Struct Bernoulli

pub struct Bernoulli { /* private fields */ }

The Bernoulli distribution.

This is a special case of the Binomial distribution where n = 1.

Example

use rand::distributions::{Bernoulli, Distribution};

let d = Bernoulli::new(0.3).unwrap();
let v = d.sample(&mut rand::thread_rng());
println!("{} is from a Bernoulli distribution", v);

Precision

This Bernoulli distribution uses 64 bits from the RNG (a u64), so only probabilities that are multiples of 2^-64 can be represented.

Implementations

impl Bernoulli

pub fn new(p: f64) -> Result<Bernoulli, BernoulliError>

Construct a new Bernoulli with the given probability of success p.

Precision

For p = 1.0, the resulting distribution will always generate true. For p = 0.0, the resulting distribution will always generate false.

This method is accurate for any input p in the range [0, 1] which is a multiple of 2^-64. (Note that not all multiples of 2^-64 in [0, 1] can be represented as a f64.)

pub fn from_ratio( numerator: u32, denominator: u32, ) -> Result<Bernoulli, BernoulliError>

Construct a new Bernoulli with the probability of success of numerator-in-denominator. I.e. new_ratio(2, 3) will return a Bernoulli with a 2-in-3 chance, or about 67%, of returning true.

return true. If numerator == 0 it will always return false. For numerator > denominator and denominator == 0, this returns an error. Otherwise, for numerator == denominator, samples are always true; for numerator == 0 samples are always false.

Trait Implementations

impl Clone for Bernoulli

fn clone(&self) -> Bernoulli

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for Bernoulli

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

Formats the value using the given formatter.

impl Distribution<bool> for Bernoulli

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

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

fn sample_iter<R>(self, rng: R) -> DistIter<Self, R, T>

where R: Rng, Self: Sized,

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

fn map<F, S>(self, func: F) -> DistMap<Self, F, T, S>

where F: Fn(T) -> S, Self: Sized,

Create a distribution of values of ‘S’ by mapping the output of Self through the closure F

impl PartialEq for Bernoulli

fn eq(&self, other: &Bernoulli) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Copy for Bernoulli

impl StructuralPartialEq for Bernoulli

Layout

Note: Most layout information is completely unstable and may even differ between compilations. The only exception is types with certain repr(...) attributes. Please see the Rust Reference's “Type Layout” chapter for details on type layout guarantees.

Size: 8 bytes