Compare commits
10 Commits
Author | SHA1 | Date | |
---|---|---|---|
0c5532ac0d | |||
11d091de6a | |||
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a56dad13cf | ||
a04f4692c1 | |||
06e13b8f19 | |||
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9c398488e5 | ||
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47d1380266 | ||
5094ee732c | |||
9eb5029b38 | |||
8cdf6d8118 |
@ -1,4 +1,7 @@
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<?xml version="1.0" encoding="UTF-8"?>
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<project version="4">
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<component name="Black">
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<option name="sdkName" value="Python 3.9 (traktor)" />
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</component>
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<component name="ProjectRootManager" version="2" project-jdk-name="Python 3.9 (traktor)" project-jdk-type="Python SDK" />
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</project>
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BIN
__pycache__/board.cpython-312.pyc
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BIN
__pycache__/board.cpython-312.pyc
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Binary file not shown.
BIN
__pycache__/constant.cpython-312.pyc
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BIN
__pycache__/constant.cpython-312.pyc
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BIN
__pycache__/kolejka.cpython-312.pyc
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BIN
__pycache__/kolejka.cpython-312.pyc
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BIN
__pycache__/tractor.cpython-312.pyc
Normal file
BIN
__pycache__/tractor.cpython-312.pyc
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Binary file not shown.
150
astar.py
Normal file
150
astar.py
Normal file
@ -0,0 +1,150 @@
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import pygame
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from board import Board
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from constant import width, height, rows, cols
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from tractor import Tractor
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import heapq
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fps = 2
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WIN = pygame.display.set_mode((width, height))
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pygame.display.set_caption('Inteligenty Traktor')
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class Node:
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def __init__(self, state, parent=None, action=None, cost=0):
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self.state = state # Stan reprezentowany przez węzeł
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self.parent = parent # Węzeł rodzica
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self.action = action # Akcja prowadząca do tego stanu
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self.cost = cost # Koszt przejścia do tego stanu
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self.f = 0 # Wartość funkcji priorytetowej
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self.tie_breaker = 0 # Wartość używana do rozwiązywania konfliktów priorytetów
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def __lt__(self, other):
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# Porównanie węzłów w celu ustalenia kolejności w kolejce priorytetowej
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if self.f == other.f:
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return self.tie_breaker > other.tie_breaker # Większy tie_breaker ma wyższy priorytet
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return self.f < other.f
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# Jesli pare wezlow ma taie same f, to tilebreaker ustawia
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# prorytety akcje right i down maja wyzszy priorytet
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def manhattan(pos0, pos1):
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# Heurystyka odległości Manhattan
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d1 = abs(pos1[0] - pos0[0])
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d2 = abs(pos1[1] - pos0[1])
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return d1 + d2
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def nastepnik(state, board):
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# Funkcja generująca możliwe następne stany (akcje)
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x, y = state
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successors = []
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actions = [('right', (x+1, y), 1), ('down', (x, y+1), 1), ('up', (x, y-1), 0), ('left', (x-1, y), 0)]
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for action, next_state, tie_breaker in actions:
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if 0 <= next_state[0] < cols and 0 <= next_state[1] < rows:
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cost = board.get_cost(next_state[0], next_state[1])
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successors.append((action, next_state, cost, tie_breaker))
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return successors
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def goal_test(state, goal):
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# Czy dany stan jest stanem docelowym
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return state == goal
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def graphsearch(istate, goal, board, heuristic=manhattan):
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# Algorytm przeszukiwania grafu
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fringe = [] # Kolejka priorytetowa przechowująca węzły do odwiedzenia
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explored = set() # Zbiór odwiedzonych stanów
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start_node = Node(istate)
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start_node.f = heuristic(istate, goal) # Obliczenie wartości heurystycznej dla stanu początkowego
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start_node.tie_breaker = 0 # Ustawienie tie_breaker dla węzła startowego,
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heapq.heappush(fringe, start_node)
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while fringe:
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elem = heapq.heappop(fringe)
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if goal_test(elem.state, goal):
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path = []
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total_cost = elem.cost # Zapisanie całkowitego kosztu
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while elem:
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path.append((elem.state, elem.action))
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elem = elem.parent
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return path[::-1], total_cost # Zwrócenie ścieżki i kosztu
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explored.add(elem.state)
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for action_index, (action, state, cost, tie_breaker) in enumerate(nastepnik(elem.state, board)):
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x = Node(state, parent=elem, action=action, cost=elem.cost + cost)
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x.f = x.cost + heuristic(state, goal) # Obliczenie wartości funkcji priorytetowej
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x.tie_breaker = elem.tie_breaker * 4 + action_index # Obliczanie tie_breaker na podstawie akcji
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if state not in explored and not any(node.state == state for node in fringe):
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heapq.heappush(fringe, x)
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else:
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for i, node in enumerate(fringe):
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if node.state == state and (node.f > x.f or (node.f == x.f and node.tie_breaker < x.tie_breaker)):
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fringe[i] = x
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heapq.heapify(fringe)
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break
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print("Nie znaleziono ścieżki.")
