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|
use crate::Decimal;
use rand::{
distributions::{
uniform::{SampleBorrow, SampleUniform, UniformInt, UniformSampler},
Distribution, Standard,
},
Rng,
};
impl Distribution<Decimal> for Standard {
fn sample<R>(&self, rng: &mut R) -> Decimal
where
R: Rng + ?Sized,
{
Decimal::from_parts(
rng.next_u32(),
rng.next_u32(),
rng.next_u32(),
rng.gen(),
rng.next_u32(),
)
}
}
impl SampleUniform for Decimal {
type Sampler = DecimalSampler;
}
#[derive(Clone, Copy, Debug, PartialEq)]
pub struct DecimalSampler {
mantissa_sampler: UniformInt<i128>,
scale: u32,
}
impl UniformSampler for DecimalSampler {
type X = Decimal;
/// Creates a new sampler that will yield random decimal objects between `low` and `high`.
///
/// The sampler will always provide decimals at the same scale as the inputs; if the inputs
/// have different scales, the higher scale is used.
///
/// # Example
///
/// ```
/// # use rand::Rng;
/// # use rust_decimal_macros::dec;
/// let mut rng = rand::rngs::OsRng;
/// let random = rng.gen_range(dec!(1.00)..dec!(2.00));
/// assert!(random >= dec!(1.00));
/// assert!(random < dec!(2.00));
/// assert_eq!(random.scale(), 2);
/// ```
#[inline]
fn new<B1, B2>(low: B1, high: B2) -> Self
where
B1: SampleBorrow<Self::X> + Sized,
B2: SampleBorrow<Self::X> + Sized,
{
let (low, high) = sync_scales(*low.borrow(), *high.borrow());
let high = Decimal::from_i128_with_scale(high.mantissa() - 1, high.scale());
UniformSampler::new_inclusive(low, high)
}
/// Creates a new sampler that will yield random decimal objects between `low` and `high`.
///
/// The sampler will always provide decimals at the same scale as the inputs; if the inputs
/// have different scales, the higher scale is used.
///
/// # Example
///
/// ```
/// # use rand::Rng;
/// # use rust_decimal_macros::dec;
/// let mut rng = rand::rngs::OsRng;
/// let random = rng.gen_range(dec!(1.00)..=dec!(2.00));
/// assert!(random >= dec!(1.00));
/// assert!(random <= dec!(2.00));
/// assert_eq!(random.scale(), 2);
/// ```
#[inline]
fn new_inclusive<B1, B2>(low: B1, high: B2) -> Self
where
B1: SampleBorrow<Self::X> + Sized,
B2: SampleBorrow<Self::X> + Sized,
{
let (low, high) = sync_scales(*low.borrow(), *high.borrow());
// Return our sampler, which contains an underlying i128 sampler so we
// outsource the actual randomness implementation.
Self {
mantissa_sampler: UniformInt::new_inclusive(low.mantissa(), high.mantissa()),
scale: low.scale(),
}
}
#[inline]
fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Self::X {
let mantissa = self.mantissa_sampler.sample(rng);
Decimal::from_i128_with_scale(mantissa, self.scale)
}
}
/// Return equivalent Decimal objects with the same scale as one another.
#[inline]
fn sync_scales(mut a: Decimal, mut b: Decimal) -> (Decimal, Decimal) {
if a.scale() == b.scale() {
return (a, b);
}
// Set scales to match one another, because we are relying on mantissas'
// being comparable in order outsource the actual sampling implementation.
a.rescale(a.scale().max(b.scale()));
b.rescale(a.scale().max(b.scale()));
// Edge case: If the values have _wildly_ different scales, the values may not have rescaled far enough to match one another.
//
// In this case, we accept some precision loss because the randomization approach we are using assumes that the scales will necessarily match.
if a.scale() != b.scale() {
a.rescale(a.scale().min(b.scale()));
b.rescale(a.scale().min(b.scale()));
}
(a, b)
}
#[cfg(test)]
mod tests {
use std::collections::HashSet;
use super::*;
macro_rules! dec {
($e:expr) => {
Decimal::from_str_exact(stringify!($e)).unwrap()
};
}
#[test]
fn has_random_decimal_instances() {
let mut rng = rand::rngs::OsRng;
let random: [Decimal; 32] = rng.gen();
assert!(random.windows(2).any(|slice| { slice[0] != slice[1] }));
}
#[test]
fn generates_within_range() {
let mut rng = rand::rngs::OsRng;
for _ in 0..128 {
let random = rng.gen_range(dec!(1.00)..dec!(1.05));
assert!(random < dec!(1.05));
assert!(random >= dec!(1.00));
}
}
#[test]
fn generates_within_inclusive_range() {
let mut rng = rand::rngs::OsRng;
let mut values: HashSet<Decimal> = HashSet::new();
for _ in 0..256 {
let random = rng.gen_range(dec!(1.00)..=dec!(1.01));
// The scale is 2, so 1.00 and 1.01 are the only two valid choices.
assert!(random == dec!(1.00) || random == dec!(1.01));
values.insert(random);
}
// Somewhat flaky, will fail 1 out of every 2^255 times this is run.
// Probably acceptable in the real world.
assert_eq!(values.len(), 2);
}
#[test]
fn test_edge_case_scales_match() {
let (low, high) = sync_scales(dec!(1.000_000_000_000_000_000_01), dec!(100_000_000_000_000_000_001));
assert_eq!(low.scale(), high.scale());
}
}
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