astar na następnikach
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.vscode/settings.json
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.vscode/settings.json
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{
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"python.analysis.extraPaths": [
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"./path_alghoritms",
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"./path_algorithms"
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]
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}
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__pycache__/astar.cpython-310.pyc
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__pycache__/astar.cpython-310.pyc
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__pycache__/node.cpython-310.pyc
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__pycache__/node.cpython-310.pyc
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astar.py
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astar.py
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from config import *
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import heapq
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class Astar():
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def __init__(self,game):
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self.g = game
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# Define the movement directions (up, down, left, right)
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self.directions = [(-1, 0), (1, 0), (0, -1), (0, 1)]
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def heuristic(self,a, b):
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# Calculate the Manhattan distance between two points
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return abs(b[0] - a[0]) + abs(b[1] - a[1])
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def get_successors(self,position):
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# Get the neighboring cells that can be traversed
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successors = []
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for direction in self.directions:
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neighbor = (position[0] + direction[0], position[1] + direction[1])
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if 0 <= neighbor[0] < TILE_SIZE and 0 <= neighbor[1] < TILE_SIZE and self.g.obstacles[neighbor[0]][neighbor[1]] == False:
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successors.append(neighbor)
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return successors
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def print_path(self,came_from, current,path):
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# Recursively print the path from the start to the current position
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if current in came_from:
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path = self.print_path(came_from, came_from[current],path)
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path.append(self.g.bfs.get_cell_number(current[0]*TILE_SIZE,current[1]*TILE_SIZE))
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print("Budowanie ścieżki: ",path)
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return path
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def a_star(self,start, goal,path):
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open_set = []
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heapq.heappush(open_set, (0, start)) # Priority queue with the start position
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came_from = {}
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g_scores = {start: 0} # Cost from start to each position
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f_scores = {start: self.heuristic(start, goal)} # Total estimated cost from start to goal through each position
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while open_set:
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_, current = heapq.heappop(open_set)
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if current == goal:
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# Goal reached, print the path
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path = self.print_path(came_from, goal,path)
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return path
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for successor in self.get_successors(current):
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# Calculate the cost to move from the current position to the successor
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cost = self.g.cell_costs[successor[0]][successor[1]]
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tentative_g_score = g_scores[current] + cost
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if successor not in g_scores or tentative_g_score < g_scores[successor]:
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# Update the cost and priority if it's a better path
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came_from[successor] = current
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g_scores[successor] = tentative_g_score
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f_scores[successor] = tentative_g_score + self.heuristic(successor, goal)
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heapq.heappush(open_set, (f_scores[successor], successor))
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# No path found
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print("No path found.")
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26
bfs.py
26
bfs.py
@ -41,7 +41,7 @@ class Bfs():
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def get_cell_number(self,x, y): #zamienia koordynaty na numer kratki
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cell_number = None
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cell_number =(x // TILE_SIZE) + (NUM_ROWS * (( y// TILE_SIZE)))
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cell_number =(x // TILE_SIZE) + (ROWS * (( y// TILE_SIZE)))
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return cell_number
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def get_possible_moves(self,cell_number):
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@ -66,28 +66,28 @@ class Bfs():
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def get_up_cell(self,cell_number):
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cell_row_number = cell_number // NUM_ROWS
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cell_row_number = cell_number // ROWS
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if (cell_row_number - 1 < 0):
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return None
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else:
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return (cell_number - NUM_ROWS)
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return (cell_number - ROWS)
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def get_right_cell(self,cell_number):
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cell_column_number = cell_number % NUM_ROWS
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if (cell_column_number + 1 >= NUM_ROWS):
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cell_column_number = cell_number % ROWS
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if (cell_column_number + 1 >= ROWS):
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return None
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else:
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return (cell_number + 1)
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def get_down_cell(self,cell_number):
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cell_row_number = cell_number // NUM_ROWS
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if (cell_row_number + 1 >= NUM_ROWS):
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cell_row_number = cell_number // ROWS
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if (cell_row_number + 1 >= ROWS):
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return None
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else:
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return (cell_number + NUM_ROWS)
