def get_route(start_point, end_point):
start_stations = vc_landmarks[start_point]
end_stations = vc_landmarks[end_point]
routes = []
for start_station in start_stations:
for end_station in end_stations:
metro_system = get_active_stations(
) if stations_under_construction else vc_metro
if len(stations_under_construction) > 0:
possible_route = dfs(metro_system, start_station, end_station)
if possible_route is None:
return None
route = bfs(metro_system, start_station, end_station)
if route is not None:
routes.append(route)
shortest_route = min(routes, key=len)
return shortest_route
def get_route(start_point, end_point):
start_stations = vc_landmarks[start_point]
end_stations = vc_landmarks[end_point]
routes = []
for start_station in start_stations:
for end_station in end_stations:
metro_system = get_active_stations(
) if stations_under_construction else vc_metro
if stations_under_construction:
possible_route = dfs(metro_system, start_station, end_station)
if not possible_route:
return
route = bfs(metro_system, start_station, end_station)
if route:
routes += [route]
shortest_route = min(routes, key=len)
return shortest_route
def get_route(start_point,end_point):
if start_point == end_point:
print("ERROR: Start point and end point cannot be the same!\nPlease try again")
new_route()
else:
start_stations = vc_landmarks[start_point]
end_stations = vc_landmarks[end_point]
routes = []
for start_station in start_stations:
for end_station in end_stations:
metro_system = get_active_stations() if stations_under_construction else vc_metro
if stations_under_construction:
possible_route = dfs(metro_system,start_station,end_station)
if not possible_route:
return None
route = bfs(metro_system,start_station,end_station)
if route:
routes.append(route)
shortest_route = min(routes,key=len)
return shortest_route
def get_route(start_point, end_point):
start_stations = vc_landmarks[start_point]
end_stations = vc_landmarks[end_point]
routes = []
for start_station in start_stations:
for end_station in end_stations:
# if there is construction metro_system becomes new updated graph. Else vc_metro graph is used
metro_system = get_active_stations(
) if stations_under_construction else vc_metro
# checks if there is a possible route with a depth first search
if len(stations_under_construction) > 0:
possible_route = dfs(metro_system, start_station, end_station)
if possible_route is None:
return None
# creates routes with the different start and end stations
route = bfs(metro_system, start_station, end_station)
if route:
routes.append(route)
# selects shortest route from list of routes.
shortest_route = min(routes, key=len)
return shortest_route
def get_route(start_point, end_point):
start_stations = vc_landmarks[start_point]
end_stations = vc_landmarks[end_point]
routes = []
for start_station in start_stations:
for end_station in end_stations:
# accommodats ournew updated_metro graph if there are stations under construction
metro_system = get_active_stations(
) if stations_under_construction else vc_metro
# makes sure stations_under_constructions isn't empty
if len(stations_under_construction) > 0:
# using depth-first function to help find shortest route between points
possible_route = dfs(metro_system, start_station, end_station)
if possible_route is None:
return None
route = bfs(metro_system, start_station, end_station)
if route is not None:
routes.append(route)
# find shortest route with little trick, 2D list
shortest_route = min(routes, key=len)
return shortest_route
def get_route(start_point, end_point):
start_stations = vc_landmarks[start_point]
end_stations = vc_landmarks[end_point]
routes = []
for start_station in start_stations:
for end_station in end_stations:
metro_system = get_active_stations(
) if stations_under_construction else vc_metro
if stations_under_construction:
possible_route = dfs(metro_system, start_station,
end_station)
if not possible_route:
print(
"There is not route between station {0} and station {1}."
.format(start_station, end_station))
return None
route = bfs(metro_system, start_station, end_station)
if route:
routes += [route]
shortest_route = min(routes, key=len)
return shortest_route
def get_route(start_point, end_point):
# we grab the sets of stations connected to the start_point and end_point landmarks
start_stations = vc_landmarks[start_point]
end_stations = vc_landmarks[end_point]
# because some landmarks have more than one station, there is sometimes more than one route between landmarks
# it’s our job to collect ALL of the shortest routes between stations and then compare them based on path length
# to collect our shortest routes for comparison, create an empty list
routes = []
# we loop through each station in start_stations
for start_station in start_stations:
# and each station in end_stations
for end_station in end_stations:
## add changes to accommodate our new updated_metro graph if there are stations under construction
## if stations_under_construction isn't empty we use the updated metro graph returned with the helper function
## if there are no stations_under_construction we can keep using the original graph
metro_system = get_active_stations() if stations_under_construction else vc_metro
## if there are stations_under_construction it means we might not find a route at all
if stations_under_construction:
## so it is worth to check if a route even exists using the dfs() function
possible_route = dfs(metro_system, start_station, end_station)
## if there is no possible_route we return None, we need this step because
## then shortest_route will be None in new_route() and we have some control flow set up to handle that condition
if not possible_route:
return None
## update the graph used to metro_system so that we can get the shortest route for whichever metro graph is currently in place
# we call bfs() on each combination of start and end station to find all the shortest routes
route = bfs(metro_system, start_station, end_station)
