lace 0.9.1

A probabilistic cross-categorization engine
Documentation 
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#![warn(unused_extern_crates)]
#![warn(
    clippy::all,
    clippy::imprecise_flops,
    clippy::suboptimal_flops,
    clippy::unseparated_literal_suffix,
    clippy::unreadable_literal,
    clippy::option_option,
    clippy::implicit_clone
)]

pub mod assignment;
mod cdf;
mod chi_square;
// pub mod dist;
mod entropy;
pub mod integrate;
mod ks;
pub mod mat;
pub mod mh;
mod mixture_type;
mod perm;
pub mod prior;
pub mod prior_process;
pub mod seq;
mod simplex;
pub mod uncertainty;

mod sample_error;

pub use cdf::EmpiricalCdf;
pub use entropy::QmcEntropy;
use itertools::iproduct;
pub use mixture_type::MixtureType;
pub use perm::L2Norm;
use rand::Rng;
use rv::traits::KlDivergence;
use rv::traits::Rv;
pub use sample_error::SampleError;
pub use simplex::*;

pub mod test {
    pub use chi_square::chi_square_test;
    pub use ks::ks2sample;
    pub use ks::ks_test;
    pub use perm::gauss_kernel;
    pub use perm::gauss_perm_test;
    pub use perm::perm_test;

    use super::chi_square;
    use super::ks;
    use super::perm;
}

/// Trait defining methods to update prior hyperparameters
pub trait UpdatePrior<X, Fx: Rv<X>, H> {
    /// Draw new prior parameters given a set of existing models and the hyper
    /// prior. Returns the likelihood of the components given the new prior
    fn update_prior<R: Rng>(
        &mut self,
        components: &[&Fx],
        hyper: &H,
        rng: &mut R,
    ) -> f64;
}

impl UpdatePrior<bool, rv::dist::Bernoulli, ()> for rv::dist::Beta {
    fn update_prior<R: rand::Rng>(
        &mut self,
        _components: &[&rv::dist::Bernoulli],
        _hyper: &(),
        _rng: &mut R,
    ) -> f64 {
        0.0
    }
}

/// Compute the Jensen-Shannon divergence of all Components of a Mixture
pub trait MixtureJsd {
    fn mixture_jsd(&self) -> f64;
}

/// Compute pairwise KL divergence on collections of probability distributions
pub trait PairwiseKl {
    /// Sum of pairwise KL Divergences
    fn pairwise_kl(&self) -> f64;
}

impl<Fx> PairwiseKl for Vec<Fx>
where
    Fx: KlDivergence,
{
    fn pairwise_kl(&self) -> f64 {
        iproduct!(self, self).fold(0_f64, |acc, (f1, f2)| acc + f1.kl(f2))
    }
}