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use rand::Rng;
use crate::{ziggurat_tables, Distribution};
use crate::utils::{ziggurat, Float};
#[derive(Clone, Copy, Debug)]
pub struct Exp1;
impl Distribution<f32> for Exp1 {
#[inline]
fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f32 {
let x: f64 = self.sample(rng);
x as f32
}
}
impl Distribution<f64> for Exp1 {
#[inline]
fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64 {
#[inline]
fn pdf(x: f64) -> f64 {
(-x).exp()
}
#[inline]
fn zero_case<R: Rng + ?Sized>(rng: &mut R, _u: f64) -> f64 {
ziggurat_tables::ZIG_EXP_R - rng.gen::<f64>().ln()
}
ziggurat(rng, false,
&ziggurat_tables::ZIG_EXP_X,
&ziggurat_tables::ZIG_EXP_F,
pdf, zero_case)
}
}
#[derive(Clone, Copy, Debug)]
pub struct Exp<N> {
lambda_inverse: N
}
#[derive(Clone, Copy, Debug, PartialEq, Eq)]
pub enum Error {
LambdaTooSmall,
}
impl<N: Float> Exp<N>
where Exp1: Distribution<N>
{
#[inline]
pub fn new(lambda: N) -> Result<Exp<N>, Error> {
if !(lambda > N::from(0.0)) {
return Err(Error::LambdaTooSmall);
}
Ok(Exp { lambda_inverse: N::from(1.0) / lambda })
}
}
impl<N: Float> Distribution<N> for Exp<N>
where Exp1: Distribution<N>
{
fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> N {
rng.sample(Exp1) * self.lambda_inverse
}
}
#[cfg(test)]
mod test {
use crate::Distribution;
use super::Exp;
#[test]
fn test_exp() {
let exp = Exp::new(10.0).unwrap();
let mut rng = crate::test::rng(221);
for _ in 0..1000 {
assert!(exp.sample(&mut rng) >= 0.0);
}
}
#[test]
#[should_panic]
fn test_exp_invalid_lambda_zero() {
Exp::new(0.0).unwrap();
}
#[test]
#[should_panic]
fn test_exp_invalid_lambda_neg() {
Exp::new(-10.0).unwrap();
}
}