def apply_astar(self):
print "A star algorithm running to find the goal"
close = set()
open = set()
open.add(self.return_key(self._tiles))
parent = {}
g_score = defaultdict(lambda: math.inf)
g_score[self.return_key(self._tiles)] = 0
f_score = PQDict.minpq()
f_matric = {}
value = g_score[self.return_key(self._tiles)] + self.heuristic(self._tiles,self.end_index)
f_score[self.return_key(self._tiles)] = value
f_matric[self.return_key(self._tiles)] = self._tiles
while open:
temp_current_key = f_score.pop()
current = f_matric[temp_current_key]
if temp_current_key == self.return_key(self.end):
print "goal found"
self.construct_path(parent,moves,temp_current_key)
print "Number of closed states are ", len(close)
return 1
if temp_current_key in open:
open.discard(temp_current_key)
close.add(self.return_key(current))
l = self.cal_child_nodes(current)
moves = {}
for x in l:
temp_node = copy.copy(l[x][0])
if self.return_key(temp_node) in close:
continue
new_g_value = g_score[self.return_key(current)] + 1
if self.return_key(temp_node) not in open or new_g_value < g_score[self.return_key(temp_node)]:
parent[self.return_key(temp_node)] = [self.return_key(current),l[x][1]]
moves[self.return_key(temp_node)] = l[x][1]
g_score[self.return_key(temp_node)] = new_g_value
value_new = g_score[self.return_key(temp_node)] + self.heuristic(temp_node,self.end_index)
f_score[self.return_key(temp_node)] = value_new
if self.return_key(temp_node) not in open:
open.add(self.return_key(temp_node))
if self.return_key(temp_node) not in f_matric:
f_matric[self.return_key(temp_node)] = temp_node
return 0
def a_star_algo(self, start_city, end_city, routing_option):
print "calling a-star algorithm"
close = set()
open = set()
open.add(start_city)
parent = {}
g_score = defaultdict(lambda: math.inf)
g_score[start_city] = 0
# PQDict is a function imported from a code found online.
# reference : http://pydoc.net/Python/pqdict/0.5/pqdict/
f_score = PQDict.minpq()
if routing_option == "distance":
f_score[start_city] = g_score[start_city] + self.great_circle_distance(start_city, end_city)
elif routing_option == "segments":
f_score[start_city] = g_score[start_city]
elif routing_option == "time":
f_score[start_city] = g_score[start_city] + self.great_circle_distance(start_city, end_city)/self.avg_speed
while open:
temp_current = f_score.pop()
current = temp_current
if current == end_city:
self.bfs_short_path(parent,start_city, end_city)
return 1
if current in open:
open.discard(current)
close.add(current)
l = self.cities[current].get_outEdges()
for x in range(len(l)):
temp_city = l[x].get_highway_end().get_cityname()
if temp_city in close:
continue
# if requested for miles
if routing_option == "distance":
new_g_value = g_score[current] + int(l[x].get_miles())
# if requested for segments
elif routing_option == "segments":
new_g_value = g_score[current] + 1
# if requested for time
elif routing_option == "time":
dis = int(l[x].get_miles())
speed = int(l[x].get_speed())
new_g_value = g_score[current] + int(dis/speed)
if temp_city not in open or new_g_value < g_score[temp_city]:
parent[temp_city] = [current,l[x]]
g_score[temp_city] = new_g_value
if routing_option == "distance":
f_score[temp_city] = g_score[temp_city] + self.great_circle_distance(temp_city,end_city)
elif routing_option == "segments":
f_score[temp_city] = g_score[temp_city]
elif routing_option == "time":
f_score[temp_city] = g_score[temp_city] + self.great_circle_distance(temp_city, end_city)/self.avg_speed
if temp_city not in open:
open.add(temp_city)
return 0
def a_star_algo(self, start_city, end_city, routing_option):
print "calling a-star algorithm"
close = set()
open = set()
open.add(start_city)
parent = {}
g_score = defaultdict(lambda: math.inf)
g_score[start_city] = 0
# PQDict is a function imported from a code found online.
# reference : http://pydoc.net/Python/pqdict/0.5/pqdict/
f_score = PQDict.minpq()
if routing_option == "distance":
f_score[
start_city] = g_score[start_city] + self.great_circle_distance(
start_city, end_city)
elif routing_option == "segments":
f_score[start_city] = g_score[start_city]
elif routing_option == "time":
f_score[
start_city] = g_score[start_city] + self.great_circle_distance(
start_city, end_city) / self.avg_speed
while open:
temp_current = f_score.pop()
current = temp_current
if current == end_city:
self.bfs_short_path(parent, start_city, end_city)
return 1
if current in open:
open.discard(current)
close.add(current)
l = self.cities[current].get_outEdges()
for x in range(len(l)):
temp_city = l[x].get_highway_end().get_cityname()
if temp_city in close:
continue
# if requested for miles
if routing_option == "distance":
new_g_value = g_score[current] + int(l[x].get_miles())
# if requested for segments
elif routing_option == "segments":
new_g_value = g_score[current] + 1
# if requested for time
elif routing_option == "time":
dis = int(l[x].get_miles())
speed = int(l[x].get_speed())
new_g_value = g_score[current] + int(dis / speed)
if temp_city not in open or new_g_value < g_score[temp_city]:
parent[temp_city] = [current, l[x]]
g_score[temp_city] = new_g_value
if routing_option == "distance":
f_score[temp_city] = g_score[
temp_city] + self.great_circle_distance(
temp_city, end_city)
elif routing_option == "segments":
f_score[temp_city] = g_score[temp_city]
elif routing_option == "time":
f_score[temp_city] = g_score[
temp_city] + self.great_circle_distance(
temp_city, end_city) / self.avg_speed
if temp_city not in open:
open.add(temp_city)
return 0
