,

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impl<A> Distribution<(A,)> for StandardUniform
where StandardUniform: Distribution<A>,

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impl<D, F, T, S> Distribution<S> for Map<D, F, T, S>
where D: Distribution<T>, F: Fn(T) -> S,

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impl<F> Distribution<F> for nyx_space::mc::Normal<F>
where F: Float, StandardNormal: Distribution<F>,

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impl<T, D> Distribution<OPoint<T, D>> for StandardUniform
where T: Scalar, D: DimName, StandardUniform: Distribution<T>, DefaultAllocator: Allocator<D>,

Available on crate feature rand-no-std only.
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impl<T, R, C> Distribution<Matrix<T, R, C, <DefaultAllocator as Allocator<R, C>>::Buffer<T>>> for StandardUniform
where T: Scalar, R: Dim, C: Dim, DefaultAllocator: Allocator<R, C>, StandardUniform: Distribution<T>,

Available on crate feature rand-no-std only.
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impl<T, R, const D: usize> Distribution<Isometry<T, R, D>> for StandardUniform
where T: RealField, R: AbstractRotation<T, D>, StandardUniform: Distribution<T> + Distribution<R>,

Available on crate feature rand-no-std only.
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impl<T, R, const D: usize> Distribution<Similarity<T, R, D>> for StandardUniform
where T: RealField, R: AbstractRotation<T, D>, StandardUniform: Distribution<T> + Distribution<R>,

Available on crate feature rand-no-std only.
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impl<T, const D: usize> Distribution<Scale<T, D>> for StandardUniform
where T: Scalar, StandardUniform: Distribution<T>,

Available on crate feature rand-no-std only.
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impl<T, const D: usize> Distribution<Translation<T, D>> for StandardUniform
where T: Scalar, StandardUniform: Distribution<T>,

Available on crate feature rand-no-std only.
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impl<T, const N: usize> Distribution<[T; N]> for StandardUniform
where StandardUniform: Distribution<T>,

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impl<T> Distribution<Orthographic3<T>> for StandardUniform
where T: RealField, StandardUniform: Distribution<T>,

Available on crate feature rand-no-std only.
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impl<T> Distribution<Perspective3<T>> for StandardUniform
where T: RealField, StandardUniform: Distribution<T>,

Available on crate feature rand-no-std only.
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impl<T> Distribution<Quaternion<T>> for StandardUniform
where T: SimdRealField, StandardUniform: Distribution<T>,

Available on crate feature rand-no-std only.
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impl<T> Distribution<Rotation<T, 2>> for StandardUniform
where T: SimdRealField + SampleUniform, <T as SimdValue>::Element: SimdRealField,

Available on crate feature rand-no-std only.
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impl<T> Distribution<Rotation<T, 3>> for StandardUniform
where T: SimdRealField + SampleUniform, <T as SimdValue>::Element: SimdRealField, OpenClosed01: Distribution<T>,

Available on crate feature rand-no-std only.
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impl<T> Distribution<Unit<Quaternion<T>>> for StandardUniform
where T: SimdRealField + SampleUniform, <T as SimdValue>::Element: SimdRealField, OpenClosed01: Distribution<T>,

Available on crate feature rand-no-std only.
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impl<T> Distribution<Wrapping<T>> for StandardUniform
where StandardUniform: Distribution<T>,

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impl<X> Distribution<X> for nyx_space::mc::Uniform<X>
where X: SampleUniform,

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impl<X> Distribution<usize> for WeightedIndex<X>
where X: SampleUniform + PartialOrd,