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return None, 0 # Zwrócenie ścieżki jako None i kosztu jako 0 w przypadku braku ścieżki
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def main():
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run = True
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clock = pygame.time.Clock()
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board = Board()
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board.load_images()
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start_state = (9, 9) # Stan początkowy
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goal_state = (0, 0) # Stan docelowy
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tractor = Tractor(start_state[1], start_state[0])
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board.set_grass(start_state[0], start_state[1]) # Ustawienie startowego pola jako trawę
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board.set_grass(goal_state[0], goal_state[1]) # Ustawienie docelowego pola jako trawę
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path, total_cost = graphsearch(start_state, goal_state, board)
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while run:
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clock.tick(fps)
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for event in pygame.event.get():
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if event.type == pygame.QUIT:
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run = False
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if not path:
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run = False
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continue
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next_state, action = path.pop(0) if path else (start_state, None)
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print(next_state) # Wypisanie następnego stanu
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tractor.row, tractor.col = next_state[1], next_state[0]
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if action == "right":
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tractor.direction = "right"
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elif action == "left":
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tractor.direction = "left"
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elif action == "down":
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tractor.direction = "down"
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elif action == "up":
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tractor.direction = "up"
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# Aktualizacja planszy na podstawie położenia traktora
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if board.is_weed(tractor.col, tractor.row):
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board.set_grass(tractor.col, tractor.row)
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elif board.is_dirt(tractor.col, tractor.row):
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board.set_soil(tractor.col, tractor.row)
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elif board.is_soil(tractor.col, tractor.row):
