Struct std::rand::distributions::Range [] [src]

pub struct Range<X> {
    low: X,
    range: X,
    accept_zone: X,
}
Unstable (rand)

: use rand from crates.io

Sample values uniformly between two bounds.

This gives a uniform distribution (assuming the RNG used to sample it is itself uniform & the SampleRange implementation for the given type is correct), even for edge cases like low = 0, high = 170, for which a naive modulo operation would return numbers less than 85 with double the probability to those greater than 85.

Types should attempt to sample in [low, high), i.e., not including high, but this may be very difficult. All the primitive integer types satisfy this property, and the float types normally satisfy it, but rounding may mean high can occur.

Fields

low
Unstable (rand)

: use rand from crates.io

range
Unstable (rand)

: use rand from crates.io

accept_zone
Unstable (rand)

: use rand from crates.io

Methods

impl<X> Range<X> where X: SampleRange + PartialOrd<X>

fn new(low: X, high: X) -> Range<X>

Unstable (rand)

: use rand from crates.io

Create a new Range instance that samples uniformly from [low, high). Panics if low >= high.

Trait Implementations

impl<Sup> Sample<Sup> for Range<Sup> where Sup: SampleRange

fn sample<R>(&mut self, rng: &mut R) -> Sup where R: Rng

impl<Sup> IndependentSample<Sup> for Range<Sup> where Sup: SampleRange

fn ind_sample<R>(&self, rng: &mut R) -> Sup where R: Rng