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AdditionalFunctions.py
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AdditionalFunctions.py
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from collections import defaultdict
import copy
# read file and return information about environment
def read_file(file_name):
path = "./input/" + file_name
with open(path, 'r') as file:
size_rows_cols = file.readline()
number_of_rows = int(size_rows_cols.split("\t")[0])
number_of_cols = int(size_rows_cols.split("\t")[1])
number_of_butter = 0
matrix_with_cost = []
matrix_cost = []
matrix_without_cost = []
robot_coordinates = {"x": 0, "y": 0}
for i in range(number_of_rows):
row = file.readline().replace("\t", " ").replace("\n", "").split(" ")
row_matrix_with_cost, row_matrix_cost, row_matrix_without_cost = [], [], []
for j in range(number_of_cols):
row_matrix_with_cost.append(row[j])
if row[j].isnumeric():
row_matrix_without_cost.append("")
row_matrix_cost.append(int(row[j]))
else:
if row[j] == "x":
row_matrix_without_cost.append(row[j])
row_matrix_cost.append(row[j])
else:
char = row[j][-1]
number = row[j][0:-1]
row_matrix_without_cost.append(char)
row_matrix_cost.append(int(number))
if char == "r":
robot_coordinates = {"x": i, "y": j}
if char == "b":
number_of_butter += 1
matrix_with_cost.append(row_matrix_with_cost)
matrix_without_cost.append(row_matrix_without_cost)
matrix_cost.append(row_matrix_cost)
return matrix_with_cost, matrix_without_cost, matrix_cost, number_of_butter, robot_coordinates
def move_forward(environment, next_move, robot_coordinates):
num_rows, num_cols = len(environment), len(environment[0])
new_robot_coordinates = dsum(robot_coordinates, movement_to_coordinate[next_move])
# robot is not allowed to go outside the environment
if 0 <= new_robot_coordinates['x'] < num_rows and 0 <= new_robot_coordinates['y'] < num_cols:
return True, new_robot_coordinates
else:
return False, new_robot_coordinates
# it takes the enviroment, our next move and robot coordinates as input and checks whether the robot can make this
# move or not
def check_next_move(environment, next_move, robot_coordinates):
is_first_step_available, robot_next_coordinates = move_forward(environment, next_move, robot_coordinates)
if not is_first_step_available:
return False
else:
# robot is not allowed to go to the cells with x or bp in it
if 'bp' in environment[robot_next_coordinates['x']][robot_next_coordinates['y']] or 'x' in \
environment[robot_next_coordinates['x']][robot_next_coordinates['y']]:
return False
if 'b' in environment[robot_next_coordinates['x']][robot_next_coordinates['y']]:
# robot can't push two cells both with butter or after butter cell, cell is x
is_two_step_available, butter_next_coordinates = move_forward(environment, next_move,
robot_next_coordinates)
if not is_two_step_available:
return False
else:
if 'b' in environment[butter_next_coordinates['x']][butter_next_coordinates['y']]:
return False
if 'x' in environment[butter_next_coordinates['x']][butter_next_coordinates['y']]:
return False
else:
return True
else:
return True
# get all permitted movements in each state
def get_all_permitted_movements(environment, robot_coordinates):
all_movements = {'u', 'r', 'd', 'l'}
all_permitted_movements = []
for movement in all_movements:
if check_next_move(environment, movement, robot_coordinates):
all_permitted_movements.append(movement)
return all_permitted_movements
movement_to_coordinate = {'u': {"x": -1}, 'r': {"y": +1}, 'd': {"x": +1}, 'l': {"y": -1}}
def dsum(*dicts):
ret = defaultdict(int)
for d in dicts:
for k, v in d.items():
ret[k] += v
return dict(ret)
# get environment and movement then return new environment and new robot coordinates
def update_environment(environment, current_robot_coordinates, movement):
new_robot_coordinates = dsum(current_robot_coordinates, movement_to_coordinate[movement])
curr_robot_x_coordinate, curr_robot_y_coordinate = current_robot_coordinates['x'], current_robot_coordinates['y']
new_robot_x_coordinate, new_robot_y_coordinate = new_robot_coordinates['x'], new_robot_coordinates['y']
new_environment = copy.deepcopy(environment)
# next robot coordinates have butter
if new_environment[new_robot_x_coordinate][new_robot_y_coordinate] == 'b':
new_butter_coordinates = dsum(new_robot_coordinates, movement_to_coordinate[movement])
new_butter_x_coordinate, new_butter_y_coordinate = new_butter_coordinates['x'], new_butter_coordinates['y']
# next butter coordinates have plate
if new_environment[new_butter_x_coordinate][new_butter_y_coordinate] == 'p':
new_environment[new_butter_x_coordinate][new_butter_y_coordinate] = 'bp'
else:
new_environment[new_butter_x_coordinate][new_butter_y_coordinate] = 'b'
new_environment[curr_robot_x_coordinate][curr_robot_y_coordinate] = ''