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board.set_carrot(tractor.col, tractor.row)
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board.draw_cubes(WIN)
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tractor.draw(WIN)
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pygame.display.update()
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print(f"Całkowity koszt trasy: {total_cost}")
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while True:
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for event in pygame.event.get():
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if event.type == pygame.QUIT:
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pygame.quit()
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return
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main()
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43
board.py
43
board.py
@ -1,13 +1,14 @@
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import pygame
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from constant import size, rows, cols
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import random
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from tractor import Tractor
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class Board:
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def __init__(self):
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self.board = []
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self.load_images()
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self.generate_board()
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self.load_costs()
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def load_images(self):
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@ -16,6 +17,7 @@ class Board:
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self.rock= pygame.image.load("board/rock.png")
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self.weeds = pygame.image.load("board/weeds.png")
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self.soil = pygame.image.load("board/zyzna.png")
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self.carrot = pygame.image.load("board/carrot.png")
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def generate_board(self):
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self.board = [[random.choice([0,1,2,3,4,5,6,7,8,9]) for _ in range(rows)] for _ in range(cols)]
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@ -41,11 +43,38 @@ class Board:
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win.blit(self.grass, cube_rect)
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elif cube == 10:
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win.blit(self.soil, cube_rect)
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elif cube == 11:
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carrot_scale = pygame.transform.scale(self.carrot, (size,size))
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win.blit(self.carrot, cube_rect)
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win.blit(carrot_scale, cube_rect)
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else:
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win.blit(self.dirt, cube_rect)
