Male_zoo_Projekt_SI/agent.py

import pygame
import random
from constants import Constants
from state_space_search import is_border, is_obstacle
from night import draw_night
from decision_tree import feed_decision
from constants import Constants
from classification import AnimalClassifier

const = Constants()

classes = [
    "bat",
    "bear",
    "elephant",
    "giraffe",
    "owl",
    "parrot",
    "penguin"
]
class Agent:
    def __init__(self, istate, image_path, grid_size):
        self.istate = istate
        self.x, self.y, self.direction = istate 
        self.grid_size = grid_size
        self.image= pygame.image.load(image_path)
        self.image = pygame.transform.scale(self.image, (grid_size, grid_size))
        self._dryfood = 0
        self._wetfood = 0
        
    def draw(self, const):
        # Obróć obrazek zgodnie z kierunkiem
        if self.direction == 'E':
            self.image= pygame.image.load('images/agent4.png')
        elif self.direction == 'S':
            self.image= pygame.image.load('images/agent1.png')
        elif self.direction == 'W':
            self.image= pygame.image.load('images/agent3.png')
        else:  # direction == 'N'
            self.image= pygame.image.load('images/agent2.png')
        self.image = pygame.transform.scale(self.image, (const.GRID_SIZE, const.GRID_SIZE))
        const.screen.blit(self.image, (self.x * self.grid_size, self.y * self.grid_size))

        if const.IS_NIGHT: draw_night(const)

    def handle_event(self, event, max_x, max_y, animals, obstacles,const):
        if event.type == pygame.KEYDOWN:
            if event.key == pygame.K_UP:
                self.move('Go Forward', max_x, max_y, obstacles, animals,const)
            elif event.key == pygame.K_LEFT:
                self.move('Turn Left', max_x, max_y, obstacles, animals,const)
            elif event.key == pygame.K_RIGHT:
                self.move('Turn Right', max_x, max_y, obstacles, animals,const)

    def move(self, action, max_x, max_y, obstacles, animals, goal,const):
        if action == 'Go Forward':
            new_x, new_y = self.x, self.y
            if self.direction == 'N':
                new_y -= 1
            elif self.direction == 'E':
                new_x += 1
            elif self.direction == 'S':
                new_y += 1
            elif self.direction == 'W':
                new_x -= 1
            
            # Sprawdź, czy nowe położenie mieści się w granicach kraty i nie jest przeszkodą
            if is_border(new_x, new_y, max_x, max_y) and not(is_obstacle(new_x, new_y, obstacles)):
                self.x, self.y = new_x, new_y
                
        elif action == 'Turn Left':
            self.direction = {'N': 'W', 'W': 'S', 'S': 'E', 'E': 'N'}[self.direction]

        elif action == 'Turn Right':
            self.direction = {'N': 'E', 'E': 'S', 'S': 'W', 'W': 'N'}[self.direction]
        
        self.istate = (self.x, self.y, self.direction) 
        feed_animal(self, animals, goal,const)
        take_food(self)

def feed_animal(self, animals, goal,const):
    goal_x, goal_y = goal
    neuron = AnimalClassifier('./model/best_model.pth', classes)
    if self.x == goal_x and self.y == goal_y:
        for animal in animals:
            if animal.x == goal_x and animal.y == goal_y:
                if (animal.activity == 'nocturnal' and const.IS_NIGHT) or (animal.activity == 'diurnal' and not(const.IS_NIGHT)):
                    activity_time = True
                else:
                    activity_time = False
                guests = random.randint(1, 15)
                guess = neuron.classify(animal.image_path)
                if guess == animal.name:
                    print(f"I'm sure this is {guess} and i give it {animal.food} as a snack")
                    animal.draw_snack(const.screen, const.GRID_SIZE, animal.x, animal.y)
                else:
                    print(f"I was wrong, this is not a {guess} but a {animal.name}")
                decision = feed_decision(animal.adult, activity_time, animal.ill, const.season, guests, animal._feed, self._dryfood, self._wetfood)
                if decision != [1]:
                    if decision == [2]:
                        if animal.getting_hungry(const=Constants()) < self._wetfood :
                            self._wetfood -= animal._feed
                            animal._feed = 0
                        else:
                            animal._feed -= self._wetfood
                            self._wetfood = 0
                        print(animal.name, "fed with wet food")
                    else:
                        if animal.getting_hungry(const=Constants()) < self._dryfood :
                            self._dryfood -= animal._feed
                            animal._feed = 0
                        else:
                            animal._feed -= self._dryfood
                            self._dryfood = 0
                        print(animal.name, "fed with dry food")
                    print("Current wet food level: ", self._wetfood)
                    print("Current dry food level: ", self._dryfood)
                else: print(animal.name, " not fed")


def take_food(self):
    house_x = 3
    house_y = 1
    if self.x == house_x and self.y == house_y:
        if self._dryfood < 1 or self._wetfood < 1:
            self._dryfood = 50
            self._wetfood = 50
            print("Agent took food and current food level is", self._dryfood, self._wetfood)