Merge pull request 'adding genetic algorithm implementation that chooses which plants to farm' (#3) from genetic_algorithm into master
Reviewed-on: #3
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a139a5376b
@ -25,4 +25,8 @@ class Constants:
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NONE = 'brak'
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CACTUS = 'kaktus'
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POTATO = 'ziemniak'
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WEATH = 'pszenica'
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WHEAT = 'pszenica'
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# Genetic algorithm points average
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POINTS_AVERAGE = 6.33
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62
src/utils/GeneticAlgorithm.py
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62
src/utils/GeneticAlgorithm.py
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@ -0,0 +1,62 @@
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from src.utils.Plants import *
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from random import choice, random
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class GeneticAlgorithm:
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def __init__(self):
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self.mutation_probability = 0.1
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self.stop_condition = stop_condition
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def selection_strategy(self, generation: BaseField):
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maximum_selected_items = int(len(generation) / 10)
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sorted_elements = sorted(generation, key=lambda x: x.evaluation)
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return sorted_elements[:maximum_selected_items]
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def _generate_random_plants(self):
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plant_names = [choice(BaseField.possibilities) for _ in range(9)]
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return [plant_selector(plant_name) for plant_name in plant_names]
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def _generate_first_population(self):
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return [BaseField(self._generate_random_plants()) for _ in range(15)]
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def run(self) -> BaseField:
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first_population = self._generate_first_population()
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first_population.sort(key=lambda x: x.evaluation)
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population_length = len(first_population)
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i = 0
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while True:
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selected = self.selection_strategy(first_population)
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new_population = selected.copy()
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while len(new_population) != population_length:
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child = choice(first_population).crossover(choice(first_population))
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propability = random()
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if propability <= self.mutation_probability:
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child.mutate()
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new_population.append(child)
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first_population = new_population
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best_match = min(first_population, key=lambda x: x.evaluation)
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i += 1
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if self.stop_condition(float(best_match)):
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break
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print(f'Best match is {best_match} with {i} iterations')
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return best_match
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def get_plants(self) -> list:
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result_array = []
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for i in range(4):
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result_array = result_array + self.run().plants
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return result_array
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def main():
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result_array = []
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genetic_algorithm = GeneticAlgorithm()
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for i in range(4):
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result_array = result_array + genetic_algorithm.run().plants
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print(result_array)
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if __name__ == '__main__':
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main()
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104
src/utils/Plants.py
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104
src/utils/Plants.py
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@ -0,0 +1,104 @@
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from constants import Constants
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from random import randint, choice
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class BasePlant:
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def __init__(self):
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self.appearance_points = 0
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self.difficulty_points = 0
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self.profit_points = 0
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def first_population_generator(self):
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pass
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def __int__(self):
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return sum([self.appearance_points, self.profit_points]) - self.difficulty_points
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def __float__(self):
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return self.__int__()
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def stop_condition(average):
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return round(average, 2) == Constants.POINTS_AVERAGE
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def plant_selector(plant_name: str) -> BasePlant:
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if plant_name == Constants.POTATO:
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return Potato()
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elif plant_name == Constants.WHEAT:
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return Wheat()
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elif plant_name == Constants.CACTUS:
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return Cactus()
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class BaseField:
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"""Class that represents what plants grow on a certain field divided into 9 tiles"""
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possibilities = [Constants.WHEAT, Constants.POTATO, Constants.CACTUS]
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def __init__(self, plants):
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self.plants: list(BasePlant) = plants