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def load_costs(self):
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self.costs = {
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0: 100, #kamien
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1:2, #chwast
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2: 1, #po trawie
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3: 1, #po trawie
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4: 1, #po trawie
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5: 1, #po trawie
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6: 3, #ziemia
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7: 3, #ziemia
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8: 3, #ziemia
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9: 3, #ziemia
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10: 4, #zyzna
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11: 10 #marchewka
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}
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def get_cost(self, row, col):
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tile_type = self.board[row][col]
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return self.costs.get(tile_type, 1)
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def is_rock(self, row, col):
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return self.board[row][col] == 0
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tractor = Tractor(row, col)
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return self.board[row][col] == 0 and not (row == tractor.row and col == tractor.col)
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def is_weed(self,row,col):
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return self.board[row][col] == 1
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@ -55,6 +84,12 @@ class Board:
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def is_dirt(self,row,col):
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return self.board[row][col] in (6,7,8,9)
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def is_soil(self, row, col):
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return self.board[row][col] == 10
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def set_soil(self, row, col):
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self.board[row][col] = 10
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self.board[row][col] = 10
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def set_carrot(self, row, col):
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self.board[row][col] = 11
|
BIN
board/carrot.png
Normal file
BIN
board/carrot.png
Normal file
Binary file not shown.
After Width: | Height: | Size: 232 KiB |
@ -1,6 +1,6 @@
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||||
import pygame
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||||
width, height = 640, 640
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||||
rows, cols = 8, 8
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rows, cols = 10, 10
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||||
size = width//cols
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||||
