causal-hub 0.0.4

A library for causal models, inference and discovery.
Documentation 
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mod table;
mod trajectory;

use crate::{
    datasets::MissingMethod,
    models::Labelled,
    types::{Labels, Map, Set},
};

/// A struct representing a Bayesian estimator.
#[derive(Clone, Debug)]
pub struct BE<'a, D, T> {
    dataset: &'a D,
    missing_method: Option<MissingMethod>,
    missing_mechanism: Option<Map<usize, Set<usize>>>,
    prior: T,
}

impl<'a, D> BE<'a, D, ()> {
    /// Creates a new Bayesian estimator.
    ///
    /// # Arguments
    ///
    /// * `dataset` - A reference to the dataset to fit the estimator to.
    ///
    /// # Returns
    ///
    /// A new Bayesian estimator.
    ///
    #[inline]
    pub const fn new(dataset: &'a D) -> Self {
        Self {
            dataset,
            missing_method: None,
            missing_mechanism: None,
            prior: (),
        }
    }
}

impl<'a, D, T> BE<'a, D, T> {
    /// Sets the missing handling method.
    ///
    /// # Arguments
    ///
    /// * `missing_method` - An optional missing handling method to set.
    /// * `missing_mechanism` - An optional missing mechanism to set.
    ///
    /// # Returns
    ///
    /// A new estimator with the specified missing handling method.
    ///
    #[inline]
    pub fn with_missing_method(
        mut self,
        missing_method: Option<MissingMethod>,
        missing_mechanism: Option<Map<usize, Set<usize>>>,
    ) -> Self {
        self.missing_method = missing_method;
        self.missing_mechanism = missing_mechanism;
        self
    }

    /// Sets the prior distribution.
    ///
    /// # Arguments
    ///
    /// * `prior` - The prior distribution to set.
    ///
    /// # Returns
    ///
    /// A new Bayesian estimator with the specified prior.
    ///
    #[inline]
    pub fn with_prior<U>(self, prior: U) -> BE<'a, D, U> {
        BE {
            dataset: self.dataset,
            missing_method: self.missing_method,
            missing_mechanism: self.missing_mechanism,
            prior,
        }
    }
}

impl<D, T> Labelled for BE<'_, D, T>
where
    D: Labelled,
{
    #[inline]
    fn labels(&self) -> &Labels {
        self.dataset.labels()
    }
}