feat and fix
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MlodyJacky
parent
b5e69bcc97
commit
997564080e
88
app.py
88
app.py
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@ -9,67 +9,76 @@ from classes.agent import Agent
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from collections import deque
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import threading
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import time
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import random
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pygame.init()
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window = pygame.display.set_mode((prefs.WIDTH, prefs.HEIGHT))
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pygame.display.set_caption("Game Window")
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table_coords = [(4, 4), (4, prefs.GRID_SIZE-5), (prefs.GRID_SIZE-5, 4), (prefs.GRID_SIZE-5, prefs.GRID_SIZE-5)]
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def initBoard():
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wall_probability = 0.001
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global cells
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cells = []
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for i in range(prefs.GRID_SIZE):
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row = []
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for j in range(prefs.GRID_SIZE):
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cell = Cell(i, j, 1)
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waga = random.choices([1, 4, 5], weights=[0.7, 0.1, 0.1], k=1)[0]
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cell = Cell(i, j, waga)
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if (i, j) not in table_coords:
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if waga == 5:
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cell.prepareTexture("sprites/plama.png")
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if waga == 4:
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cell.prepareTexture("sprites/dywan.png")
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if random.random() < wall_probability:
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cell.prepareTexture("sprites/wall.png")
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cell.blocking_movement = True
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# Wybierz kolor dla płytki na podstawie jej położenia
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if i == 0 or i == prefs.GRID_SIZE - 1 or j == 0 or j == prefs.GRID_SIZE - 1:
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color = (100, 20, 20)
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elif i == 1 or i == prefs.GRID_SIZE - 2 or j == 1 or j == prefs.GRID_SIZE - 2:
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color = (20, 100, 20)
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elif i == 2 or i == prefs.GRID_SIZE - 3 or j == 2 or j == prefs.GRID_SIZE - 3:
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color = (20, 20, 100)
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else:
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color = (150, 200, 200)
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cell.color = color
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row.append(cell)
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cells.append(row)
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# Test
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# Na potrzeby prezentacji tworzę sobie prostokątne ściany na które nie da się wejść
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x1 = 3
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y1 = 6
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for i in range(x1, x1+4):
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for j in range(y1, y1+2):
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cells[i][j].prepareTexture("sprites/wall.png")
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cells[i][j].blocking_movement = True
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# x1 = 3
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# y1 = 6
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# for i in range(x1, x1+4):
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# for j in range(y1, y1+2):
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# cells[i][j].prepareTexture("sprites/wall.png")
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# cells[i][j].blocking_movement = True
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for i in range(prefs.GRID_SIZE):
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for j in range(prefs.GRID_SIZE):
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if i == 0 or j==0 or j==prefs.GRID_SIZE-1 or (i == prefs.GRID_SIZE-1 and j != 17):
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cells[i][j].prepareTexture("sprites/wall.png")
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cells[i][j].blocking_movement = True
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cells[6][4].interactableItem = BeerKeg(cells[6][4], "Beer Keg")
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cells[6][6].interactableItem = BeerKeg(cells[6][6], "Beer Keg")
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cells[4][10].interactableItem = CoffeMachine(cells[4][10], "Coffe Machine")
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cells[9][10].interactableItem = Table(cells[9][10], "Table")
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cells[8][2].interactableItem = Table(cells[8][2], "Table")
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cells[6][2].interactableItem = Table(cells[6][2], "Table")
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cells[4][2].interactableItem = Table(cells[4][2], "Table")
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for cell in cells:
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for cel in cell:
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cel.waga = Agent.get_cost((cel.X, cel.Y), cells)
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cells[4][4].interactableItem = Table(cells[4][4], "Table")
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cells[4][prefs.GRID_SIZE-5].interactableItem = Table(cells[4][prefs.GRID_SIZE-5], "Table")
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cells[prefs.GRID_SIZE-5][4].interactableItem = Table(cells[prefs.GRID_SIZE-5][4], "Table")
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cells[prefs.GRID_SIZE-5][prefs.GRID_SIZE-5].interactableItem = Table(cells[prefs.GRID_SIZE-5][prefs.GRID_SIZE-5], "Table")
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cells[9][9].waga = 2
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cells[9][8].waga = 10
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cells[8][8].waga = 10
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cells[prefs.SPAWN_POINT[0]+1][prefs.SPAWN_POINT[1]].waga = 100
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cells[prefs.SPAWN_POINT[0]][prefs.SPAWN_POINT[1]-1].waga = 100
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cells[9][7].waga = 2
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cells[10][6].waga = 2
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cells[7][7].waga = 2
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# cells[9][9].waga = 2
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# cells[9][8].waga = 10