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return (cell_number + ROWS)
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def get_left_cell(self,cell_number):
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cell_column_number = cell_number % NUM_ROWS
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cell_column_number = cell_number % ROWS
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if (cell_column_number - 1 < 0):
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return None
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else:
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@ -103,17 +103,17 @@ class Bfs():
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if(from_cell - 1 == to_cell):
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return True
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if(from_cell - NUM_ROWS == to_cell):
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if(from_cell - ROWS == to_cell):
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return True
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if(from_cell + NUM_ROWS == to_cell):
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if(from_cell + ROWS == to_cell):
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return True
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return False
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def get_coordinates(self,cell_to_move): #zamienia numer kratki na koordynaty
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cell_row_number = cell_to_move // NUM_ROWS
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cell_column_number = cell_to_move % NUM_ROWS
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cell_row_number = cell_to_move // ROWS
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cell_column_number = cell_to_move % ROWS
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y = cell_row_number * TILE_SIZE
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x = cell_column_number * TILE_SIZE
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@ -3,7 +3,8 @@ WIDTH, HEIGHT = 832, 832
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TILE_SIZE = 64
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BLACK = ((0,0,0))
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WHITE = ((255,255,255))
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NUM_ROWS = WIDTH//TILE_SIZE
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AGENT_LAYER = 2
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FLOWER_LAYER = 1
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GRASS_LAYER = 3
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ROWS = HEIGHT // TILE_SIZE
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COLS = WIDTH // TILE_SIZE
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144
main.py
144
main.py
@ -1,11 +1,13 @@
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import pygame
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from config import *
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from agent import *
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from map_add_ons import *
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from mobs import *
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from bfs import *
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from heapq import *
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from nn import *
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from astar import *
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class Game:
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@ -26,6 +28,12 @@ class Game:
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self.bfs = Bfs(self)
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self.nn = NeuralN()
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self.astar = Astar(self)
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self.cell_costs = [[1 for _ in range(TILE_SIZE)] for _ in range(TILE_SIZE)]
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self.obstacles = [[False for _ in range(TILE_SIZE)] for _ in range(TILE_SIZE)]
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def new(self): # tworzy się nowa sesja grania
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@ -42,23 +50,25 @@ class Game:
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self.agent = Agent(self,1,1)
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self.archer_ork = Archer_ork(self,10,10)
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self.obstacles[10][10] = True
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self.bfs.enemy_cells.append(self.bfs.get_cell_number(self.archer_ork.x,self.archer_ork.y))
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self.infantry_ork = Infantry_ork(self,10,4)
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self.obstacles[10][4] = True
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self.bfs.enemy_cells.append(self.bfs.get_cell_number(self.infantry_ork.x,self.infantry_ork.y))
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self.sauron = Sauron(self, 1, 10)
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self.obstacles[1][10] = True
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self.bfs.enemy_cells.append(self.bfs.get_cell_number(self.sauron.x,self.sauron.y))
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self.flower = Health_flower(self, 8,2)
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self.grass = Grass(self,0,2)
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self.grass = Grass(self,1,2)
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self.grass = Grass(self,0,3)
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self.grass = Grass(self,1,3)
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self.grass = Grass(self,0,4)
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self.grass = Grass(self,1,4)
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cost_cell_1000=[13,26,27,40]
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for y in range (2,5):
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for x in range (2):
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self.grass = Grass(self,x,y)
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self.cell_costs[x][y] = 5
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for y in range(5):
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self.rock = Rocks(self,3,y)
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self.obstacles[3][y] = True
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self.bfs.wall_cells.append(self.bfs.get_cell_number(self.rock.x,self.rock.y))
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@ -71,6 +81,15 @@ class Game:
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if event.type == pygame.QUIT:
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self.running = False
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pygame.quit()
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if event.type == pygame.KEYDOWN:
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if event.key == pygame.K_SPACE:
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self.start_pos = (self.agent.x//TILE_SIZE, self.agent.y//TILE_SIZE)
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self.goal_pos = (self.flower.x//TILE_SIZE, self.flower.y//TILE_SIZE)
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self.path = []
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self.move_agent(self.astar.a_star(self.start_pos, self.goal_pos,self.path))
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if event.type == pygame.MOUSEBUTTONDOWN:
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mouse_presses = pygame.mouse.get_pressed()
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if mouse_presses[0]:
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@ -78,7 +97,7 @@ class Game:
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x = self.sauron.x
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y = self.sauron.y
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mob_image = self.sauron.SAURON_IMG
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while True: #do poprawienia poprawne rozpoznawanie póki co nie będzie działać dobrze
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while True: #do poprawienia poprawne rozpoznawanie póki co nie będzie działać dobrze, program się będzie zawieszać
