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use crate::{DependentJoint, Distribution, IndependentJoint, RandomVariable};
use rand::prelude::*;
use rand_distr::Poisson as RandPoisson;
use std::{error::Error, ops::BitAnd, ops::Mul};
#[derive(Clone, Debug)]
pub struct Poisson;
#[derive(thiserror::Error, Debug)]
pub enum PoissonError {
#[error("'λ' must be positive")]
LambdaMustBePositive,
#[error("Unknown error")]
Unknown,
}
fn factorial(num: u64) -> u64 {
match num {
0 | 1 => 1,
_ => factorial(num - 1) * num,
}
}
impl Distribution for Poisson {
type T = u64;
type U = PoissonParams;
fn p(&self, x: &Self::T, theta: &Self::U) -> Result<f64, Box<dyn Error>> {
let lambda = theta.lambda();
Ok(lambda.powi(*x as i32) / factorial(*x) as f64 * (-lambda).exp())
}
fn sample(&self, theta: &Self::U, rng: &mut StdRng) -> Result<Self::T, Box<dyn Error>> {
let lambda = theta.lambda();
let poisson = match RandPoisson::new(lambda) {
Ok(n) => n,
Err(_) => return Err(PoissonError::Unknown.into()),
};
Ok(rng.sample(poisson) as u64)
}
}
#[derive(Clone, Debug, PartialEq)]
pub struct PoissonParams {
lambda: f64,
}
impl PoissonParams {
pub fn new(lambda: f64) -> Result<Self, Box<dyn Error>> {
if lambda <= 0.0 {
return Err(PoissonError::LambdaMustBePositive.into());
}
Ok(Self { lambda })
}
pub fn lambda(&self) -> f64 {
self.lambda
}
}
impl<Rhs, TRhs> Mul<Rhs> for Poisson
where
Rhs: Distribution<T = TRhs, U = PoissonParams>,
TRhs: RandomVariable,
{
type Output = IndependentJoint<Self, Rhs, u64, TRhs, PoissonParams>;
fn mul(self, rhs: Rhs) -> Self::Output {
IndependentJoint::new(self, rhs)
}
}
impl<Rhs, URhs> BitAnd<Rhs> for Poisson
where
Rhs: Distribution<T = PoissonParams, U = URhs>,
URhs: RandomVariable,
{
type Output = DependentJoint<Self, Rhs, u64, PoissonParams, URhs>;
fn bitand(self, rhs: Rhs) -> Self::Output {
DependentJoint::new(self, rhs)
}
}
#[cfg(test)]
mod tests {
#[test]
fn it_works() {
assert_eq!(2 + 2, 4);
}
}