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ids.py
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ids.py
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import numpy as np
from ordered_set import OrderedSet
import view
import time
class Node:
def __init__(self, state, parent, direction=None):
self.__state = state
self.__parent = parent
self.__direction = direction
def get_state(self):
return self.__state
def get_parent(self):
return self.__parent
def get_direction(self):
return self.__direction
def __eq__(self, other):
if isinstance(other, Node):
return np.array_equal(self.__state, other.get_state())
else:
return False
def __hash__(self):
return hash(repr(self.__state)[6:-15])
def evaluate_neighbour(state, cor, target=False):
up, down, left, right = None, None, None, None
if cor[0] - 1 >= 0:
up = state[cor[0] - 1, cor[1]]
if ('x' in up) or ((not target) and 'b' in up):
up = None
if cor[0] + 1 < state.shape[0]:
down = state[cor[0] + 1, cor[1]]
if ('x' in down) or ((not target) and 'b' in down):
down = None
if cor[1] - 1 >= 0:
left = state[cor[0], cor[1] - 1]
if ('x' in left) or ((not target) and 'b' in left):
left = None
if cor[1] + 1 < state.shape[1]:
right = state[cor[0], cor[1] + 1]
if ('x' in right) or ((not target) and 'b' in right):
right = None
return up, down, left, right
def determine_direction(a, b):
if a == 1:
direction = 'D'
elif a == -1:
direction = 'U'
else:
if b == 1:
direction = 'R'
else:
direction = 'L'
return direction
def butter_destination_successor(state, robot_cor, butter_cor):
result = []
up, down, left, right = evaluate_neighbour(state, butter_cor)
if up is None:
down = None
if down is None:
up = None
if left is None:
right = None
if right is None:
left = None
def new_state(a, b):
n_state = state.copy()
n_state[butter_cor[0], butter_cor[1]] = n_state[butter_cor[0], butter_cor[1]][:-1] + 'r'
n_state[robot_cor[0], robot_cor[1]] = n_state[robot_cor[0], robot_cor[1]][:-1]
if 'p' in n_state[butter_cor[0] + a, butter_cor[1] + b]:
n_state[butter_cor[0] + a, butter_cor[1] + b] = n_state[butter_cor[0] + a, butter_cor[1] + b][:-1] + 'b'
else:
n_state[butter_cor[0] + a, butter_cor[1] + b] += 'b'
dst_state = state.copy()
dst_state[robot_cor[0], robot_cor[1]] = dst_state[robot_cor[0], robot_cor[1]][:-1]
dst_state[butter_cor[0] - a, butter_cor[1] - b] += 'r'
res, _, _, _ = ids(Node(state, None), [Node(dst_state, None)], robot_butter_successor, (state, robot_cor))
return (n_state,), (butter_cor[0] + a, butter_cor[1] + b), (butter_cor[0], butter_cor[1]), \
(determine_direction(a, b),), (res,)
if up is not None:
data = new_state(-1, 0)
if data[4][0] is not None:
result.append(data)
if down is not None:
data = new_state(1, 0)
if data[4][0] is not None:
result.append(data)
if left is not None:
data = new_state(0, -1)
if data[4][0] is not None:
result.append(data)
if right is not None:
data = new_state(0, 1)
if data[4][0] is not None:
result.append(data)
return result
def robot_butter_successor(state, robot_cor, butter_cor=None):
states = []
up, down, left, right = evaluate_neighbour(state, robot_cor)
def new_state(a, b):
n_state = state.copy()
n_state[robot_cor[0] + a, robot_cor[1] + b] += 'r'
n_state[robot_cor[0], robot_cor[1]] = n_state[robot_cor[0], robot_cor[1]][:-1]
return (n_state,), (None, None), (robot_cor[0] + a, robot_cor[1] + b), \
(determine_direction(a, b),), (None,)
if up is not None:
states.append(new_state(-1, 0))
if down is not None:
states.append(new_state(1, 0))
if left is not None:
states.append(new_state(0, -1))
if right is not None:
states.append(new_state(0, 1))
return states
def goal(src_node, dst_nodes):
for dst_node in dst_nodes:
if np.array_equal(src_node.get_state(), dst_node.get_state()):
return True
return False
def dls(node, dst_nodes, successor, successor_args, visited, limit, stack, cost=0):
if goal(node, dst_nodes):
return stack, node, cost
visited.add(repr(node.get_state())[6:-15])
if limit <= 0:
visited.pop()
return None, None, None
for data in successor(*successor_args):
if data[4][0] is not None:
stack.append(data[4][0])
cost += len(data[4][0])
stack.append(data[3][0])
cost += 1
cur_node = Node(data[0][0], node)
cur_successor_args = data[0][0], data[2], data[1]
if not (repr(cur_node.get_state())[6:-15] in visited):
res, goal_node, new_cost = dls(cur_node, dst_nodes, successor, cur_successor_args, visited, limit - 1,
