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// use crate::{
// ConditionDifferentiableDistribution, DependentJoint, Distribution, DistributionError, Event,
// IndependentJoint, RandomVariable, ValueDifferentiableDistribution,
// };
// use rand::prelude::*;
// use std::{
// fmt::Debug,
// marker::PhantomData,
// ops::{BitAnd, Mul},
// };
// #[derive(Clone, Debug)]
// pub struct ConditionalizeLatentVariableDistribution<D, F, T, U, V, W>
// where
// D: Distribution<Value = T, Condition = U>,
// F: Fn((V, W)) -> (T, U) + Clone + Debug + Send + Sync,
// T: RandomVariable,
// U: RandomVariable,
// V: RandomVariable,
// W: RandomVariable,
// {
// distribution: D,
// converter: F,
// phantom: PhantomData<(V, W)>,
// }
// impl<D, F, T, U, V, W> ConditionalizeLatentVariableDistribution<D, F, T, U, V, W>
// where
// D: Distribution<Value = T, Condition = U>,
// F: Fn((V, W)) -> (T, U) + Clone + Debug + Send + Sync,
// T: RandomVariable,
// U: RandomVariable,
// V: RandomVariable,
// W: RandomVariable,
// {
// pub fn new(distribution: D, converter: F) -> Self {
// Self {
// distribution,
// converter,
// phantom: PhantomData,
// }
// }
// }
// impl<D, F, T, U, V, W> Distribution for ConditionalizeLatentVariableDistribution<D, F, T, U, V, W>
// where
// D: Distribution<Value = T, Condition = U>,
// F: Fn((V, W)) -> (T, U) + Clone + Debug + Send + Sync,
// T: RandomVariable,
// U: RandomVariable,
// V: RandomVariable,
// W: RandomVariable,
// {
// type Value = V;
// type Condition = W;
// fn p_kernel(
// &self,
// x: &Self::Value,
// theta: &Self::Condition,
// ) -> Result<f64, crate::DistributionError> {
// let converted = (x, theta).converter();
// self.distribution.p_kernel(converted.0, converted.1)
// }
// fn sample(
// &self,
// x: &Self::Value,
// theta: &Self::Condition,
// rng: &mut dyn RngCore,
// ) -> Result<Self::Value, crate::DistributionError> {
// todo!()
// }
// }
// impl<D, F, T, U, V, W, Rhs, TRhs> Mul<Rhs>
// for ConditionalizeLatentVariableDistribution<D, F, T, U, V, W>
// where
// D: Distribution<Value = T, Condition = U>,
// F: Fn((V, W)) -> (T, U) + Clone + Debug + Send + Sync,
// T: RandomVariable,
// U: RandomVariable,
// V: RandomVariable,
// W: RandomVariable,
// Rhs: Distribution<Value = TRhs, Condition = U>,
// TRhs: RandomVariable,
// {
// type Output = ConditionalizeLatentVariableDistribution<
// IndependentJoint<D, Rhs, T, TRhs, U>,
// F,
// T,
// U,
// V,
// W,
// >;
// fn mul(self, rhs: Rhs) -> Self::Output {
// ConditionalizeLatentVariableDistribution::new(
// IndependentJoint::new(self.distribution, rhs),
// self.converter,
// )
// }
// }
// impl<D, F, T, U, V, W, Rhs, URhs> BitAnd<Rhs>
// for ConditionalizeLatentVariableDistribution<D, F, T, U, V, W>
// where
// D: Distribution<Value = T, Condition = U>,
// F: Fn((V, W)) -> (T, U) + Clone + Debug + Send + Sync,
// T: RandomVariable,
// U: RandomVariable,
// V: RandomVariable,
// W: RandomVariable,
// Rhs: Distribution<Value = U, Condition = URhs>,
// URhs: RandomVariable,
// {
// type Output = ConditionalizeLatentVariableDistribution<
// DependentJoint<D, Rhs, T, U, URhs>,
// F,
// (T, U),
// URhs,
// V,
// W,
// >;
// fn bitand(self, rhs: Rhs) -> Self::Output {
// let converter_new = |result: (V, W, URhs)| ((result.0, result.1).converter(), result.2);
// ConditionalizeLatentVariableDistribution::new(
// DependentJoint::new(self.distribution, rhs),
// converter_new,
// )
// }
// }
// impl<D, F, T, U, V, W> ValueDifferentiableDistribution
// for ConditionalizeLatentVariableDistribution<D, F, T, U, V, W>
// where
// D: Distribution<Value = T, Condition = U>,
// F: Fn((V, W)) -> (T, U) + Clone + Debug + Send + Sync,
// T: RandomVariable,
// U: RandomVariable,
// V: RandomVariable,
// W: RandomVariable,
// {
// fn ln_diff_value(
// &self,
// x: &Self::Value,
// theta: &Self::Condition,
// ) -> Result<Vec<f64>, DistributionError> {
// let converted = (x, theta).converter()?;
// let v_len = x.len();
// let t_len = converted.0.len();
// let diff = t_len - v_len;
// if 0 < diff {
// let value_orig = self.distribution.ln_diff_value(converted)?;
// let condition_orig = self.distribution.ln_diff_condition(converted)?;
// let result_value = [value_orig, condition_orig[..diff]].concat();
// Ok(result_value)
// } else {
// let value_orig = self.distribution.ln_diff_value(converted)?;
// Ok(value_orig[..t_len])
// }
// }
// }
// impl<D, F, T, U, V, W> ConditionDifferentiableDistribution
// for ConditionalizeLatentVariableDistribution<D, F, T, U, V, W>
// where
// D: Distribution<Value = T, Condition = U>,
// F: Fn((V, W)) -> (T, U) + Clone + Debug + Send + Sync,
// T: RandomVariable,
// U: RandomVariable,
// V: RandomVariable,
// W: RandomVariable,
// {
// fn ln_diff_condition(
// &self,
// x: &Self::Value,
// theta: &Self::Condition,
// ) -> Result<Vec<f64>, DistributionError> {
// let converted = (x, theta).converter()?;
// let w_len = x.len();
// let u_len = converted.1.len();
// let diff = u_len - w_len;
// if 0 < diff {
// let value_orig = self.distribution.ln_diff_value(converted)?;
// let condition_orig = self.distribution.ln_diff_condition(converted)?;
// let result_condition = [value_orig[w_len..], condition_orig].concat();
// Ok(result_condition)
// } else {
// let value_orig = self.distribution.ln_diff_condition(converted)?;
// Ok(value_orig[..w_len])
// }
// }
// }