yellow = (216,178,0)
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||||
green= (103,178,0)
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||||
|
206
dane.csv
Normal file
206
dane.csv
Normal file
@ -0,0 +1,206 @@
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wilgotnosc_gleby,temperatura_gleby,opady_deszczu,wiek_rosliny,proc_ekspo_na_swiatlo,pora_dnia,pora_roku,roslina,podlac
|
||||
40, 20, 5, 3, 70, 10, 2, 1, nie
|
||||
60, 25, 0, 2, 50, 15, 3, 2, tak
|
||||
30, 18, 10, 1, 80, 12, 4, 3, nie
|
||||
50, 22, 3, 4, 60, 18, 1, 4, tak
|
||||
45, 23, 2, 5, 75, 8, 2, 5, tak
|
||||
55, 26, 8, 3, 70, 14, 3, 6, nie
|
||||
35, 21, 1, 2, 55, 16, 4, 7, tak
|
||||
65, 24, 6, 4, 80, 11, 1, 8, nie
|
||||
42, 20, 4, 3, 65, 13, 2, 9, tak
|
||||
48, 22, 7, 5, 75, 9, 3, 10, tak
|
||||
30, 25, 0, 1, 70, 14, 2, 1, tak
|
||||
60, 18, 10, 2, 60, 8, 3, 2, nie
|
||||
35, 20, 2, 3, 50, 12, 4, 3, tak
|
||||
50, 23, 1, 4, 65, 17, 1, 4, tak
|
||||
45, 24, 5, 5, 80, 10, 2, 5, tak
|
||||
55, 22, 3, 3, 75, 13, 3, 6, nie
|
||||
40, 26, 8, 6, 70, 16, 1, 7, nie
|
||||
62, 21, 1, 4, 85, 9, 2, 8, tak
|
||||
47, 25, 6, 5, 60, 11, 3, 9, nie
|
||||
58, 20, 4, 3, 75, 14, 4, 10, tak
|
||||
38, 24, 7, 3, 65, 11, 1, 1, tak
|
||||
59, 20, 3, 2, 55, 16, 2, 2, nie
|
||||
33, 22, 5, 1, 70, 9, 3, 3, nie
|
||||
52, 25, 2, 4, 80, 14, 4, 4, tak
|
||||
46, 21, 1, 5, 75, 10, 1, 5, tak
|
||||
56, 26, 8, 3, 70, 15, 2, 6, nie
|
||||
34, 23, 0, 2, 60, 8, 3, 7, nie
|
||||
63, 18, 4, 4, 85, 12, 4, 8, nie
|
||||
41, 20, 1, 3, 65, 13, 1, 9, tak
|
||||
49, 22, 9, 5, 75, 17, 2, 10, tak
|
||||
29, 25, 0, 2, 70, 14, 3, 1, tak
|
||||
61, 18, 11, 3, 60, 8, 1, 2, nie
|
||||
37, 20, 2, 4, 50, 12, 2, 3, tak
|
||||
51, 23, 0, 5, 65, 16, 4, 4, tak
|
||||
44, 24, 4, 6, 80, 10, 3, 5, tak
|
||||
54, 22, 3, 3, 75, 13, 1, 6, nie
|
||||
39, 26, 7, 1, 70, 15, 2, 7, nie
|
||||
64, 21, 0, 4, 85, 9, 3, 8, tak
|
||||
48, 25, 5, 5, 60, 11, 4, 9, nie
|
||||
57, 20, 2, 3, 75, 14, 1, 10, tak
|
||||
32, 24, 8, 3, 65, 10, 2, 1, tak
|
||||
62, 19, 2, 2, 55, 15, 3, 2, nie
|
||||
36, 21, 1, 1, 70, 12, 4, 3, nie
|
||||
53, 22, 4, 4, 80, 16, 1, 4, tak
|
||||
42, 23, 2, 5, 75, 8, 2, 5, tak
|
||||
58, 26, 6, 3, 70, 14, 3, 6, nie
|
||||
35, 21, 0, 2, 60, 17, 4, 7, nie
|
||||
65, 18, 3, 4, 85, 11, 1, 8, nie
|
||||
45, 20, 1, 3, 65, 13, 2, 9, tak
|
||||
50, 22, 7, 5, 75, 9, 3, 10, tak
|
||||
31, 25, 0, 2, 70, 14, 1, 1, tak
|
||||
60, 18, 9, 3, 60, 8, 2, 2, nie
|
||||
34, 20, 3, 4, 50, 12, 3, 3, tak
|
||||
52, 23, 1, 5, 65, 16, 4, 4, tak
|
||||
47, 24, 6, 6, 80, 10, 1, 5, tak
|
||||
55, 22, 2, 3, 75, 13, 2, 6, nie
|
||||
38, 26, 8, 1, 70, 15, 3, 7, nie
|
||||
64, 21, 0, 4, 85, 9, 4, 8, tak
|
||||
41, 20, 2, 3, 65, 13, 1, 9, tak
|
||||
49, 22, 8, 5, 75, 17, 2, 10, tak
|
||||
30, 24, 1, 2, 70, 14, 3, 1, tak
|
||||
61, 18, 10, 3, 60, 8, 1, 2, nie
|
||||
37, 20, 4, 4, 50, 12, 2, 3, tak
|
||||
51, 23, 2, 5, 65, 16, 4, 4, tak
|
||||
44, 24, 5, 6, 80, 10, 3, 5, tak
|
||||
53, 22, 3, 3, 75, 13, 1, 6, nie
|
||||
39, 26, 7, 1, 70, 15, 2, 7, nie
|
||||
65, 21, 0, 4, 85, 9, 3, 8, tak
|
||||
48, 25, 6, 5, 60, 11, 4, 9, nie
|
||||
57, 20, 3, 3, 75, 14, 1, 10, tak
|
||||
32, 24, 9, 2, 65, 10, 2, 1, tak
|
||||
62, 19, 1, 2, 55, 15, 3, 2, nie
|
||||
36, 21, 2, 1, 70, 12, 4, 3, nie
|
||||
55, 23, 3, 4, 80, 16, 1, 4, tak