stack, cost)
if res is not None:
return res, goal_node, new_cost
del cur_node
stack.pop()
cost -= 1
if data[4][0] is not None:
stack.pop()
cost -= len(data[4][0])
visited.pop()
return None, None, None
def ids(node, dst_nodes, successor, successor_args):
for limit in range(1, node.get_state().shape[0] * node.get_state().shape[1]):
res, goal_node, cost = dls(node, dst_nodes, successor, successor_args, OrderedSet(),
limit, [])
if res is not None:
return res, goal_node, cost, sum(map(len, res))
return None, None, None, None
def goal_node_creator(initial_state, robot_cor, butter_cor, target_cors):
def new_state(a, b):
n_state = initial_state.copy()
n_state[target_cor[0], target_cor[1]] = n_state[target_cor[0], target_cor[1]][:-1] + 'b'
n_state[butter_cor[0], butter_cor[1]] = n_state[butter_cor[0], butter_cor[1]][:-1]
if 'b' not in n_state[target_cor[0] + a, target_cor[1] + b]:
n_state[target_cor[0] + a, target_cor[1] + b] += 'r'
else:
return None
n_state[robot_cor[0], robot_cor[1]] = n_state[robot_cor[0], robot_cor[1]][:-1]
return n_state
goal_nodes = []
for target_cor in target_cors:
up, down, left, right = evaluate_neighbour(initial_state, target_cor, target=True)
if up is not None:
new_node = Node(new_state(-1, 0), None)
if new_node.get_state() is not None:
goal_nodes.append(new_node)
if down is not None:
new_node = Node(new_state(1, 0), None)
if new_node.get_state() is not None:
goal_nodes.append(new_node)
if left is not None:
new_node = Node(new_state(0, -1), None)
if new_node.get_state() is not None:
goal_nodes.append(new_node)
if right is not None:
new_node = Node(new_state(0, 1), None)
if new_node.get_state() is not None:
goal_nodes.append(new_node)
return goal_nodes
def input_parser():
row, col = input().split()
data = []
for i in range(int(row)):
dummy = input().split()
data.append(dummy)
return np.array(data, dtype='object')
def permutation_of_butters(butter_cors, init_state, robot_cor, target_cors, step=0, result=None):
if result is None:
result = []
if step == len(butter_cors):
current_state = init_state
total_path = []
total_cost = 0
counter = 0
total_depth = 0
for butter_cor in butter_cors:
path, goal_node, cost, depth = ids(Node(current_state, None),
goal_node_creator(current_state, robot_cor,
butter_cor, target_cors),
butter_destination_successor,
(current_state, robot_cor, butter_cor))
if path is not None:
current_state = goal_node.get_state()
for i in range(current_state.shape[0]):
for j in range(current_state.shape[1]):
if 'r' in current_state[i, j]:
robot_cor = i, j
total_path.extend(path)
total_cost += cost
counter += 1
total_depth = total_cost
result.append([total_path, total_cost, counter, total_depth])
for i in range(step, len(butter_cors)):
butter_cors_copy = butter_cors.copy()
butter_cors_copy[i], butter_cors_copy[step] = butter_cors_copy[step], butter_cors_copy[i]
permutation_of_butters(butter_cors_copy, init_state, robot_cor, target_cors, step + 1, result)
def extract_result(final_result, num_of_butters):
max_counter = max(i[2] for i in final_result)
min_cost = np.Inf
best_result = None
for i in range(len(final_result)):
if max_counter == final_result[i][2]:
if final_result[i][1] < min_cost:
min_cost = final_result[i][1]
best_result = final_result[i]
if max_counter == 0:
print('can’t pass the butter')
elif max_counter == num_of_butters:
li = []
for part in best_result[0]:
li.extend(part)
print(*li)
print(best_result[1])
print(best_result[3])
return li
else:
print('can’t pass {} butter{}'.format(num_of_butters - max_counter,
's' if num_of_butters - max_counter > 1 else ''))
li = []
for part in best_result[0]:
li.extend(part)
print(*li)
print(best_result[1])
print(best_result[3])
return li
def main():
init_state = input_parser()
robot_cor = ()
butter_cors = []
target_cors = []
for i in range(init_state.shape[0]):
for j in range(init_state.shape[1]):
if 'r' in init_state[i, j]:
robot_cor = i, j
elif 'b' in init_state[i, j]:
butter_cor = i, j
butter_cors.append(butter_cor)
elif 'p' in init_state[i, j]:
target_cor = i, j
target_cors.append(target_cor)
final_result = []
permutation_of_butters(butter_cors, init_state, robot_cor, target_cors, result=final_result)
moves = extract_result(final_result, len(butter_cors))
time.sleep(2)
view.start(init_state, moves)
if __name__ == '__main__':
main()