def hc_expand(heap):
path = heap.pop()
nodes = path.get_vertexes()
# nodes.reverse() # must reverse for the new path to work
node_to_be_expanded = path.get_end()
connections = node_to_be_expanded.get_connection()
connections = list(connections)
connections.sort(key=lambda x: x.id, reverse=False)
for c in connections:
if c not in nodes: # because node in 'nodes' are 'visited'
new_path = Path()
for n in nodes:
# print("adding to new path: " + n.id)
new_path.add_vertex(n)
new_path.add_vertex(c)
heap.push_hc(new_path)
heap.hc_sort(
) # find whether path to explore next after pushing all children
def bms_expand(heap, beam_width, visited):
if heap.size() > beam_width:
# print("Before trimming: "+ heap.str_heuristic())
# heap.heuristic_sort()
heap.trim(beam_width)
# print("After trimming: " + heap.str_heuristic())
path = heap.pop()
nodes = path.get_vertexes()
# nodes.reverse() # must reverse for the new path to work
node_to_be_expanded = path.get_end()
connections = node_to_be_expanded.get_connection()
connections = list(connections)
connections.sort(key=lambda x: x.id, reverse=False)
for c in connections:
if c not in nodes and c not in visited: # because node in 'nodes' are 'visited'
new_path = Path()
for n in nodes:
# print("adding to new path: " + n.id)
new_path.add_vertex(n)
new_path.add_vertex(c)
heap.push_bms(
new_path) # use the same push as HC (simple insertion)
def dfs_search(self, source, dest):
'''
Finds all paths from the source vertex to the dettination vertex,
creates a Path object for each of these paths, and adds those Paths
to dfs_paths in order of discovery.
@param sourcs: The ID of the source vertex.
@param dest: The ID of the destination vertex.
'''
stack = [source]
while (len(stack) > 0):
current_vertex = self.vertex_list[stack[len(stack)-1]]
next = current_vertex.get_next()
if (next == dest):
path = Path()
path.add_vertices(stack)
path.add_vertex(next)
self.dfs_paths.append(path)
elif (next != -1):
stack.append(next)
else:
self.vertex_list[stack.pop()].reset_visited()
def General_Search(graph, search_method, d):
start = time.time()
print("Running: " + search_method)
if search_method == 'IDDFS':
print("L = " + str(d) + " Expanded Queue")
else:
print(" Expanded Queue")
# root = g.get_vertex('S')
# destination = g.get_vertex('G')
root = g.get_vertex('S')
destination = g.get_vertex('G')
# queue for unweighted search
queue = Queue()
queue.push([root])
#heap for weighted search
path = Path()
path.add_vertex(root)
heap = Heap()
heap.push(path)
visited = [] # visited used by BMS
while 1:
if search_method == 'UCS' or search_method == 'GS' or search_method == 'AS'\
or search_method == 'HC' or search_method == 'BMS':
nodes = heap.get_left_peek().get_vertexes()
nodes.reverse()
else:
nodes = queue.get_left_peek() # get the left peek without popping
print(' ' + nodes[0].id, end=' ')
# use the given search method
# DFS
if search_method == 'DFS':
print(queue)
dfs_expand(queue)
# BFS
elif search_method == 'BFS':
print(queue)
bfs_expand(queue)
elif search_method == "DLS":
print(queue)
dls_expand(queue, 2)
elif search_method == 'IDDFS':
print(queue)
dls_expand(queue, d)
elif search_method == 'UCS':
print(heap)
ucs_expand(heap)
elif search_method == 'GS':
print(heap.str_heuristic())
gs_expand(heap)
elif search_method == 'AS':
print(heap.str_a_star())
as_expand(heap)
elif search_method == 'HC':
# if len(nodes) > 1:
# unexplored_children = list(nodes[0].get_connection())
# unexplored_children.remove(nodes[1])
#
# # print(unexplored_children)
#
# if len(unexplored_children) != 0: # there is unvisited node(s) from this node
# print(' ' + nodes[0].id, end=' ')
# print(heap.str_heuristic()) # use the same on as the Greedy Search
#
# hc_expand(heap)
#
# else:
print(heap.str_heuristic()) # use the same on as the Greedy Search
hc_expand(heap)
elif search_method == 'BMS':
visited.append(nodes[0])
print(heap.str_heuristic()) # use the same on as the Greedy Search
bms_expand(heap, 2, visited)
# the if's must be in this order: check destination before searching
# otherwise IDDFS won't work
if nodes[0] == destination:
end = time.time()
print(
" goal reached! " + "Time taken by " + search_method +
" is", end - start, "seconds")
return nodes[0]
if queue.isEmpty() or heap.isEmpty():
if search_method == 'IDDFS':
d = d + 1
General_Search(g, 'IDDFS', d) # use recursion for IDDFS
# print("No solution, terminated")
return
