1 files changed, 16 insertions(+), 23 deletions(-)

M codes/eoa_lib/src/evolution.rs

@@ 101,18 101,18 @@ pub fn evolution_algorithm<TChromosome: Clone, TResult: Clone>(
 pub mod tests {
     use nalgebra::Const;
 
-    use crate::{binary_string::BinaryString, comparison::MinimizingOperator, crossover::BinaryOnePointCrossover, fitness::one_max::OneMax, initializer::{Initializer, RandomInitializer}, pairing::AdjacentPairing, perturbation::{BinaryStringBitPerturbation, MutationPerturbation}, replacement::{BestReplacement, Population}, selection::TournamentSelection};
+    use crate::{binary_string::BinaryString, comparison::MinimizingOperator, crossover::BinaryOnePointCrossover, fitness::one_max::OneMax, initializer::{Initializer, RandomInitializer}, pairing::AdjacentPairing, perturbation::{BinaryStringBitPerturbation, BinaryStringFlipPerturbation, BinaryStringSingleBitPerturbation, CombinedPerturbation, MutationPerturbation}, replacement::{BestReplacement, Population, TournamentReplacement}, selection::TournamentSelection};
 
     use super::evolution_algorithm;
 
     #[test]
-    pub fn test_one_max() {
+    pub fn test_evolution_one_max() {
         const D: usize = 512;
         let optimum = BinaryString::<Const<D>>::new(vec![0; D]);
         let one_max = OneMax::<Const<D>>::new();
 
         let initializer = RandomInitializer::<Const<D>, BinaryString::<Const<D>>>::new_binary();
-        let population_size = 512;
+        let population_size = 10;
 
         let mut rng_init = rand::rng();
         let population = Population::from_vec(


@@ 122,34 122,27 @@ pub mod tests {
         let mut rng = rand::rng();
         let result = evolution_algorithm(
             population,
-            population_size / 4,
+            50,
             &one_max,
-            // TODO: tournament should somehow accept sorting?
-            // TODO: deterministic and nondeterministic tournament ordering
-            &TournamentSelection::new(3, 0.8),
+            &TournamentSelection::new(5, 0.8),
             &mut AdjacentPairing::new(),
             &BinaryOnePointCrossover::new(),
-            &MutationPerturbation::new(
-                Box::new(BinaryStringBitPerturbation::new(0.05)),
-                0.1),
-            &BestReplacement::new(),
+            &CombinedPerturbation::new(
+                vec![
+                    Box::new(MutationPerturbation::new(
+                        Box::new(BinaryStringSingleBitPerturbation::new()),
+                        0.3)),
+                    Box::new(MutationPerturbation::new(
+                        Box::new(BinaryStringFlipPerturbation::new()),
+                        0.3))
+                ]
+            ),
+            &TournamentReplacement::new(5, 0.8),
             &MinimizingOperator,
             1000,
             &mut rng
         ).unwrap();
 
-        println!("{:?}", result.stats.best_candidates
-                 .iter()
-                 .map(|candidate| candidate.evaluated_chromosome.evaluation)
-                 .collect::<Vec<_>>());
-        println!("{:?}", result.stats.best_candidates
-                 .iter()
-                 .map(|candidate| candidate.iteration)
-                 .collect::<Vec<_>>());
-        println!("{:?}", result.population.best_candidate(&MinimizingOperator));
-        println!("{:?}", result.best_candidate);
-        // println!("{:?}", res);
-
         assert_eq!(
             result.best_candidate.evaluation,
             0