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use super::{Crossover, KeepParent};
use crate::chromosome::Chromosome;
use crate::genotype::Genotype;
use crate::population::Population;
use rand::distributions::{Bernoulli, Distribution};
use rand::Rng;

/// Crossover with 50% probability for each gene to come from one of the two parents.
/// Optionally keep parents around to compete with children later on.
///
/// Not allowed for unique genotypes as it would not preserve the gene uniqueness in the children.
#[derive(Clone, Debug)]
pub struct Uniform(pub KeepParent);
impl Crossover for Uniform {
    fn call<T: Genotype, R: Rng>(&self, genotype: &T, population: &mut Population<T>, rng: &mut R) {
        if population.size() < 2 {
            return;
        }
        let crossover_indexes = genotype.crossover_indexes();
        let bool_sampler = Bernoulli::new(0.5).unwrap();

        if self.0 {
            let mut child_chromosomes: Vec<Chromosome<T>> = Vec::with_capacity(population.size());

            for chunk in population.chromosomes.chunks(2) {
                if let [father, mother] = chunk {
                    let mut child_father_genes = father.genes.clone();
                    let mut child_mother_genes = mother.genes.clone();

                    for index in &crossover_indexes {
                        if bool_sampler.sample(rng) {
                            std::mem::swap(
                                &mut child_father_genes[*index],
                                &mut child_mother_genes[*index],
                            );
                        }
                    }

                    // no need to taint_fitness_score as it is initialized with None
                    child_chromosomes.push(Chromosome::new(child_father_genes));
                    child_chromosomes.push(Chromosome::new(child_mother_genes));
                }
            }

            population.chromosomes.append(&mut child_chromosomes);
        } else {
            for chunk in population.chromosomes.chunks_mut(2) {
                if let [father, mother] = chunk {
                    for index in &crossover_indexes {
                        if bool_sampler.sample(rng) {
                            std::mem::swap(&mut father.genes[*index], &mut mother.genes[*index]);
                        }
                    }
                    mother.taint_fitness_score();
                    father.taint_fitness_score();
                }
            }
        }
    }
    fn require_crossover_indexes(&self) -> bool {
        true
    }
    fn require_crossover_points(&self) -> bool {
        false
    }
}