def get_itinerary(addresses):
#return nothing if no input
if len(addresses) == 1 and addresses[0] == "":
return []
# if fails vertices is -1 and D is the address for which there is a format error
D, vertices = construct_matrix(addresses)
if vertices == -1:
return ["Format Error: " + str(D)]
path = solve_tsp(D, optim_steps=10)
ordered_addresses = []
for entry in path:
ordered_addresses.append(vertices[entry].geoloc.address)
return ordered_addresses
def main(cities, origin_address, origin_coordinates, search_limit=1):
SEARCH_LIMIT = 1
if search_limit != 1:
SEARCH_LIMIT = search_limit
# coordinates of locations
locations = []
# User-friendly Addresses
prettyLocations = []
locations.append(origin_coordinates)
prettyLocations.append(['Origin',origin_address])
counter = 0
# Get list of top restaurants in each city
for city in cities:
try:
response = yelp.query_api('bars', city, SEARCH_LIMIT)
for item in response:
locations.append(str(item.get('location').get('coordinate').get('latitude')) + ',' +
str(item.get('location').get('coordinate').get('longitude')))
# Save restaurant name and address
prettyName = ""
if len(item.get('location').get('display_address')) > 0:
prettyName += item.get('location').get('display_address')[0]
if len(item.get('location').get('display_address')) > 1:
prettyName += ", "+item.get('location').get('display_address')[1]
if len(item.get('location').get('display_address')) > 2:
prettyName += ", "+item.get('location').get('display_address')[2]
prettyLocations.append([item.get('name'),prettyName])
except urllib2.HTTPError as error:
sys.exit('Encountered HTTP error {0}. Abort program.'.format(error.code))
# ------
# STEP 2 - Get distances between each restaurant
# ------
# Generate list of locations to visit in order
url = 'https://maps.googleapis.com/maps/api/directions/json'
# Create 2D array to keep track of pairs of locations - USE NUMPY LATER
pairs = [[0]*len(locations) for x in xrange(len(locations))]
distances_matrix = [[0]*len(locations) for x in xrange(len(locations))]
# Numbers to indicate progress
lookupNum = 0
for i in range(len(locations) - 1):
lookupNum += (i+1)
counter = 0
for i in range(0, len(locations)):
for j in range(0, len(locations)):
# Skip over duplicate pairs of locations to reduce requests
if pairs[i][j] != 1 and i != j:
# Set parameters
params = dict(
origin = locations[i],
destination = locations[j],
key = get_server_key()
)
# Set to 1 to skip later
pairs[i][j] = 1
pairs[j][i] = 1
# Send request to Google Maps
time.sleep(0.1)
resp = requests.get(url=url, params=params)
data = json.loads(resp.text)
if (data.get('status') == 'ZERO_RESULTS'):
return {"status": 500,
"message": "Directions not found from " + prettyLocations[i][1]
+ " to " + prettyLocations[j][1]}
else:
# Storing distances in matrix for tsp_solver
distances_matrix[i][j] = data.get('routes')[0].get('legs')[0].get('distance').get('value')
distances_matrix[j][i] = data.get('routes')[0].get('legs')[0].get('distance').get('value')
counter += 1
sys.stdout.write("\rGetting Distances...%d%%" % int((float(counter)/lookupNum) * 100))
sys.stdout.flush()
# ------
# STEP 3 - Algorithm to find shortest path
# ------
# Returns route cycle
cities_index = tsp_solver.solve_tsp(distances_matrix, 3)
# Start and end cycle at start location
route_distance = 0
previous = 0
for index, city in enumerate(cities_index):
route_distance += distances_matrix[previous][city]
previous = city
route_distance += distances_matrix[cities_index[-1]][0]
print('\nDone!')
route_dict = {"origin_coordinates":{"lat": float(origin_coordinates.split(",")[0]),
"lng": float(origin_coordinates.split(",")[1])},
"route_coordinates":[],
"route_names":[],
"route_addresses":[],
"status": 200}
for item in cities_index:
coordinates = locations[item].split(",")
coordict = {"lat": float(coordinates[0]),
"lng": float(coordinates[1])}
route_dict["route_coordinates"].append(coordict)
route_dict["route_names"].append(prettyLocations[item][0])
route_dict["route_addresses"].append(prettyLocations[item][1])
return route_dict
# Storing distances in matrix for tsp_solver
distances_matrix[i][j] = data.get('routes')[0].get('legs')[0].get('distance').get('value')
distances_matrix[j][i] = data.get('routes')[0].get('legs')[0].get('distance').get('value')
counter += 1
sys.stdout.write("\rGetting Distances...%d%%" % int((float(counter)/lookupNum) * 100))
sys.stdout.flush()
print('\n' + ('-' * 50))
# ------
# STEP 3 - Algorithm to find shortest path
# ------
print('Calculating shortest route...')
# Returns route cycle
cities_index = tsp_solver.solve_tsp(distances_matrix, 3)
# Start and end cycle at start location
print('\nRoute:')
route_distance = 0
previous = 0
for index, city in enumerate(cities_index):
route_distance += distances_matrix[previous][city]
print("%d miles driven - %s\n%s\n" % (int(route_distance*0.00062137), prettyLocations[city][0], prettyLocations[city][1]))
previous = city
route_distance += distances_matrix[cities_index[-1]][0]
print("%d miles driven - %s\n%s\n" % (int(route_distance*0.00062137), prettyLocations[0][0], prettyLocations[0][1]))
print("Total Distance Traveled: %d miles" % int(route_distance*0.00062137))
print('\nDone!')
