radiate-core 1.2.22

Core traits and interfaces for the Radiate genetic algorithm library.
Documentation
use super::Codec;
use crate::{BitChromosome, Chromosome, Gene, Genotype};
use std::sync::Arc;

/// A `Codec` for a subset of items. This is useful for problems where the goal is to find the best subset of items
/// from a larger set of items. The `encode` function creates a `Genotype` with a single chromosome of `BitGenes`
/// where each gene represents an item in the `items` vector. The `decode` function creates a `Vec<&T>` from the
/// `Genotype` where the `Vec` contains the items that are selected by the `BitGenes` - the `true` genes.
///
/// A `SubSetCodec` is useful for problems like the Knapsack problem, where the goal is to find the best subset of items
/// that fit in a knapsack. The `items` vector would contain the items that can be placed in the knapsack and the `Genotype`
/// would contain `BitGenes` that represent weather or not the item is in the knapsack.
#[derive(Clone)]
pub struct SubSetCodec<T> {
    items: Arc<[Arc<T>]>,
}

impl<T> SubSetCodec<T> {
    pub fn new(items: Vec<T>) -> Self {
        SubSetCodec {
            items: items.into_iter().map(Arc::new).collect(),
        }
    }
}

impl<T> Codec<BitChromosome, Vec<Arc<T>>> for SubSetCodec<T> {
    fn encode(&self) -> Genotype<BitChromosome> {
        Genotype::new(vec![BitChromosome::new(self.items.len())])
    }

    fn decode(&self, genotype: &Genotype<BitChromosome>) -> Vec<Arc<T>> {
        let mut result = Vec::new();
        for (i, gene) in genotype.iter().next().unwrap().iter().enumerate() {
            if *gene.allele() {
                result.push(Arc::clone(&self.items[i]));
            }
        }

        result
    }
}