1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92

use crate::{DependentJoint, Distribution, IndependentJoint, RandomVariable};
use rand::prelude::StdRng;
use std::iter::Iterator;
use std::{error::Error, ops::BitAnd, ops::Mul};

/// # IndependentArrayJoint
/// ![tex](https://latex.codecogs.com/svg.latex?p%28\mathbf%7Ba%7D%7Cb%29%3D\prod_%7Bi\in%20I%7Dp%28a_i%7Cb%29)
pub struct IndependentArrayJoint<D, T, U>
where
    D: Distribution<T = T, U = U>,
    T: RandomVariable,
    U: RandomVariable,
{
    distributions: Vec<D>,
}

impl<D, T, U> Distribution for IndependentArrayJoint<D, T, U>
where
    D: Distribution<T = T, U = U>,
    T: RandomVariable,
    U: RandomVariable,
{
    type T = Vec<T>;
    type U = U;

    fn p(&self, x: &Self::T, theta: &Self::U) -> Result<f64, Box<dyn Error>> {
        x.iter()
            .enumerate()
            .map(|(i, xi)| self.distributions[i].p(xi, theta))
            .product()
    }

    fn sample(&self, theta: &Self::U, rng: &mut StdRng) -> Result<Self::T, Box<dyn Error>> {
        self.distributions
            .iter()
            .map(|di| di.sample(theta, rng))
            .collect()
    }
}

impl<D, T, U, Rhs, TRhs> Mul<Rhs> for IndependentArrayJoint<D, T, U>
where
    D: Distribution<T = T, U = U>,
    T: RandomVariable,
    U: RandomVariable,
    Rhs: Distribution<T = TRhs, U = U>,
    TRhs: RandomVariable,
{
    type Output = IndependentJoint<Self, Rhs, Vec<T>, TRhs, U>;

    fn mul(self, rhs: Rhs) -> Self::Output {
        IndependentJoint::new(self, rhs)
    }
}

impl<D, T, U, Rhs, URhs> BitAnd<Rhs> for IndependentArrayJoint<D, T, U>
where
    D: Distribution<T = T, U = U>,
    T: RandomVariable,
    U: RandomVariable,
    Rhs: Distribution<T = U, U = URhs>,
    URhs: RandomVariable,
{
    type Output = DependentJoint<Self, Rhs, Vec<T>, U, URhs>;

    fn bitand(self, rhs: Rhs) -> Self::Output {
        DependentJoint::new(self, rhs)
    }
}

pub trait DistributionProduct<D, T, U>
where
    D: Distribution<T = T, U = U>,
    T: RandomVariable,
    U: RandomVariable,
{
    fn product(self) -> IndependentArrayJoint<D, T, U>;
}

impl<I, D, T, U> DistributionProduct<D, T, U> for I
where
    I: Iterator<Item = D>,
    D: Distribution<T = T, U = U>,
    T: RandomVariable,
    U: RandomVariable,
{
    fn product(self) -> IndependentArrayJoint<D, T, U> {
        let distributions = self.collect::<Vec<_>>();

        IndependentArrayJoint::<D, T, U> { distributions }
    }
}