new_environment[new_robot_x_coordinate][new_robot_y_coordinate] = 'r'
# next robot coordinates have plate
elif new_environment[new_robot_x_coordinate][new_robot_y_coordinate] == 'p':
new_environment[curr_robot_x_coordinate][curr_robot_y_coordinate] = ''
new_environment[new_robot_x_coordinate][new_robot_y_coordinate] = 'rp'
elif new_environment[new_robot_x_coordinate][new_robot_y_coordinate] == '' and \
new_environment[curr_robot_x_coordinate][curr_robot_y_coordinate] == 'rp':
new_environment[curr_robot_x_coordinate][curr_robot_y_coordinate] = 'p'
new_environment[new_robot_x_coordinate][new_robot_y_coordinate] = 'r'
else:
new_environment[curr_robot_x_coordinate][curr_robot_y_coordinate] = ''
new_environment[new_robot_x_coordinate][new_robot_y_coordinate] = 'r'
return new_environment, new_robot_coordinates
def find_plates_coordinates(file_name):
environment_with_cost, environment_without_cost, environment_cost, number_of_butters, robot_coordinates = read_file(
file_name)
num_rows, num_cols = len(environment_without_cost), len(environment_without_cost[0])
plates_coordinates = []
for i in range(num_rows):
for j in range(num_cols):
if environment_without_cost[i][j] == 'p':
plates_coordinates.append({"x": i, "y": j})
return plates_coordinates
def find_butters_coordinates(file_name):
environment_with_cost, environment_without_cost, environment_cost, number_of_butters, robot_coordinates = read_file(
file_name)
num_rows, num_cols = len(environment_without_cost), len(environment_without_cost[0])
butters_coordinates = []
for i in range(num_rows):
for j in range(num_cols):
if environment_without_cost[i][j] == 'b':
butters_coordinates.append({"x": i, "y": j})
return butters_coordinates
def generate_all_goal_environment(file_name):
environment_with_cost, environment_without_cost, environment_cost, number_of_butters, robot_coordinates = read_file(
file_name)
start_robot_x_coordinates, start_robot_y_coordinates = robot_coordinates['x'], robot_coordinates['y']
all_plates_coordinates = find_plates_coordinates(file_name)
all_butters_coordinates = find_butters_coordinates(file_name)
for plate_coordinates in all_plates_coordinates:
plate_x_coordinate, plate_y_coordinate = plate_coordinates['x'], plate_coordinates['y']
environment_without_cost[plate_x_coordinate][plate_y_coordinate] = "bp"
for butter_coordinates in all_butters_coordinates:
butter_x_coordinate, butter_y_coordinate = butter_coordinates['x'], butter_coordinates['y']
environment_without_cost[butter_x_coordinate][butter_y_coordinate] = ''
all_final_robot_coordinates = []
for plate_coordinates in all_plates_coordinates:
plate_x_coordinate, plate_y_coordinate = plate_coordinates['x'], plate_coordinates['y']
all_permitted_movements = get_all_permitted_movements(environment_without_cost, plate_coordinates)
for movement in all_permitted_movements:
final_robot_coordinates = dsum(plate_coordinates, movement_to_coordinate[movement])
all_final_robot_coordinates.append(final_robot_coordinates)
environment_without_cost[start_robot_x_coordinates][start_robot_y_coordinates] = ""
all_goal_environment = []
all_goal_robot_coordinates = []
for final_robot_coordinates in all_final_robot_coordinates:
goal_environment = copy.deepcopy(environment_without_cost)
final_robot_x_coordinates, final_robot_y_coordinates = final_robot_coordinates['x'], final_robot_coordinates[
'y']
goal_environment[final_robot_x_coordinates][final_robot_y_coordinates] = 'r'
all_goal_environment.append(goal_environment)
all_goal_robot_coordinates.append(final_robot_coordinates)
return all_goal_environment, all_goal_robot_coordinates
# get final node(goal state) and return path from start node to goal node
def find_path_with_final_node(node):
path_by_nodes = []
pre_node = node
while pre_node != "":
path_by_nodes.append(pre_node)
pre_node = pre_node.parent
path_by_nodes.reverse()
return path_by_nodes
def print_environment(environment):
for r in environment:
for c in r:
if c == "":
print("-", end=" ")
else:
print(c, end=" ")
print()
def print_path(path):
for node in path:
print("*********************************************************")
print(node.movement)
print_environment(node.environment)
def find_movement_list(path):
movement_list = []
for p in path:
movement_list.append(p.movement)
movement_list.pop(0)
return movement_list
def write_to_file(algorithm, test_case, movement_list, duration):
if algorithm == "IDS":
f = open("result IDS.txt", "a")
elif algorithm == "BBFS":
f = open("result BBFS.txt", "a")
elif algorithm == "ASTAR":
f = open("result ASTAR.txt", "a")
f.write(test_case)
f.write("\npath is: ")
f.write(' --> '.join(movement_list))
f.write('\nduration: ')
f.write(str("{:.2f}".format(duration)))
f.write("\n**************************\n")