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# cells[8][8].waga = 10
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# cells[prefs.SPAWN_POINT[0]+1][prefs.SPAWN_POINT[1]].waga = 100
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# cells[prefs.SPAWN_POINT[0]][prefs.SPAWN_POINT[1]-1].waga = 100
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# cells[9][7].waga = 2
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# cells[10][6].waga = 2
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# cells[7][7].waga = 2
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def draw_grid(window, cells, agent):
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for i in range(prefs.GRID_SIZE):
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for j in range(prefs.GRID_SIZE):
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cell = cells[i][j]
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color = cell.color
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pygame.draw.rect(window, cell.color, (i*prefs.CELL_SIZE, j*prefs.CELL_SIZE, prefs.CELL_SIZE, prefs.CELL_SIZE))
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cells[i][j].update(window)
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if(cells[i][j].interactableItem):
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cells[i][j].interactableItem.update(window)
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if(not cells[i][j].blocking_movement):
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@ -84,7 +93,7 @@ def draw_grid(window, cells, agent):
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initBoard()
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agent = Agent(prefs.SPAWN_POINT[0], prefs.SPAWN_POINT[1], cells)
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target_x, target_y = 9, 11
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target_x, target_y = 18, 18
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def watekDlaSciezkiAgenta():
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time.sleep(3)
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@ -137,13 +146,6 @@ while running:
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watek.daemon = True
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watek.start()
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if keys[K_g]:
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path, cost = agent.astar((target_x, target_y), start_cost=0)
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print("Shortest path:", path)
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print("Total cost:", cost)
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watek = threading.Thread(target=watekDlaSciezkiAgenta)
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watek.daemon = True
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watek.start()
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if pygame.key.get_pressed()[pygame.K_e]:
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@ -18,8 +18,8 @@ class Agent:
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self.multiplier = 1
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self.direction = 0
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self.directionPOM = 0
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self.xPOM = 5
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self.yPOM = 5
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self.xPOM = x
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self.yPOM = y
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self.g_scores = {}
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self.textures = [
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@ -270,74 +270,12 @@ class Agent:
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return []
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#Algorytm astar
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def moveto(self,x,y):
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if pygame.time.get_ticks()-self.last_move_time > 125 and self.current_cell.X < prefs.GRID_SIZE-1 and not self.cells[x][y].blocking_movement:
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self.current_cell = self.cells[x][y]
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self.moved=True
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self.last_move_time=pygame.time.get_ticks()
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print("Agent moved to x,y: ",x,y)
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else:
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print("Agent cannot move to this direction")
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def get_cost(cell, cells):
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x, y = cell[0], cell[1]
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if x == 0 or x == len(cells) - 1 or y == 0 or y == len(cells[0]) - 1:
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return 15 # Koszt dla pól na krawędziach
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elif x == 1 or x == len(cells) - 2 or y == 1 or y == len(cells[0]) - 2:
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return 10 # Koszt dla pól drugiego rzędu i przedostatniego oraz drugiej kolumny i przedostatniej
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elif x == 2 or x == len(cells) - 3 or y == 2 or y == len(cells[0]) - 3:
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return 5 # Koszt dla pól trzeciego rzędu i trzeciego od końca oraz trzeciej kolumny i trzeciej od końca
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else:
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return 1
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def heuristic(self, current, target):
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# Manhattan distance heuristic
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dx = abs(current[0] - target[0])
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dy = abs(current[1] - target[1])
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return dx + dy
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def priority(self, state, target):
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# Oblicza priorytet dla danego stanu
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g_score = self.g_score[state]
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h_score = self.heuristic(state, target)
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return g_score + h_score
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def astar(self, target, start_cost=0):
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if not isinstance(target, tuple) or len(target) != 2:
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raise ValueError("Target must be a tuple of two elements (x, y).")
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open_list = [(start_cost, (self.current_cell.X, self.current_cell.Y, self.directionPOM))]
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came_from = {}
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g_score = {(self.current_cell.X, self.current_cell.Y, self.directionPOM): start_cost}
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while open_list:
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_, current = heapq.heappop(open_list)
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if isinstance(current, int):
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raise ValueError("Current must be a tuple of three elements (x, y, direction).")