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self.evaluation = self.evaluate_function()
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def mutate(self):
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self._perform_mutation()
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self.evaluation = self.evaluate_function()
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def _perform_mutation(self):
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random_index = randint(0, 8)
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self.plants[random_index] = plant_selector(choice(self.possibilities))
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def crossover(self, other_field):
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length = int(randint(0, 8))
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new_plants = self.plants[:length] + other_field.plants[length:]
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return BaseField(new_plants)
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def evaluate_function(self) -> float:
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current_fields_average = self.__float__()
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return abs(current_fields_average - Constants.POINTS_AVERAGE)
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def __str__(self):
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return ''.join([str(plant) + ' ' for plant in self.plants])
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def __float__(self):
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return sum([int(plant) for plant in self.plants]) / 9
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class Potato(BasePlant):
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def __init__(self):
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super().__init__()
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self.appearance_points = 3
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self.difficulty_points = 4
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self.profit_points = 7
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def __str__(self):
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return Constants.POTATO
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class Cactus(BasePlant):
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def __init__(self):
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super(Cactus, self).__init__()
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self.appearance_points = 4
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self.difficulty_points = 3
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self.profit_points = 2
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def __str__(self):
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return Constants.CACTUS
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class Wheat(BasePlant):
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def __init__(self):
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super(Wheat, self).__init__()
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self.appearance_points = 5
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self.difficulty_points = 7
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self.profit_points = 9
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def __str__(self):
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return Constants.WHEAT
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@ -2,6 +2,7 @@ import pygame
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from constants import Constants
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from src.tile import Tile
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from utils.GeneticAlgorithm import GeneticAlgorithm
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class World:
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@ -30,6 +31,7 @@ class World:
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self.farmland_wheat = pygame.image.load('assets/images/farmland_wheat.jpg')
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self.farmland_potato = pygame.image.load('assets/images/farmland_potato.jpg')
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self.tiles = pygame.sprite.Group() # mamy tiles jako Sprite Group, to sie przyda potem do kolizji itp.
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self.plants = GeneticAlgorithm().get_plants()
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self.create_tiles()
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def create_tiles(self):
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@ -45,7 +47,7 @@ class World:
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rodzaj_gleby = self.model.df.iloc[df_idx][Constants.SOIL_TYPE]
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stan_nawiezienia = self.model.df.iloc[df_idx][Constants.FERTILIZATION_STATUS]
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stopien_rozwoju = self.model.df.iloc[df_idx][Constants.GROWTH_LEVEL]
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rodzaj_rosliny = self.model.df.iloc[df_idx][Constants.PLANT_TYPE]
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rodzaj_rosliny = self.plants[df_idx].__str__()
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rodzaj_nawozu = self.model.df.iloc[df_idx][Constants.FERTILISER_TYPE]
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to_water = self.model.df.iloc[df_idx][Constants.TO_WATER]
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@ -53,7 +55,7 @@ class World:
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img = pygame.transform.scale(self.farmland_empty, (self.settings.tile_size, self.settings.tile_size))
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elif to_water == 0 and rodzaj_rosliny == Constants.CACTUS:
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img = pygame.transform.scale(self.farmland_cactus, (self.settings.tile_size, self.settings.tile_size))
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elif to_water == 0 and rodzaj_rosliny == Constants.WEATH:
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elif to_water == 0 and rodzaj_rosliny == Constants.WHEAT:
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img = pygame.transform.scale(self.farmland_wheat, (self.settings.tile_size, self.settings.tile_size))
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elif to_water == 0 and rodzaj_rosliny == Constants.POTATO:
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img = pygame.transform.scale(self.farmland_potato, (self.settings.tile_size, self.settings.tile_size))
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@ -61,7 +63,7 @@ class World:
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img = pygame.transform.scale(self.dirt_empty, (self.settings.tile_size, self.settings.tile_size))
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elif to_water == 1 and rodzaj_rosliny == Constants.CACTUS:
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img = pygame.transform.scale(self.dirt_cactus, (self.settings.tile_size, self.settings.tile_size))
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elif to_water == 1 and rodzaj_rosliny == Constants.WEATH:
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elif to_water == 1 and rodzaj_rosliny == Constants.WHEAT:
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img = pygame.transform.scale(self.dirt_wheat, (self.settings.tile_size, self.settings.tile_size))
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elif to_water == 1 and rodzaj_rosliny == Constants.POTATO:
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img = pygame.transform.scale(self.dirt_potato, (self.settings.tile_size, self.settings.tile_size))
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