Trait rand_distr::Distribution
source · 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) -> DistIter<Self, R, T> ⓘ
where R: Rng,
Self: Sized { ... }
fn map<F, S>(self, func: F) -> DistMap<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 Rng
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§
Provided Methods§
sourcefn sample_iter<R>(self, rng: R) -> DistIter<Self, R, T> ⓘ
fn sample_iter<R>(self, rng: R) -> DistIter<Self, R, T> ⓘ
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::thread_rng;
use rand::distributions::{Distribution, Alphanumeric, Uniform, Standard};
let mut rng = thread_rng();
// Vec of 16 x f32:
let v: Vec<f32> = Standard.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!");
}
sourcefn map<F, S>(self, func: F) -> DistMap<Self, F, T, S>
fn map<F, S>(self, func: F) -> DistMap<Self, F, T, S>
Create a distribution of values of ‘S’ by mapping the output of Self
through the closure F
§Example
use rand::thread_rng;
use rand::distributions::{Distribution, Uniform};
let mut rng = thread_rng();
let die = Uniform::new_inclusive(1, 6).unwrap();
let even_number = die.map(|num| num % 2 == 0);
while !even_number.sample(&mut rng) {
println!("Still odd; rolling again!");
}
Object Safety§
Implementations on Foreign Types§
source§impl<'a, T, D> Distribution<T> for &'a Dwhere
D: Distribution<T> + ?Sized,
impl<'a, T, D> Distribution<T> for &'a Dwhere
D: Distribution<T> + ?Sized,
Implementors§
impl Distribution<bool> for Bernoulli
impl Distribution<bool> for Standard
impl Distribution<char> for Standard
impl Distribution<f32> for Exp1
impl Distribution<f32> for Open01
impl Distribution<f32> for OpenClosed01
impl Distribution<f32> for Standard
impl Distribution<f32> for StandardNormal
impl Distribution<f64> for Exp1
impl Distribution<f64> for Open01
impl Distribution<f64> for OpenClosed01
impl Distribution<f64> for Standard
impl Distribution<f64> for StandardNormal
impl Distribution<i8> for Standard
impl Distribution<i16> for Standard
impl Distribution<i32> for Standard
impl Distribution<i64> for Standard
impl Distribution<i128> for Standard
impl Distribution<isize> for Standard
impl Distribution<u8> for Alphanumeric
impl Distribution<u8> for Standard
impl Distribution<u16> for Standard
impl Distribution<u32> for Standard
impl Distribution<u64> for Binomial
impl Distribution<u64> for Geometric
impl Distribution<u64> for Hypergeometric
impl Distribution<u64> for Standard
impl Distribution<u64> for StandardGeometric
impl Distribution<u128> for Standard
impl Distribution<()> for Standard
impl Distribution<usize> for Standard
impl Distribution<__m128i> for Standard
impl Distribution<__m256i> for Standard
impl Distribution<NonZero<i8>> for Standard
impl Distribution<NonZero<i16>> for Standard
impl Distribution<NonZero<i32>> for Standard
impl Distribution<NonZero<i64>> for Standard
impl Distribution<NonZero<i128>> for Standard
impl Distribution<NonZero<isize>> for Standard
impl Distribution<NonZero<u8>> for Standard
impl Distribution<NonZero<u16>> for Standard
impl Distribution<NonZero<u32>> for Standard
impl Distribution<NonZero<u64>> for Standard
impl Distribution<NonZero<u128>> for Standard
impl Distribution<NonZero<usize>> for Standard
impl<'a, T> Distribution<&'a T> for Slice<'a, T>
impl<A> Distribution<(A,)> for Standardwhere
Standard: Distribution<A>,
impl<A, B> Distribution<(A, B)> for Standard
impl<A, B, C> Distribution<(A, B, C)> for Standard
impl<A, B, C, D> Distribution<(A, B, C, D)> for Standard
impl<A, B, C, D, E> Distribution<(A, B, C, D, E)> for Standardwhere
