Delete old enemy Fitness script and fix its references

Author: Tyago-Teoi

Assets/Scripts/Game/EnemyGenerator/EnemyGenerator.cs

@@ -13,9 +13,9 @@ public class EnemyGenerator
         private SearchSpaceConfig _searchSpace;
         private Population _solution;
         private GeneticAlgorithmData _data;
+        private readonly IEnemyFitness _fitnessFunction;
         public Population Solution { get => _solution; }
         public GeneticAlgorithmData Data { get => _data; }
-        private readonly IEnemyFitness _fitnessFunction;
 
         public EnemyGenerator(EnemyGeneratorGeneticAlgorithmSettings parameters, SearchSpaceConfig searchSpace, IEnemyFitness fitnessFunction)
         {
@@ -43,14 +43,14 @@ private void Evolution()
 
             Population pop = new Population(
                 _parameters.numberOfMovements,
-                _parameters.numberOfWeapons
+                _parameters.numberOfWeapons,
+                _fitnessFunction
             );
             while (pop.Count() < _parameters.initialPopulationSize)
             {
                 Individual ind = Individual.GetRandom(_searchSpace);
                 //Difficulty.Calculate(ref ind);
                 _fitnessFunction.Calculate(ref ind, _parameters.difficulty);
-                Fitness.Calculate(ref ind, _parameters.difficulty);
                 pop.PlaceIndividual(ind);
             }
             _data.initialPopulation = new List<Individual>(pop.ToList());
@@ -61,7 +61,7 @@ private void Evolution()
                 List<Individual> intermediate = new List<Individual>();
                 while (intermediate.Count < _parameters.intermediatePopulationSize)
                 {
-                    Individual[] parents = Selection.Select(CROSSOVER_PARENTS, _parameters.numberOfCompetitors, pop);
+                    Individual[] parents = Selection.Select(CROSSOVER_PARENTS, _parameters.numberOfCompetitors, pop, _fitnessFunction);
                     Individual[] offspring = Crossover.Apply(parents[0], parents[1], _searchSpace);
 
                     if (_parameters.mutationRate > RandomSingleton.GetInstance().RandomPercent())
@@ -75,7 +75,7 @@ private void Evolution()
                     for (int i = 0; i < offspring.Length; i++)
                     {
                         //Difficulty.Calculate(ref offspring[i]);
-                        Fitness.Calculate(ref offspring[i], _parameters.difficulty);
+                        _fitnessFunction.Calculate(ref offspring[i], _parameters.difficulty);
                         intermediate.Add(offspring[i]);
                     }
                 }

Assets/Scripts/Game/EnemyGenerator/Fitness.cs

@@ -24,14 +24,14 @@ public struct Population
         /// The MAP-Elites map (a matrix of individuals).
         public Individual[,] map { get; }
 
+        private IEnemyFitness _fitnessFunction;
+
         /// MAP-Elites Population constructor.
-        public Population(
-            int _movement,
-            int _weapons
-        )
+        public Population(int _movement, int _weapons, IEnemyFitness fitnessFunction)
         {
             dimension = (_movement, _weapons);
             map = new Individual[dimension.movement, dimension.weapon];
+            _fitnessFunction = fitnessFunction;
         }
 
         /// Return the number of Elites of the population.
@@ -82,7 +82,7 @@ Individual _individual
             int m = Convert.ToInt32(_individual.Enemy.Movement);
             int w = Convert.ToInt32(_individual.Weapon.Weapon);
             // If the new individual deserves to survive
-            if (Fitness.IsBest(_individual, map[m, w]))
+            if (_fitnessFunction.IsBest(_individual, map[m, w]))
             {
                 // Then, place the individual in the MAP-Elites population
                 map[m, w] = _individual;

Assets/Scripts/Game/EnemyGenerator/Fitness.cs.meta

@@ -14,7 +14,6 @@ public static class Selection
         public static readonly string NOT_ENOUGH_COMPETITORS =
             "There are not enough individuals in the entered population to " +
             "perform this operation.";
-
         /// Select individuals from the MAP-Elites population.
         ///
         /// This function ensures that the same individual will not be selected
@@ -23,7 +22,7 @@ public static class Selection
         /// population. Instead of selecting directly an individual, we select
         /// its coordinate from the auxiliary list and remove it then it is not
         /// available for the next selection.
-        public static Individual[] Select(int _amount, int _competitors, Population _pop)
+        public static Individual[] Select(int _amount, int _competitors, Population _pop, IEnemyFitness fitnessFunction)
         {
             // Get the list of Elites' coordinates (the available competitors)
             List<Coordinate> avco = _pop.GetElitesCoordinates();
@@ -40,7 +39,8 @@ public static Individual[] Select(int _amount, int _competitors, Population _pop
                 (Coordinate coordinate, Individual individual) = Tournament(
                     _competitors, // Number of competitors
                     _pop,         // Population
-                    avco         // List of available competitors
+                    avco,         // List of available competitors
+                    fitnessFunction
                 );
                 // Select an individual and remove it from available competitors
                 individuals[i] = individual;
@@ -58,6 +58,7 @@ public static Individual[] Select(int _amount, int _competitors, Population _pop
             int _competitors,
             Population _pop,
             List<Coordinate> _avco
+            , IEnemyFitness fitnessFunction
         )
         {
             // List of available competitors
@@ -79,7 +80,7 @@ List<Coordinate> _avco
             Coordinate coordinate = (Common.UNKNOWN, Common.UNKNOWN);
             for (int i = 0; i < _competitors; i++)
             {
-                if (Fitness.IsBest(competitors[i], winner))
+                if (fitnessFunction.IsBest(competitors[i], winner))
                 {
                     winner = competitors[i];
                     coordinate = coordinates[i];