def aStar(source):
global explored_num
global produced_num
# The open and closed sets
openset = set()
closedset = set()
# Current point is the starting point
start = Node(state=source, parent=None, depth=0)
# Add the starting point to the open set
openset.add(start)
# While the open set is not empty
while openset:
# Find the item in the open set with the lowest G + H score
node = min(openset, key=lambda o: o.g + o.h)
explored_num += 1
# If it is the item we want, retrace the path and return it
if node.is_goal():
print("goal depth = {}".format(node.depth))
cells = []
while node.parent is not None:
state = node.state
for pack in state:
pack.reverse()
cells.append(state)
node = node.parent
for pack in source:
pack.reverse()
cells.append(source)
cells.reverse()
return cells
# Remove the item from the open set
openset.remove(node)
# Add it to the closed set
closedset.add(node)
# Loop through the node's children/siblings
neighbors = list(neighbors_for_packs(node.state))
produced_num += len(neighbors)
for neighbor_state in neighbors:
neighbor = Node(state=neighbor_state,
parent=node,
depth=node.depth + 1)
# If it is already in the closed set, skip it
if neighbor in closedset:
continue
# Otherwise if it is already in the open set
if neighbor in openset:
# Check if we beat the G score
new_g = node.g + 1
if neighbor.g > new_g:
# If so, update the node to have a new parent
neighbor.g = new_g
neighbor.parent = node
else:
# If it isn't in the open set, calculate the G and H score for the node
neighbor.g = node.g + 1
neighbor.h = heuristic(neighbor)
neighbor.parent = node
# Add it to the set
openset.add(neighbor)
# return None if there is no path
return None
