# [−][src]Struct rand::distributions::Bernoulli

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.

## Methods

`impl Bernoulli`

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

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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>

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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`

.

If `numerator == denominator`

then the returned `Bernoulli`

will always
return `true`

. If `numerator == 0`

it will always return `false`

.

## Trait Implementations

`impl Distribution<bool> for Bernoulli`

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

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#### ⓘImportant traits for DistIter<D, R, T>`fn sample_iter<R>(self, rng: R) -> DistIter<Self, R, T> where`

R: Rng,

Self: Sized,

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R: Rng,

Self: Sized,

`impl Clone for Bernoulli`

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`impl Copy for Bernoulli`

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`impl Debug for Bernoulli`

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## Auto Trait Implementations

`impl Unpin for Bernoulli`

`impl Sync for Bernoulli`

`impl Send for Bernoulli`

`impl UnwindSafe for Bernoulli`

`impl RefUnwindSafe for Bernoulli`

## Blanket Implementations

`impl<T> ToOwned for T where`

T: Clone,

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T: Clone,

`type Owned = T`

The resulting type after obtaining ownership.

`fn to_owned(&self) -> T`

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`fn clone_into(&self, target: &mut T)`

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`impl<T, U> Into<U> for T where`

U: From<T>,

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U: From<T>,

`impl<T> From<T> for T`

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`impl<T, U> TryFrom<U> for T where`

U: Into<T>,

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U: Into<T>,

`type Error = Infallible`

The type returned in the event of a conversion error.

`fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>`

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`impl<T, U> TryInto<U> for T where`

U: TryFrom<T>,

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U: TryFrom<T>,

`type Error = <U as TryFrom<T>>::Error`

The type returned in the event of a conversion error.

`fn try_into(self) -> Result<U, <U as TryFrom<T>>::Error>`

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`impl<T> BorrowMut<T> for T where`

T: ?Sized,

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T: ?Sized,

`fn borrow_mut(&mut self) -> &mut T`

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`impl<T> Borrow<T> for T where`

T: ?Sized,

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T: ?Sized,

`impl<T> Any for T where`

T: 'static + ?Sized,

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T: 'static + ?Sized,

`impl<T> FromCast<T> for T`

`fn from_cast(t: T) -> T`

`impl<T, U> Cast<U> for T where`

U: FromCast<T>,

U: FromCast<T>,

`fn cast(self) -> U`

`impl<T> FromBits<T> for T`

`fn from_bits(t: T) -> T`

`impl<T, U> IntoBits<U> for T where`

U: FromBits<T>,

U: FromBits<T>,

`fn into_bits(self) -> U`

`impl<V, T> VZip<V> for T where`

V: MultiLane<T>,

V: MultiLane<T>,