|
||||
42, 23, 1, 5, 75, 8, 2, 5, tak
|
||||
58, 26, 5, 3, 70, 14, 3, 6, nie
|
||||
35, 21, 0, 2, 60, 17, 4, 7, nie
|
||||
46, 20, 2, 3, 65, 13, 2, 9, tak
|
||||
50, 22, 6, 5, 75, 9, 3, 10, tak
|
||||
31, 25, 1, 2, 70, 14, 1, 1, tak
|
||||
60, 18, 8, 3, 60, 8, 2, 2, nie
|
||||
33, 20, 4, 4, 50, 12, 3, 3, tak
|
||||
52, 23, 1, 5, 65, 16, 4, 4, tak
|
||||
47, 24, 7, 6, 80, 10, 1, 5, tak
|
||||
38, 25, 2, 3, 65, 10, 1, 1, tak
|
||||
59, 21, 1, 2, 55, 15, 2, 2, nie
|
||||
33, 23, 3, 1, 70, 9, 3, 3, nie
|
||||
47, 22, 7, 4, 75, 11, 2, 1, tak
|
||||
58, 20, 4, 3, 60, 16, 1, 2, nie
|
||||
32, 24, 6, 2, 70, 8, 3, 3, nie
|
||||
53, 23, 3, 5, 80, 15, 4, 4, tak
|
||||
45, 21, 8, 6, 75, 12, 1, 5, tak
|
||||
55, 26, 11, 4, 70, 17, 2, 6, nie
|
||||
36, 24, 5, 3, 60, 9, 3, 7, nie
|
||||
67, 19, 10, 4, 85, 13, 4, 8, nie
|
||||
43, 22, 1, 3, 65, 14, 1, 9, tak
|
||||
51, 24, 9, 5, 75, 10, 2, 10, tak
|
||||
31, 27, 2, 2, 70, 15, 3, 1, tak
|
||||
62, 18, 12, 3, 60, 8, 1, 2, nie
|
||||
38, 21, 6, 4, 50, 11, 2, 3, tak
|
||||
49, 24, 4, 5, 65, 16, 4, 4, tak
|
||||
42, 25, 7, 3, 80, 9, 3, 5, tak
|
||||
57, 23, 4, 3, 75, 12, 1, 6, nie
|
||||
35, 28, 9, 1, 70, 16, 2, 7, nie
|
||||
76, 20, 11, 4, 85, 10, 3, 8, nie
|
||||
46, 22, 0, 3, 65, 13, 1, 9, tak
|
||||
10, 25, 10, 5, 95, 9, 2, 10, tak
|
||||
38, 19, 3, 6, 80, 11, 2, 1, tak
|
||||
57, 24, 2, 7, 90, 15, 1, 2, tak
|
||||
81, 18, 9, 8, 70, 12, 4, 3, nie
|
||||
49, 22, 2, 9, 85, 18, 3, 4, tak
|
||||
44, 23, 1, 3, 60, 8, 2, 5, nie
|
||||
24, 26, 5, 2, 75, 14, 3, 6, tak
|
||||
76, 13, 0, 4, 25, 19, 4, 7, nie
|
||||
67, 15, 5, 2, 80, 11, 1, 8, nie
|
||||
43, 20, 1, 1, 65, 13, 2, 9, tak
|
||||
50, 22, 8, 1, 20, 19, 3, 10, nie
|
||||
62, 25, 0, 2, 75, 14, 2, 1, tak
|
||||
58, 18, 11, 3, 30, 8, 3, 2, nie
|
||||
37, 20, 2, 2, 50, 12, 4, 3, tak
|
||||
21, 23, 0, 1, 65, 20, 1, 4, tak
|
||||
46, 24, 2, 2, 75, 12, 2, 5, tak
|
||||
76, 22, 6, 2, 70, 13, 3, 6, nie
|
||||
39, 26, 9, 2, 15, 16, 1, 7, nie
|
||||
53, 21, 2, 3, 80, 12, 2, 8, tak
|
||||
48, 25, 7, 4, 10, 11, 3, 9, nie
|
||||
88, 19, 3, 6, 30, 11, 2, 1, nie
|
||||
57, 24, 4, 7, 10, 15, 1, 2, nie
|
||||
11, 18, 9, 8, 90, 12, 4, 3, tak
|
||||
49, 22, 2, 9, 85, 18, 3, 4, tak
|
||||
44, 23, 1, 1, 60, 8, 2, 5, tak
|
||||
54, 26, 7, 2, 75, 14, 3, 6, nie
|
||||
36, 21, 0, 2, 55, 16, 4, 7, tak
|
||||
27, 24, 2, 3, 80, 11, 1, 8, tak
|
||||
13, 20, 6, 4, 95, 10, 2, 9, tak
|
||||
50, 22, 8, 5, 20, 17, 3, 10, nie
|
||||
32, 25, 1, 6, 95, 14, 2, 1, tak
|
||||
58, 18, 11, 3, 80, 8, 3, 2, nie
|
||||
37, 20, 2, 1, 50, 12, 4, 3, tak
|
||||
51, 23, 5, 2, 25, 22, 1, 4, nie
|
||||
46, 24, 0, 2, 75, 10, 2, 5, tak
|
||||
56, 22, 1, 3, 70, 13, 3, 6, tak
|
||||
39, 26, 9, 4, 35, 20, 1, 7, nie
|
||||
63, 21, 2, 3, 90, 9, 2, 8, tak
|
||||
48, 25, 7, 1, 70, 11, 3, 9, nie
|
||||
42, 24, 1, 5, 75, 14, 2, 1, tak
|
||||
55, 20, 1, 8, 65, 13, 1, 2, tak
|
||||
58, 22, 6, 4, 10, 12, 3, 3, nie
|
||||
47, 21, 2, 2, 70, 9, 4, 4, tak
|
||||
50, 25, 1, 1, 85, 15, 1, 5, nie
|
||||
60, 23, 7, 7, 70, 11, 2, 6, nie
|
||||
83, 19, 4, 3, 60, 13, 3, 7, nie
|
||||
68, 26, 8, 5, 90, 16, 4, 8, nie
|
||||
41, 18, 9, 1, 75, 14, 2, 9, nie
|
||||
48, 20, 0, 8, 70, 8, 1, 10, tak
|
||||
89, 23, 2, 6, 55, 12, 3, 1, nie
|
||||
59, 21, 2, 7, 80, 10, 4, 2, tak
|
||||
97, 24, 3, 5, 65, 9, 1, 3, nie
