136 lines
4.4 KiB
Python
136 lines
4.4 KiB
Python
import time
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# Constants and Initialization
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MAP_SIZE = 9
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start = (0, 0) # initial position of Neo
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neo = start # position of Neo
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observer = neo
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keymaster = () # position of Keymaster
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closed_cells = []
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blocked_cells = []
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passed_cells = []
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steps_count = 0
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accumulated_g = 0
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weighted_map_dict = dict()
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# Helper Functions
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def get_position_input():
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position_input_list = input().split(" ")
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return int(position_input_list[0]), int(position_input_list[1])
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def get_walkable_cells(obj:tuple):
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potential_positions = [
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(obj[0], obj[1] + 1), (obj[0], obj[1] - 1),
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(obj[0] - 1, obj[1]), (obj[0] + 1, obj[1])
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]
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return [pos for pos in potential_positions if pos[0] in range(MAP_SIZE) and pos[1] in range(MAP_SIZE) and pos not in closed_cells]
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def get_g(cell):
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return accumulated_g + 1
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def get_h(cell):
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return abs(keymaster[0] - cell[0]) + abs(keymaster[1] - cell[1])
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def get_f(cell):
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return get_g(cell) + get_h(cell)
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'''def get_verified_move_position(new_position):
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if new_position in get_walkable_cells():
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return new_position
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else:
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print("CAN'T MOVE HERE!")
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return neo'''
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def print_map():
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map_str = ""
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for x in range(MAP_SIZE):
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for y in range(MAP_SIZE):
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if x == neo[0] and y == neo[1]:
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map_str += " n "
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elif (x == observer[0] and y == observer[1]):
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map_str += " o "
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elif (x == keymaster[0] and y == keymaster[1]):
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map_str += " k "
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elif ((x,y) in passed_cells):
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map_str += " # "
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elif ((x,y) in closed_cells):
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map_str += " = "
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elif ((x,y) in blocked_cells):
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map_str += " - "
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else:
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map_str += " + "
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map_str += "\n"
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print(map_str)
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def read_system():
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number_of_items = int(input())
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if number_of_items == 0:
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return False
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items = {}
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for _ in range(number_of_items):
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x, y, status = input().split(' ')
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items[(int(x), int(y))] = status
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return items
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def regenerate_route():
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global closed_cells, observer
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accumulated_g = 0
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finish = False
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while not finish:
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walkable_cells_and_f = {cell: get_f(cell) for cell in get_walkable_cells(observer) if cell not in blocked_cells}
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min_f_value = min(walkable_cells_and_f.values())
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min_f_cell_list = [cell for cell, f_value in walkable_cells_and_f.items() if f_value == min_f_value]
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if len(min_f_cell_list) == 1:
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next_cell = min_f_cell_list[0]
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else:
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next_cell = min(min_f_cell_list, key=lambda cell: get_h(cell))
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observer = next_cell
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accumulated_g += 1 # TODO ENSURE THAT g WORKS PROPERLY
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closed_cells.append(next_cell)
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print(f"m {next_cell[1]} {next_cell[0]}") # TODO FIX OR ENSURE THAT x,y OR y,x DOES NOT MAKE ANY DIFFERENCE
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print_map()
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time.sleep(0.2)
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finish = (observer == keymaster)
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def initialize_weighted_map_dict():
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for x in range(MAP_SIZE):
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for y in range(MAP_SIZE):
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weighted_map_dict[(x, y)] = (float("inf"), float("inf"), float("inf"), '+') # (x,y) : (h, g, f, type)
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# Main Logic
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perception_radius = input()
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keymaster = get_position_input()
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print(f"m {neo[0]} {neo[1]}")
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closed_cells.extend((0, 0)) #TODO FIX START CELL SET TO =
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finish = False
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while not finish:
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observer = neo
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regenerate_route()
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recieved_input = read_system()
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if recieved_input:
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blocked_cells.extend([pos for pos, status in recieved_input.items() if status == "P"])
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walkable_cells_and_f = {cell: get_f(cell) for cell in get_walkable_cells(neo) if cell not in blocked_cells}
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min_f_value = min(walkable_cells_and_f.values())
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min_f_cell_list = [cell for cell, f_value in walkable_cells_and_f.items() if f_value == min_f_value]
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if len(min_f_cell_list) == 1:
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next_cell = min_f_cell_list[0]
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else:
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next_cell = min(min_f_cell_list, key=lambda cell: get_h(cell))
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neo = next_cell
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accumulated_g += 1 # TODO ENSURE THAT g WORKS PROPERLY
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closed_cells.append(next_cell) # TODO DELETE
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passed_cells.append(next_cell)
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print(f"m {next_cell[1]} {next_cell[0]}") # TODO FIX OR ENSURE THAT x,y OR y,x DOES NOT MAKE ANY DIFFERENCE
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steps_count += 1
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#print_map()
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finish = (neo == keymaster)
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print(f"e {steps_count}")
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# TODO CHECK TESTS FROM CODEFORCES |