# check if a route exists between the two stations looked at
if route is not None:
# the route returned from bfs() is a list that represents the path
# add this new shortest route to the routes list
routes.append(route)
# after the loops finished we have all the shortest route options saved in routes
# we can now get our shortest route from the list based on list length
shortest_route = min(routes, key = len)
return shortest_route
def get_route(start_point, end_point):
#each landmark could have several start stations and several end stations
start_stations = vc_landmarks[start_point]
end_stations = vc_landmarks[end_point]
routes = []
#for each start station, and for each end station, see if there is a route
for sstation in start_stations:
for estation in end_stations:
metro_system = get_active_stations(
) if stations_under_construction else vc_metro
if stations_under_construction != []:
possible_route = dfs(metro_system, sstation, estation)
if not possible_route:
return None
route = bfs(metro_system, sstation, estation)
#if the route exists, add to list
if route:
routes.append(route)
#find the shortest route
shortest_route = min(routes, key=len)
return shortest_route
def get_route(start_point, end_point):
# define start and end locations
start_stations = vc_landmarks[start_point]
end_stations = vc_landmarks[end_point]
# initiate route list
all_routes = []
# updated metro system with stations under construction
metro_system = get_active_stations(
) if stations_under_construction else vc_metro
# check to see if stations_under construction
# make it immposible for travel from one
# location to anothe
for ss in start_stations:
for es in end_stations:
possible_route = dfs(metro_system, ss, es)
if possible_route:
if possible_route not in all_routes:
all_routes.append(possible_route)
if possible_route == None:
return None
# itterating through all posible start stations
# nearest landmarks
for start_station in start_stations:
for end_station in end_stations:
route = bfs(vc_metro, start_station, end_station)
if route not in all_routes:
all_routes.append(route)
return all_routes
def get_route(start_point, end_point):
start_stations = vc_landmarks[start_point]
end_stations = vc_landmarks[end_point]
routes = []
for start in start_stations:
for end in end_stations:
metro_system = get_active_stations(
) if stations_under_construction else vc_metro
if stations_under_construction:
possible_route = dfs(metro_system, start, end)
if not possible_route:
return None
route = bfs(metro_system, start, end)
if route:
routes.append(route)
try:
shortest_route = min(routes, key=len)
return shortest_route
except ValueError:
print("You are already at the closest station to your destination!")
new_destination = input(
"Would you like to input a new destination? y/n")
if new_destination.lower() == "y":
new_route(start_point, end_point)
def get_route(start_point, end_point):
start_stations = vc_landmarks[start_point]
end_stations = vc_landmarks[end_point]
routes = []
for start_station in start_stations:
for end_station in end_stations:
if len(stations_under_construction) != 0:
metro_system = get_active_stations()
else:
metro_system = vc_metro
if len(stations_under_construction) != 0:
#checking if route exists
possible_route = dfs(metro_system, start_station, end_station)
if not possible_route:
return None
route = bfs(metro_system, start_station, end_station)
if route:
routes += [route]
shortest_route = min(routes, key=len)
return shortest_route
import graph_search
g = graph_search.GridMap('./map0.txt')
file = open('output0.txt', 'a')
[[path, action_path],visited]=graph_search.dfs(g.init_pos , g.transition , g.is_goal, graph_search._ACTIONS)
file.write("BFS on map0: path = "+str(path) + "\n")
file.write("BFS on map0: action_path = "+str(action_path) + "\n")
file.write("BFS on map0: visited = "+str(visited) + "\n")
g.display_map(path,visited)
file.close()
import graph_search
g = graph_search.GridMap('./map1.txt')
file = open('output1.txt', 'a')
[[path, action_path],visited]=graph_search.dfs(g.init_pos , g.transition , g.is_goal, graph_search._ACTIONS)
file.write("BFS on map1: path = "+str(path) + "\n")
file.write("BFS on map1: action_path = "+str(action_path) + "\n")
file.write("BFS on map2: visited = "+str(visited) + "\n")
g.display_map(path,visited)
file.close()
import graph_search
g = graph_search.GridMap('./map2.txt')
file = open('output2.txt', 'a')
[[path, action_path],visited]=graph_search.dfs(g.init_pos , g.transition , g.is_goal, graph_search._ACTIONS)
file.write("BFS on map2: path = "+str(path) + "\n")
file.write("BFS on map2: action_path = "+str(action_path) + "\n")
file.write("BFS on map2: visited = "+str(visited) + "\n")
g.display_map(path,visited)
file.close()
import graph_search
g = graph_search.GridMap('./map0.txt')
file = open('output0.txt', 'a')
[[path, action_path],
visited] = graph_search.dfs(g.init_pos, g.transition, g.is_goal,
graph_search._ACTIONS)
print(path)
print(action_path)
print(visited)
file.write("BFS on map0: path = " + str(path) + "\n")
file.write("BFS on map0: action_path = " + str(action_path) + "\n")
file.write("BFS on map0: visited = " + str(visited) + "\n")
g.display_map(path, visited, "Project-1_1.1_DFS on map0")
file.close()
import graph_search
g = graph_search.GridMap('./map1.txt')
file = open('output1.txt', 'a')
[[path, action_path],
visited] = graph_search.dfs(g.init_pos, g.transition, g.is_goal,
graph_search._ACTIONS)
print(path)
print(action_path)
print(visited)
file.write("BFS on map1: path = " + str(path) + "\n")
file.write("BFS on map1: action_path = " + str(action_path) + "\n")
file.write("BFS on map2: visited = " + str(visited) + "\n")
g.display_map(path, visited, "Project-1_1_1.2_DFS on map1")
file.close()
import graph_search
def run_dfs(map_path):
g = graph_search.GridMap(map_path)
res = graph_search.dfs(g.init_pos, g.transition, g.is_goal,
graph_search._ACTIONS)
g.display_map(res[0][0], res[1])