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prediction = self.prediction_road(x,y,mob_image)
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if prediction == "SAURON":
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x = self.infantry_ork.x
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@ -162,114 +181,9 @@ class Game:
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self.update()
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self.map()
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grass_cells = []
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cols, rows = 13,12
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def get_circle(x,y):
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return (x * TILE_SIZE + TILE_SIZE//2, y* TILE_SIZE + TILE_SIZE//2), TILE_SIZE//4
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def get_rect(x,y):
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return x*TILE_SIZE +1, y* TILE_SIZE +1, TILE_SIZE -2, TILE_SIZE -2
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'''
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def get_next_nodes(x,y):
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check_next_node = lambda x, y:True if 0<= x < cols and 0<=y < rows else False
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ways =[-1,0],[0,-1],[1,0],[0,1]
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return [(grid[y + dy][x + dx], (x + dx, y + dy)) for dx, dy in ways if check_next_node(x + dx, y + dy)]
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'''
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def get_neighbours(x, y):
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check_neighbour = lambda x, y: True if 0 <= x < cols and 0 <= y < rows else False
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ways = [-1, 0], [0, -1], [1, 0], [0, 1]
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return [(grid[y + dy][x + dx], (x + dx, y + dy)) for dx, dy in ways if check_neighbour(x + dx, y + dy)]
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def heuristic(a, b):
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return abs(a[0] - b[0]) + abs(a[1] - b[1])
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def dijkstra(start, goal, graph):
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queue = []
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heappush(queue, (0, start))
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cost_visited = {start: 0}
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visited = {start: None}
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while queue:
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cur_cost, cur_node = heappop(queue)
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if cur_node == goal:
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break
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neighbours = graph[cur_node]
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for neighbour in neighbours:
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neigh_cost, neigh_node = neighbour
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new_cost = cost_visited[cur_node] + neigh_cost
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if neigh_node not in cost_visited or new_cost < cost_visited[neigh_node]:
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priority = new_cost + heuristic(neigh_node, goal)
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heappush(queue, (priority, neigh_node))
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cost_visited[neigh_node] = new_cost
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visited[neigh_node] = cur_node
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return visited
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grid =['2229222222222',
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'2229222222222',
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'9929222222222',
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'9929222222222',
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'9929222222222',
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'2222222222222',
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'2222222222222',
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'2222222222222',
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'2222222222222',
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'2222222222222',
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'2222222222222',
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'2222222222222'
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]
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grid = [[int(char) for char in string ] for string in grid]
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graph ={}
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for y, row in enumerate(grid):
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for x, col in enumerate(row):
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graph[(x, y)] = graph.get((x, y), []) + get_neighbours(x, y)
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#print("graph 2 0",graph[(2,0)])
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start = (1,1)
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goal =(0,5)
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queue =[]
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heappush(queue, (0,start))
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cost_visited = {start:0}
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visited = {start: None}
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goall=1
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while goall==1:
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if queue:
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visited=dijkstra(start,goal,graph)
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goall=0
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path=[]
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path_head, path_segment = goal, goal
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while path_segment:
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# print("path_segment: ",path_segment)
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path_segment =visited[path_segment]
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path.append(path_segment)
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#print("path_head",path_head)
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path.pop(len(path)-1)
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path.reverse()
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path_true=[]
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bfss =Bfs(Game)
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for i in path:
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z=str(i)
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#print("Z:",z)
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x=z[1]
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y=z[4]
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x=int(x)*64
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y=int(y)*64
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a=bfss.get_cell_number(x,y)
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path_true.append(a)
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#print("path:",path)
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#print("path_true:",path_true)
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#bfss.move_agent(path_true)
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g = Game()
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g.new()
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while g.running:
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g.main()
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@ -50,8 +50,6 @@ class Grass(pygame.sprite.Sprite):
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self.rect.x = self.x
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self.rect.y = self.y
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self.cost = 10
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self._layer = GRASS_LAYER
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class Health_flower(pygame.sprite.Sprite):
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