Struct rand::distributions::Uniform[][src]

pub struct Uniform<X: SampleUniform>(_);
Expand description

Sample values uniformly between two bounds.

Uniform::new and Uniform::new_inclusive construct a uniform distribution sampling from the given range; these functions may do extra work up front to make sampling of multiple values faster. If only one sample from the range is required, Rng::gen_range can be more efficient.

When sampling from a constant range, many calculations can happen at compile-time and all methods should be fast; for floating-point ranges and the full range of integer types this should have comparable performance to the Standard distribution.

Steps are taken to avoid bias which might be present in naive implementations; for example rng.gen::<u8>() % 170 samples from the range [0, 169] but is twice as likely to select numbers less than 85 than other values. Further, the implementations here give more weight to the high-bits generated by the RNG than the low bits, since with some RNGs the low-bits are of lower quality than the high bits.

Implementations must sample in [low, high) range for Uniform::new(low, high), i.e., excluding high. In particular, care must be taken to ensure that rounding never results values < low or >= high.

Example

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

let between = Uniform::from(10..10000);
let mut rng = rand::thread_rng();
let mut sum = 0;
for _ in 0..1000 {
    sum += between.sample(&mut rng);
}
println!("{}", sum);

For a single sample, Rng::gen_range may be preferred:

use rand::Rng;

let mut rng = rand::thread_rng();
println!("{}", rng.gen_range(0..10));

Implementations

Create a new Uniform instance which samples uniformly from the half open range [low, high) (excluding high). Panics if low >= high.

Create a new Uniform instance which samples uniformly from the closed range [low, high] (inclusive). Panics if low > high.

Trait Implementations

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Formats the value using the given formatter. Read more

Deserialize this value from the given Serde deserializer. Read more

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

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

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

Performs the conversion.

Performs the conversion.

Serialize this value into the given Serde serializer. Read more

Auto Trait Implementations

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The type returned in the event of a conversion error.

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