|
||||
49, 22, 2, 9, 75, 15, 2, 4, tak
|
||||
92, 26, 1, 1, 85, 11, 3, 5, nie
|
||||
21, 18, 4, 8, 70, 13, 4, 6, tak
|
||||
34, 25, 9, 4, 60, 16, 1, 7, nie
|
||||
70, 19, 8, 5, 90, 14, 2, 8, nie
|
||||
45, 20, 2, 2, 80, 12, 3, 9, tak
|
||||
53, 24, 7, 7, 75, 10, 1, 10, nie
|
||||
43, 21, 3, 6, 70, 11, 2, 1, tak
|
||||
56, 22, 8, 8, 80, 13, 3, 2, nie
|
||||
39, 19, 5, 7, 65, 9, 4, 3, nie
|
||||
48, 23, 1, 9, 75, 14, 1, 4, tak
|
||||
51, 25, 6, 1, 85, 12, 2, 5, nie
|
||||
62, 24, 4, 2, 90, 15, 3, 6, nie
|
||||
35, 20, 2, 2, 60, 10, 4, 7, tak
|
||||
69, 26, 7, 3, 85, 16, 1, 8, nie
|
||||
40, 18, 9, 1, 70, 12, 2, 9, nie
|
||||
49, 22, 0, 5, 75, 11, 3, 10, tak
|
||||
54, 21, 3, 7, 80, 14, 4, 1, tak
|
||||
63, 23, 8, 8, 90, 12, 1, 2, nie
|
||||
36, 20, 2, 9, 65, 10, 2, 3, tak
|
||||
47, 24, 1, 1, 75, 13, 3, 4, tak
|
||||
50, 26, 5, 2, 85, 15, 4, 5, nie
|
||||
34, 25, 2, 2, 90, 9, 1, 6, tak
|
||||
47, 19, 6, 3, 60, 11, 2, 7, nie
|
||||
70, 25, 9, 2, 85, 17, 3, 8, nie
|
||||
41, 21, 7, 1, 70, 13, 4, 9, nie
|
||||
52, 20, 1, 1, 75, 10, 1, 10, tak
|
||||
38, 22, 3, 6, 70, 12, 2, 1, tak
|
||||
87, 23, 9, 7, 80, 14, 3, 2, nie
|
||||
61, 20, 5, 2, 65, 10, 4, 3, nie
|
||||
49, 21, 0, 9, 75, 11, 1, 4, tak
|
||||
44, 25, 6, 1, 80, 15, 2, 5, nie
|
||||
54, 19, 2, 1, 90, 13, 3, 6, tak
|
||||
36, 24, 8, 1, 60, 9, 4, 7, nie
|
||||
67, 20, 3, 2, 85, 16, 1, 8, nie
|
||||
43, 22, 7, 4, 75, 12, 2, 9, nie
|
||||
50, 23, 1, 5, 80, 10, 3, 10, tak
|
||||
55, 21, 4, 7, 70, 13, 4, 1, nie
|
||||
63, 25, 9, 8, 90, 14, 1, 2, nie
|
||||
57, 19, 5, 9, 65, 11, 2, 3, nie
|
||||
49, 24, 0, 1, 75, 16, 3, 4, tak
|
||||
51, 20, 6, 1, 85, 12, 4, 5, nie
|
||||
64, 22, 4, 2, 90, 9, 1, 6, nie
|
||||
39, 23, 8, 3, 60, 14, 2, 7, tak
|
||||
70, 21, 2, 1, 85, 13, 3, 8, nie
|
||||
41, 25, 7, 5, 70, 15, 4, 9, nie
|
||||
52, 19, 1, 2, 75, 10, 1, 10, tak
|
|
44
decisiontree.py
Normal file
44
decisiontree.py
Normal file
@ -0,0 +1,44 @@
|
||||
from sklearn.model_selection import train_test_split
|
||||
from sklearn.tree import DecisionTreeClassifier, plot_tree
|
||||
import matplotlib.pyplot as plt
|
||||
import pandas as pd
|
||||
|
||||
|
||||
data = pd.read_csv("dane.csv")
|
||||
print(data)
|
||||
|
||||
# Wczytanie danych
|
||||
X = data.drop(columns=["podlac"])
|
||||
X = pd.get_dummies(X)
|
||||
y = data["podlac"]
|
||||
|
||||
# Podział danych na zbiór treningowy i testowy
|
||||
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)
|
||||
|
||||
# Inicjalizacja i dopasowanie modelu drzewa decyzyjnego
|
||||
model = DecisionTreeClassifier(max_depth=4)
|
||||
model.fit(X_train, y_train)
|
||||
|
||||
# Wyliczenie poprawności algorytmu
|
||||
accuracy = model.score(X_test, y_test)
|
||||
print("Accuracy:", accuracy)
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
# Wyświetlenie drzewa decyzyjnego
|
||||
plt.figure(figsize=(20, 20))
|
||||
plot_tree(model, feature_names=X.columns, class_names=sorted(y.unique()), filled=True)
|
||||
plt.show()
|
||||
|
||||
#Marchew = 1
|
||||
#zmiemniaki = 2
|
||||
#pomidor = 3
|
||||
#salata = 4
|
||||
#cebula = 5
|
||||
#Papryka = 6
|
||||
#Buraki = 7
|
||||
#Bruksela = 8
|
||||
#Rzepak = 9
|
||||
#Szpinak = 10
|
22
main.py
22
main.py
@ -5,8 +5,6 @@ from tractor import Tractor
|
||||
from kolejka import Stan, Kolejka, Odwiedzone
