prodef 0.1.0

A simple Rust crate for handling probability distributions.
Documentation 
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use crate::{Density, Domain, domain::SDomain};
use nalgebra::{Dim, OVector, RealField, SVector, U1, VectorView};
use rand::Rng;
use rand_distr::{Uniform, uniform::SampleUniform};
use serde::{Deserialize, Serialize};

/// A loguniform probability density function.
#[derive(Clone, Debug, Deserialize, PartialEq, Serialize)]
pub struct LogUniformDensity<T>(SDomain<T>)
where
    T: RealField;

impl<T> LogUniformDensity<T>
where
    T: RealField,
{
    /// Create a new [`LogUniformDensity`].
    pub fn new(a: T, b: T) -> Option<Self> {
        if a > b {
            None
        } else {
            Some(Self(SDomain::Bounded(a, b)))
        }
    }
}

impl<T> Density<T, U1> for LogUniformDensity<T>
where
    T: RealField + SampleUniform,
    SDomain<T>: Domain<T, U1>,
    for<'a> &'a SDomain<T>: Domain<T, U1>,
{
    fn density<RStride: Dim, CStride: Dim>(
        &self,
        sample: &VectorView<T, U1, RStride, CStride>,
    ) -> Option<T> {
        (&self).density(sample)
    }

    fn domain(&self) -> impl Domain<T, U1> + 'static {
        self.0.clone()
    }

    fn center(&self) -> SVector<T, 1> {
        (&self).center()
    }

    fn is_constant(&self) -> OVector<bool, U1> {
        (&self).is_constant()
    }

    fn sample(&self, rng: &mut impl Rng, max_attempts: usize) -> Option<SVector<T, 1>> {
        (&self).sample(rng, max_attempts)
    }
}

impl<T> Density<T, U1> for &LogUniformDensity<T>
where
    T: RealField + SampleUniform,
    SDomain<T>: Domain<T, U1>,
    for<'a> &'a SDomain<T>: Domain<T, U1>,
{
    fn density<RStride: Dim, CStride: Dim>(
        &self,
        sample: &VectorView<T, U1, RStride, CStride>,
    ) -> Option<T> {
        if !self.0.contains(sample) {
            return None;
        }

        Some(
            T::one()
                / (sample[0].clone()
                    * (self.0.maximum_values().unwrap()[0].clone().ln()
                        - self.0.minimum_values().unwrap()[0].clone().ln())),
        )
    }

    fn domain(&self) -> impl Domain<T, U1> + 'static {
        self.0.clone()
    }

    fn center(&self) -> SVector<T, 1> {
        match &self.0 {
            SDomain::Bounded(a, b) => {
                let mean = (b.clone().ln() + a.clone().ln()) / T::from_usize(2).unwrap();
                SVector::from([mean.exp()])
            }
            _ => unreachable!(),
        }
    }

    fn is_constant(&self) -> OVector<bool, U1> {
        OVector::<bool, U1>::from_element(false)
    }

    fn sample(&self, rng: &mut impl Rng, _max_attempts: usize) -> Option<SVector<T, 1>> {
        let uniform = Uniform::new_inclusive(
            self.0.minimum_values().unwrap()[0].clone().ln(),
            self.0.maximum_values().unwrap()[0].clone().ln(),
        )
        .unwrap();

        Some(SVector::from([rng.sample(uniform).exp()]))
    }
}