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x, y, _ = current # Unpack the current tuple
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if (x, y) == target: # Check if the current cell's coordinates match the target
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path = []
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while current in came_from:
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path.append((current[0], current[1])) # Append only coordinates (x, y) to the path
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current = came_from[current]
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path = path[::-1] # Reverse the path
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cost = g_score[(x, y, self.directionPOM)] # Retrieve the cost from the g_score dictionary
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return path, cost
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for neighbor in self.get_neighbors(self.cells[x][y], self.cells):
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neighbor_coords = (neighbor.X, neighbor.Y, self.directionPOM) # Convert neighbor cell to tuple
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tentative_g_score = g_score[current] + self.get_cost(neighbor_coords)
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if tentative_g_score < g_score.get(neighbor_coords, float('inf')):
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came_from[neighbor_coords] = current
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g_score[neighbor_coords] = tentative_g_score
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f_score = tentative_g_score + self.heuristic(neighbor_coords, target)
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heapq.heappush(open_list, (f_score, neighbor_coords))
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return [], float('inf')
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@ -0,0 +1,33 @@
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digraph Tree {
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node [shape=box, style="filled, rounded", color="black", fontname="helvetica"] ;
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edge [fontname="helvetica"] ;
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0 [label=<Tattoo ≤ 1.5<br/>entropy = 1.045<br/>samples = 135<br/>value = [39.0, 1.0, 1.0, 93.0, 1.0]<br/>class = No >, fillcolor="#9190f0"] ;
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1 [label=<Hair ≤ 1.5<br/>entropy = 1.185<br/>samples = 66<br/>value = [28, 0, 1, 36, 1]<br/>class = No >, fillcolor="#d6d5fa"] ;
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0 -> 1 [labeldistance=2.5, labelangle=45, headlabel="True"] ;
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2 [label=<Balding ≤ 1.5<br/>entropy = 0.678<br/>samples = 23<br/>value = [2, 0, 0, 20, 1]<br/>class = No >, fillcolor="#5855e9"] ;
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1 -> 2 ;
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3 [label=<entropy = 0.0<br/>samples = 13<br/>value = [0, 0, 0, 13, 0]<br/>class = No >, fillcolor="#3c39e5"] ;
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2 -> 3 ;
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4 [label=<entropy = 1.157<br/>samples = 10<br/>value = [2, 0, 0, 7, 1]<br/>class = No >, fillcolor="#8583ef"] ;
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2 -> 4 ;
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5 [label=<Wrinkles ≤ 1.5<br/>entropy = 1.096<br/>samples = 43<br/>value = [26, 0, 1, 16, 0]<br/>class = Yes>, fillcolor="#f5d0b6"] ;
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1 -> 5 ;
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6 [label=<entropy = 0.976<br/>samples = 22<br/>value = [9, 0, 0, 13, 0]<br/>class = No >, fillcolor="#c3c2f7"] ;
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5 -> 6 ;
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7 [label=<entropy = 0.857<br/>samples = 21<br/>value = [17, 0, 1, 3, 0]<br/>class = Yes>, fillcolor="#eb9d65"] ;
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5 -> 7 ;
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8 [label=<Balding ≤ 1.5<br/>entropy = 0.739<br/>samples = 69<br/>value = [11.0, 1.0, 0.0, 57.0, 0.0]<br/>class = No >, fillcolor="#6462ea"] ;
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0 -> 8 [labeldistance=2.5, labelangle=-45, headlabel="False"] ;
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9 [label=<Glasses ≤ 1.5<br/>entropy = 0.323<br/>samples = 34<br/>value = [2, 0, 0, 32, 0]<br/>class = No >, fillcolor="#4845e7"] ;
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8 -> 9 ;
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10 [label=<entropy = 0.567<br/>samples = 15<br/>value = [2, 0, 0, 13, 0]<br/>class = No >, fillcolor="#5a57e9"] ;
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9 -> 10 ;
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11 [label=<entropy = 0.0<br/>samples = 19<br/>value = [0, 0, 0, 19, 0]<br/>class = No >, fillcolor="#3c39e5"] ;
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9 -> 11 ;
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12 [label=<Outfit ≤ 1.5<br/>entropy = 0.997<br/>samples = 35<br/>value = [9, 1, 0, 25, 0]<br/>class = No >, fillcolor="#8785ef"] ;
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8 -> 12 ;
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13 [label=<entropy = 1.272<br/>samples = 16<br/>value = [7, 1, 0, 8, 0]<br/>class = No >, fillcolor="#e9e9fc"] ;
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12 -> 13 ;
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14 [label=<entropy = 0.485<br/>samples = 19<br/>value = [2, 0, 0, 17, 0]<br/>class = No >, fillcolor="#5350e8"] ;
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12 -> 14 ;
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}
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@ -72,5 +72,5 @@ print("\nNew client:")
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print(new_client_df)
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print("Prediction:", prediction[0])
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graph = graphviz.Source(dot_data)
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graph.render("decision_tree", format='png')
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#graph = graphviz.Source(dot_data)
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#graph.render("decision_tree", format='png')
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6
prefs.py
6
prefs.py
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@ -1,9 +1,9 @@
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WIDTH = 600
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WIDTH = 1000
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HEIGHT = WIDTH
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GRID_SIZE = 12
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GRID_SIZE = 20
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CELL_SIZE = WIDTH // GRID_SIZE
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SPAWN_POINT = (5, 5)
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COLORS = [(100, 20, 20), (20, 100, 20), (20, 20, 100),(150, 200, 200)]
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COLORS = [(190, 190, 190),(180,180,180)]
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