Struct ndarray_rand::rand_distr::Uniform

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

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 prefered:

use rand::Rng;

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

Implementations

impl<X> Uniform<X> where
    X: SampleUniform, 

pub fn new<B1, B2>(low: B1, high: B2) -> Uniform<X> where
    B1: SampleBorrow<X>,
    B2: SampleBorrow<X>, 

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

pub fn new_inclusive<B1, B2>(low: B1, high: B2) -> Uniform<X> where
    B1: SampleBorrow<X>,
    B2: SampleBorrow<X>, 

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

Trait Implementations

impl<X> Clone for Uniform<X> where
    X: Clone + SampleUniform,
    <X as SampleUniform>::Sampler: Clone, 

pub fn clone(&self) -> Uniform<X>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<X> Copy for Uniform<X> where
    X: Copy + SampleUniform,
    <X as SampleUniform>::Sampler: Copy, 

impl<X> Debug for Uniform<X> where
    X: Debug + SampleUniform,
    <X as SampleUniform>::Sampler: Debug, 

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

Formats the value using the given formatter.

impl<X> Distribution<X> for Uniform<X> where
    X: SampleUniform, 

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

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

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

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

impl<X> From<Range<X>> for Uniform<X> where
    X: SampleUniform, 

pub fn from(r: Range<X>) -> Uniform<X>

Performs the conversion.

impl<X> From<RangeInclusive<X>> for Uniform<X> where
    X: SampleUniform, 

pub fn from(r: RangeInclusive<X>) -> Uniform<X>

Performs the conversion.