Standard: Distribution<A> + Distribution<B> + Distribution<C> + Distribution<D> + Distribution<E>,
impl<A, B, C, D, E, F> Distribution<(A, B, C, D, E, F)> for Standardwhere
Standard: Distribution<A> + Distribution<B> + Distribution<C> + Distribution<D> + Distribution<E> + Distribution<F>,
impl<A, B, C, D, E, F, G> Distribution<(A, B, C, D, E, F, G)> for Standardwhere
Standard: Distribution<A> + Distribution<B> + Distribution<C> + Distribution<D> + Distribution<E> + Distribution<F> + Distribution<G>,
impl<A, B, C, D, E, F, G, H> Distribution<(A, B, C, D, E, F, G, H)> for Standardwhere
Standard: Distribution<A> + Distribution<B> + Distribution<C> + Distribution<D> + Distribution<E> + Distribution<F> + Distribution<G> + Distribution<H>,
impl<A, B, C, D, E, F, G, H, I> Distribution<(A, B, C, D, E, F, G, H, I)> for Standardwhere
Standard: Distribution<A> + Distribution<B> + Distribution<C> + Distribution<D> + Distribution<E> + Distribution<F> + Distribution<G> + Distribution<H> + Distribution<I>,
impl<A, B, C, D, E, F, G, H, I, J> Distribution<(A, B, C, D, E, F, G, H, I, J)> for Standardwhere
Standard: Distribution<A> + Distribution<B> + Distribution<C> + Distribution<D> + Distribution<E> + Distribution<F> + Distribution<G> + Distribution<H> + Distribution<I> + Distribution<J>,
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 Standardwhere
Standard: Distribution<A> + Distribution<B> + Distribution<C> + Distribution<D> + Distribution<E> + Distribution<F> + Distribution<G> + Distribution<H> + Distribution<I> + Distribution<J> + Distribution<K>,
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 Standardwhere
Standard: Distribution<A> + Distribution<B> + Distribution<C> + Distribution<D> + Distribution<E> + Distribution<F> + Distribution<G> + Distribution<H> + Distribution<I> + Distribution<J> + Distribution<K> + Distribution<L>,
impl<D, F, T, S> Distribution<S> for DistMap<D, F, T, S>where
D: Distribution<T>,
F: Fn(T) -> S,
impl<F> Distribution<F> for Beta<F>
impl<F> Distribution<F> for Cauchy<F>
impl<F> Distribution<F> for ChiSquared<F>
impl<F> Distribution<F> for Exp<F>
impl<F> Distribution<F> for FisherF<F>
impl<F> Distribution<F> for Frechet<F>
impl<F> Distribution<F> for Gamma<F>
impl<F> Distribution<F> for Gumbel<F>
impl<F> Distribution<F> for InverseGaussian<F>
impl<F> Distribution<F> for LogNormal<F>
impl<F> Distribution<F> for Normal<F>
impl<F> Distribution<F> for NormalInverseGaussian<F>
impl<F> Distribution<F> for Pareto<F>
impl<F> Distribution<F> for Pert<F>
impl<F> Distribution<F> for Poisson<F>
impl<F> Distribution<F> for SkewNormal<F>
impl<F> Distribution<F> for StudentT<F>
impl<F> Distribution<F> for Triangular<F>
impl<F> Distribution<F> for Weibull<F>
impl<F> Distribution<F> for Zeta<F>
impl<F> Distribution<F> for Zipf<F>
impl<F, const N: usize> Distribution<[F; N]> for Dirichlet<F, N>
impl<F: Float + SampleUniform> Distribution<[F; 2]> for UnitCircle
impl<F: Float + SampleUniform> Distribution<[F; 2]> for UnitDisc
impl<F: Float + SampleUniform> Distribution<[F; 3]> for UnitBall
impl<F: Float + SampleUniform> Distribution<[F; 3]> for UnitSphere
impl<T> Distribution<Option<T>> for Standardwhere
Standard: Distribution<T>,
impl<T> Distribution<Wrapping<T>> for Standardwhere
Standard: Distribution<T>,
impl<T, const N: usize> Distribution<[T; N]> for Standardwhere
Standard: Distribution<T>,
impl<W: Clone + PartialEq + PartialOrd + SampleUniform + SubAssign<W> + Weight> Distribution<usize> for WeightedTreeIndex<W>
alloc
only.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
.
impl<W: AliasableWeight> Distribution<usize> for WeightedAliasIndex<W>
alloc
only.