Struct rand_distr::Bernoulli

pub struct Bernoulli { /* private fields */ }

The Bernoulli distribution Bernoulli(p).

This distribution describes a single boolean random variable, which is true with probability p and false with probability 1 - p. It is a special case of the Binomial distribution with n = 1.

Plot

The following plot shows the Bernoulli distribution with p = 0.1, p = 0.5, and p = 0.9.

Example

use rand::distr::{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<(), Error>

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for Bernoulli

fn deserialize<__D>( __deserializer: __D, ) -> Result<Bernoulli, <__D as Deserializer<'de>>::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Distribution<bool> for Bernoulli

fn sample<R>(&self, rng: &mut R) -> bool

where R: Rng + ?Sized,

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 Serialize for Bernoulli

fn serialize<__S>( &self, __serializer: __S, ) -> Result<<__S as Serializer>::Ok, <__S as Serializer>::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl Copy for Bernoulli

impl StructuralPartialEq for Bernoulli