improved version of working algorithm; generated plants are now displayed on the map

src/constants.py

@@ -29,4 +29,4 @@ class Constants:
 
     # Genetic algorithm points average
 
-    POINTS_AVERAGE = range(5, 8)
+    POINTS_AVERAGE = 6.33

src/utils/GeneticAlgorithm.py

@@ -1,5 +1,4 @@
-from Plants import *
-
+from src.utils.Plants import *
 from random import choice, random
 
 
@@ -19,9 +18,9 @@ class GeneticAlgorithm:
         return [plant_selector(plant_name) for plant_name in plant_names]
 
     def _generate_first_population(self):
-        return [BaseField(self._generate_random_plants()) for _ in range(100)]
+        return [BaseField(self._generate_random_plants()) for _ in range(15)]
 
-    def run(self):
+    def run(self) -> BaseField:
         first_population = self._generate_first_population()
         first_population.sort(key=lambda x: x.evaluation)
         population_length = len(first_population)
@@ -31,7 +30,8 @@ class GeneticAlgorithm:
             new_population = selected.copy()
             while len(new_population) != population_length:
                 child = choice(first_population).crossover(choice(first_population))
-                if random() <= self.mutation_probability:
+                propability = random()
+                if propability <= self.mutation_probability:
                     child.mutate()
                 new_population.append(child)
 
@@ -40,11 +40,22 @@ class GeneticAlgorithm:
             i += 1
             if self.stop_condition(float(best_match)):
                 break
-        print(best_match)
+        print(f'Best match is {best_match} with {i} iterations')
+        return best_match
+
+    def get_plants(self) -> list:
+        result_array = []
+        for i in range(4):
+            result_array = result_array + self.run().plants
+        return result_array
 
 
 def main():
-    GeneticAlgorithm().run()
+    result_array = []
+    genetic_algorithm = GeneticAlgorithm()
+    for i in range(4):
+        result_array = result_array + genetic_algorithm.run().plants
+    print(result_array)
 
 
 if __name__ == '__main__':

src/utils/Plants.py

@@ -20,7 +20,7 @@ class BasePlant:
 
 
 def stop_condition(average):
-    return average in Constants.POINTS_AVERAGE
+    return round(average, 2) == Constants.POINTS_AVERAGE
 
 
 def plant_selector(plant_name: str) -> BasePlant:
@@ -56,12 +56,7 @@ class BaseField:
 
     def evaluate_function(self) -> float:
         current_fields_average = self.__float__()
-        if current_fields_average not in Constants.POINTS_AVERAGE:
-            if current_fields_average < Constants.POINTS_AVERAGE[0]:
-                return abs(current_fields_average - Constants.POINTS_AVERAGE[0])
-            elif current_fields_average > Constants.POINTS_AVERAGE[-1]:
-                return abs(current_fields_average - Constants.POINTS_AVERAGE[1])
-        return 0
+        return abs(current_fields_average - Constants.POINTS_AVERAGE)
 
     def __str__(self):
         return ''.join([str(plant) + ' ' for plant in self.plants])
@@ -88,7 +83,7 @@ class Cactus(BasePlant):
     def __init__(self):
 
         super(Cactus, self).__init__()
-        self.appearance_points = 6
+        self.appearance_points = 4
         self.difficulty_points = 3
         self.profit_points = 2
 

src/world.py

@@ -2,6 +2,7 @@ import pygame
 
 from constants import Constants
 from src.tile import Tile
+from utils.GeneticAlgorithm import GeneticAlgorithm
 
 
 class World:
@@ -30,6 +31,7 @@ class World:
         self.farmland_wheat = pygame.image.load('assets/images/farmland_wheat.jpg')
         self.farmland_potato = pygame.image.load('assets/images/farmland_potato.jpg')
         self.tiles = pygame.sprite.Group()  # mamy tiles jako Sprite Group, to sie przyda potem do kolizji itp.
+        self.plants = GeneticAlgorithm().get_plants()
         self.create_tiles()
 
     def create_tiles(self):
@@ -45,7 +47,7 @@ class World:
                     rodzaj_gleby = self.model.df.iloc[df_idx][Constants.SOIL_TYPE]
                     stan_nawiezienia = self.model.df.iloc[df_idx][Constants.FERTILIZATION_STATUS]
                     stopien_rozwoju = self.model.df.iloc[df_idx][Constants.GROWTH_LEVEL]
-                    rodzaj_rosliny = self.model.df.iloc[df_idx][Constants.PLANT_TYPE]
+                    rodzaj_rosliny = self.plants[df_idx].__str__()
                     rodzaj_nawozu = self.model.df.iloc[df_idx][Constants.FERTILISER_TYPE]
                     to_water = self.model.df.iloc[df_idx][Constants.TO_WATER]