def test_altgraph():
# these are the edges
edges = [ (1,2), (2,4), (1,3), (2,4), (3,4), (4,5), (6,5), (6,14), (14,15), (6, 15),
(5,7), (7, 8), (7,13), (12,8), (8,13), (11,12), (11,9), (13,11), (9,13), (13,10) ]
store = {}
g = Graph.Graph()
for head, tail in edges:
store[head] = store[tail] = None
g.add_edge(head, tail)
# check the parameters
assert g.number_of_nodes() == len(store)
assert g.number_of_edges() == len(edges)
# do a forward bfs
assert g.forw_bfs(1) == [1, 2, 3, 4, 5, 7, 8, 13, 11, 10, 12, 9]
# diplay the hops and hop numbers between nodes
assert g.get_hops(1, 8) == [(1, 0), (2, 1), (3, 1), (4, 2), (5, 3), (7, 4), (8, 5)]
assert GraphAlgo.shortest_path(g, 1, 12) == [1, 2, 4, 5, 7, 13, 11, 12]
def test_shortest_path(self):
self.assertEqual(GraphAlgo.shortest_path(self.g, 1, 12),
[1, 2, 4, 5, 7, 13, 11, 12])
def test_shortest_path(self):
self.assertEqual(GraphAlgo.shortest_path(self.g, 1, 12),
[1, 2, 4, 5, 7, 13, 11, 12])
def Dijkstra(G, start, end):
return ga.shortest_path(G, start, end)
def main():
if len(sys.argv) != 5:
logging.info('please input args: car_path, road_path, cross_path, answerPath')
exit(1)
car_path = sys.argv[1]
road_path = sys.argv[2]
cross_path = sys.argv[3]
answer_path = sys.argv[4]
# car_path = '../config/car.txt'
# road_path = '../config/road.txt'
# cross_path = '../config/cross.txt'
# answer_path = '../config/answer.txt'
logging.info("car_path is %s" % (car_path))
logging.info("road_path is %s" % (road_path))
logging.info("cross_path is %s" % (cross_path))
logging.info("answer_path is %s" % (answer_path))
opts = {}
opts['car_txt_path'] = car_path
opts['cross_txt_path'] = cross_path
opts['road_txt_path'] = road_path
car_df = read_txt(car_path)
# cross_df = read_txt(cross_path)
road_df = read_txt(road_path)
# 用于记录当前道路车辆数目
road_df['car_num'] = 0
# pdb.set_trace()
car_df = car_df.sort_values(by=['speed', 'planTime'], ascending=False).sort_values(by=['planTime'])
car_df = car_df.reset_index(drop=True)
# 用于记录当前车辆所在道路及位置
car_df['current_road'] = None
car_df['current_loc'] = None
total_path = []
# 已发车车辆行车路线
total_path_dict = {}
count = 0 # 总发车数量
num = 10 # 每次发车数量
# for i in range(len(car_df.index)):
# while not total_path_dict: # 车没有全部到站
# pdb.set_trace()
while len(car_df.index)-1 >= count: # 没有排到最后一辆车
# del total_path_dict['init']
for i in range(count,min(count+num,len(car_df.index))):
car_id = car_df.loc[i, 'id']
car_df.loc[i, 'planTime'] = i // num + 1
start = car_df.loc[i, 'from']
stop = car_df.loc[i, 'to']
graph = build_graph(road_df)
dot_path = GraphAlgo.shortest_path(graph, start, stop)
road_path = []
for j in range(len(dot_path) - 1):
road_id = road_df[((road_df.loc[:, 'from'] == dot_path[j]) & (road_df.to == dot_path[j + 1])) | (
(road_df.loc[:, 'from'] == dot_path[j + 1]) & (road_df.to == dot_path[j]))]['id'].values[0]
road_path.append(road_id)
# total_path_dict[str(car_id)] = road_path
road_path.insert(0, i // num + 1)
road_path.insert(0, car_id)
total_path.append(road_path)
# print(car_id)
total_path_dict.update({str(car_id): road_path[2:]}) # 存入已经规划好行车路线的所有车的路径，若车到站，则删除
update_car_num(road_df, car_df, total_path_dict)
count += num
# to write output file
with open(answer_path, 'w') as f:
for each_car in total_path:
f.write('(')
for each in each_car[:-1]:
f.write(str(each))
f.write(',')
f.write(str(each_car[-1]))
f.write(')')
f.write('\n')
def main():
if len(sys.argv) != 5:
logging.info(
'please input args: car_path, road_path, cross_path, answerPath')
exit(1)
# pool = Pool(processes=4)
# pool = mp.Pool(4)
# jobs = []
car_path = sys.argv[1]
road_path = sys.argv[2]
cross_path = sys.argv[3]
answer_path = sys.argv[4]
# car_path = '../config/car.txt'
# road_path = '../config/road.txt'
# cross_path = '../config/cross.txt'
# answer_path = '../config/answer.txt'
logging.info("car_path is %s" % (car_path))
logging.info("road_path is %s" % (road_path))
logging.info("cross_path is %s" % (cross_path))
logging.info("answer_path is %s" % (answer_path))
opts = {}
opts['car_txt_path'] = car_path
opts['cross_txt_path'] = cross_path
opts['road_txt_path'] = road_path
car_df = read_txt(car_path)
# cross_df = read_txt(cross_path)
road_df = read_txt(road_path)
# pdb.set_trace()
# car_df = car_df.sort_values(by=['speed', 'planTime'], ascending=False).sort_values(by=['planTime'])
car_df = car_df.sort_values(by=['planTime']).reset_index(drop=True)
num = 10
# edges = [(head , tail , weight) , ... ,]
edges = []
for i in range(len(road_df.index)):
head = road_df.loc[i, 'from']
tail = road_df.loc[i, 'to']
# graph weight
time_as_weight = road_df.loc[i, 'length'] / (road_df.loc[i, 'speed'] *
road_df.loc[i, 'channel'])
edges.append((head, tail, time_as_weight))
if road_df.loc[i, 'isDuplex'] == 1:
edges.append((tail, head, time_as_weight))
graph = Graph.Graph()
for head, tail, weight in edges:
graph.add_edge(head, tail, weight)
total_path = []
for i in range(len(car_df.index)):
car_id = car_df.loc[i, 'id']
car_df.loc[i, 'planTime'] = i // num + 1
start = car_df.loc[i, 'from']
stop = car_df.loc[i, 'to']
dot_path = GraphAlgo.shortest_path(graph, start, stop)
road_path = []
for j in range(len(dot_path) - 1):
road_id = road_df[((road_df.loc[:, 'from'] == dot_path[j]) &
(road_df.to == dot_path[j + 1])) |
((road_df.loc[:, 'from'] == dot_path[j + 1]) &
(road_df.to == dot_path[j]))]['id'].values[0]
road_path.append(road_id)
road_path.insert(0, i // num + 1)
road_path.insert(0, car_id)
total_path.append(road_path)
# to write output file
with open(answer_path, 'w') as f:
for each_car in total_path:
f.write('(')
for each in each_car[:-1]:
f.write(str(each) + ',')
f.write(str(each_car[-1]) + ')' + '\n')
