Trait rand::distributions::uniform::UniformSampler
source · pub trait UniformSampler: Sized {
type X;
// Required methods
fn new<B1, B2>(low: B1, high: B2) -> Self
where B1: SampleBorrow<Self::X> + Sized,
B2: SampleBorrow<Self::X> + Sized;
fn new_inclusive<B1, B2>(low: B1, high: B2) -> Self
where B1: SampleBorrow<Self::X> + Sized,
B2: SampleBorrow<Self::X> + Sized;
fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Self::X;
// Provided methods
fn sample_single<R: Rng + ?Sized, B1, B2>(
low: B1,
high: B2,
rng: &mut R,
) -> Self::X
where B1: SampleBorrow<Self::X> + Sized,
B2: SampleBorrow<Self::X> + Sized { ... }
fn sample_single_inclusive<R: Rng + ?Sized, B1, B2>(
low: B1,
high: B2,
rng: &mut R,
) -> Self::X
where B1: SampleBorrow<Self::X> + Sized,
B2: SampleBorrow<Self::X> + Sized { ... }
}
Expand description
Helper trait handling actual uniform sampling.
See the module documentation on how to implement Uniform
range
sampling for a custom type.
Implementation of sample_single
is optional, and is only useful when
the implementation can be faster than Self::new(low, high).sample(rng)
.
Required Associated Types§
Required Methods§
sourcefn new<B1, B2>(low: B1, high: B2) -> Self
fn new<B1, B2>(low: B1, high: B2) -> Self
Construct self, with inclusive lower bound and exclusive upper bound
[low, high)
.
Usually users should not call this directly but instead use
Uniform::new
, which asserts that low < high
before calling this.
sourcefn new_inclusive<B1, B2>(low: B1, high: B2) -> Self
fn new_inclusive<B1, B2>(low: B1, high: B2) -> Self
Construct self, with inclusive bounds [low, high]
.
Usually users should not call this directly but instead use
Uniform::new_inclusive
, which asserts that low <= high
before
calling this.
Provided Methods§
sourcefn sample_single<R: Rng + ?Sized, B1, B2>(
low: B1,
high: B2,
rng: &mut R,
) -> Self::X
fn sample_single<R: Rng + ?Sized, B1, B2>( low: B1, high: B2, rng: &mut R, ) -> Self::X
Sample a single value uniformly from a range with inclusive lower bound
and exclusive upper bound [low, high)
.
By default this is implemented using
UniformSampler::new(low, high).sample(rng)
. However, for some types
more optimal implementations for single usage may be provided via this
method (which is the case for integers and floats).
Results may not be identical.
Note that to use this method in a generic context, the type needs to be
retrieved via SampleUniform::Sampler
as follows:
use rand::{thread_rng, distributions::uniform::{SampleUniform, UniformSampler}};
fn sample_from_range<T: SampleUniform>(lb: T, ub: T) -> T {
let mut rng = thread_rng();
<T as SampleUniform>::Sampler::sample_single(lb, ub, &mut rng)
}
sourcefn sample_single_inclusive<R: Rng + ?Sized, B1, B2>(
low: B1,
high: B2,
rng: &mut R,
) -> Self::X
fn sample_single_inclusive<R: Rng + ?Sized, B1, B2>( low: B1, high: B2, rng: &mut R, ) -> Self::X
Sample a single value uniformly from a range with inclusive lower bound
and inclusive upper bound [low, high]
.
By default this is implemented using
UniformSampler::new_inclusive(low, high).sample(rng)
. However, for
some types more optimal implementations for single usage may be provided
via this method.
Results may not be identical.