|
||||
|
||||
|
||||
|
||||
|
||||
fps = 5
|
||||
WIN = pygame.display.set_mode((width, height))
|
||||
|
||||
@ -24,8 +22,8 @@ def actions(elem, istate):
|
||||
while((elem.row != istate.row) or (elem.col != istate.col) or (elem.direction != istate.direction)):
|
||||
akcje.append(elem.a)
|
||||
elem = elem.p[0]
|
||||
|
||||
return akcje
|
||||
|
||||
def graphsearch(istate, goaltest, board):
|
||||
explored = Odwiedzone()
|
||||
fringe = Kolejka()
|
||||
@ -46,14 +44,14 @@ def graphsearch(istate, goaltest, board):
|
||||
def main():
|
||||
rotation = ["left", "up", "right", "down"]
|
||||
istate = Stan(4,4, "down")
|
||||
goaltest = Stan(1,1, "up")
|
||||
goaltest = Stan(2,3, "up")
|
||||
run = True
|
||||
clock = pygame.time.Clock()
|
||||
board = Board()
|
||||
board.load_images()
|
||||
actions = graphsearch(istate, goaltest, board)
|
||||
print("akcje: >",actions )
|
||||
tractor = Tractor(4, 4)
|
||||
tractor = Tractor(2, 3)
|
||||
while run:
|
||||
clock.tick(fps)
|
||||
|
||||
@ -64,6 +62,7 @@ def main():
|
||||
keys = pygame.key.get_pressed()
|
||||
|
||||
if keys[pygame.K_UP]:
|
||||
if keys[pygame.K_UP]:
|
||||
if(tractor.direction == "up" and tractor.row > 0 ):
|
||||
if board.is_weed(tractor.col, tractor.row - 1):
|
||||
board.set_grass(tractor.col, tractor.row - 1)
|
||||
@ -71,8 +70,12 @@ def main():
|
||||
elif board.is_dirt(tractor.col, tractor.row - 1):
|
||||
board.set_soil(tractor.col, tractor.row - 1)
|
||||
tractor.row -= 1
|
||||
elif board.is_soil(tractor.col, tractor.row - 1):
|
||||
board.set_carrot(tractor.col, tractor.row - 1)
|
||||
tractor.row -= 1
|
||||
elif not board.is_rock(tractor.col, tractor.row - 1):
|
||||
tractor.row -= 1
|
||||
|
||||
if(tractor.direction == "left" and tractor.col > 0):
|
||||
if board.is_weed(tractor.col - 1, tractor.row):
|
||||
board.set_grass(tractor.col - 1, tractor.row)
|
||||
@ -80,6 +83,9 @@ def main():
|
||||
elif board.is_dirt(tractor.col - 1, tractor.row):
|
||||
board.set_soil(tractor.col - 1, tractor.row)
|
||||
tractor.col -= 1
|
||||
elif board.is_soil(tractor.col - 1, tractor.row):
|
||||
board.set_carrot(tractor.col - 1, tractor.row)
|
||||
tractor.col -= 1
|
||||
elif not board.is_rock(tractor.col - 1, tractor.row):
|
||||
tractor.col -= 1
|
||||
if(tractor.direction == "down" and tractor.row < rows - 1):
|
||||
@ -89,6 +95,9 @@ def main():
|
||||
elif board.is_dirt(tractor.col, tractor.row + 1):
|
||||
board.set_soil(tractor.col, tractor.row + 1)
|
||||
tractor.row += 1
|
||||
elif board.is_soil(tractor.col, tractor.row + 1):
|
||||
board.set_carrot(tractor.col, tractor.row + 1)
|
||||
tractor.row += 1
|
||||
elif not board.is_rock(tractor.col, tractor.row + 1):
|
||||
tractor.row += 1
|
||||
if(tractor.direction == "right" and tractor.col < cols - 1):
|
||||
@ -98,6 +107,9 @@ def main():
|
||||
elif board.is_dirt(tractor.col + 1, tractor.row):
|
||||
board.set_soil(tractor.col + 1, tractor.row)
|
||||
tractor.col += 1
|
||||
elif board.is_soil(tractor.col + 1, tractor.row ):
|
||||
board.set_carrot(tractor.col + 1, tractor.row )
|
||||
tractor.col += 1
|
||||
elif not board.is_rock(tractor.col + 1, tractor.row):
|
||||
tractor.col += 1
|
||||
if keys[pygame.K_LEFT]:
|
||||
|
Loading…
Reference in New Issue
Block a user