carId = carMat[:, 0]
car_amount = len(from_car)
'''
初始化权重矩阵，并运行floyd最短路径寻找程序
'''
start = time.time() # 计算耗时，单位为s
R_all = []
planTime1 = 0
from_ = roadMat[:, 4]
to_ = roadMat[:, 5]
roadId = (roadMat[:, 0])
with open('./config/answer.txt', 'a+') as file:
file = open('./config/answer.txt', 'w')
file.truncate()
weight = buildWeight.buildWeight(roadMat, 1e5)
# print(weight.shape)
D, path = floyd.floyd(weight)
for i in range(0, car_amount):
R = floyd.router(D, path, from_car[i], to_car[i])
R1 = [] # 用R1存储道路编号carId
# 实现节点到道路编号的索引查找
for m in range(0, len(R) - 1):
for l in range(0, len(roadId)):
#if from_.tolist().index(R[m])==to_.tolist().index(R[m+1]) or from_.tolist().index(R[m+1])==to_.tolist().index(R[m]):
if from_[l] + to_[l] == R[m] + R[
m + 1] and from_[l] - R[m] + to_[l] - R[m + 1] == 0:
R1.append(roadId[l])
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]
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))
# to read input file
source = road_path ## 源文件路径
dest = '../config/road1.txt' ## 去除括号后的文件路径
f = open(dest, "w+")
f.truncate()
with open(source, 'r') as text:
with open(dest, 'a+') as road_1: ## 以追加写的方式打开目标文件
for line in text.readlines():
road_1.write(line.replace('(', '').replace(')',
'')) ## 去除一行的左右括号
roadMat = np.loadtxt(dest, dtype=int, skiprows=1,
delimiter=',') ## 读取txt并转换为ndarray
source2 = car_path ## 源文件路径
dest2 = '../config/car1.txt' ## 去除括号后的文件路径
f = open(dest2, "w+")
f.truncate()
with open(source2, 'r') as text:
with open(dest2, 'a+') as car_1: ## 以追加写的方式打开目标文件
for line in text.readlines():
car_1.write(line.replace('(', '').replace(')',
'')) ## 去除一行的左右括号
carMat = np.loadtxt(dest2, dtype=int, skiprows=1,
delimiter=',') ## 读取txt并转换为ndarray
maxSpeed = carMat[:, 3]
from_car = carMat[:, 1]
to_car = carMat[:, 2]
planTime = carMat[:, 4]
carId = carMat[:, 0]
car_amount = len(from_car)
'''
初始化权重矩阵，并运行floyd最短路径寻找程序
'''
# start = time.time() # 计算耗时，单位为s
R_all = []
planTime1 = 0
from_ = roadMat[:, 4]
to_ = roadMat[:, 5]
roadId = (roadMat[:, 0])
with open(answer_path, 'a+') as file:
file = open(answer_path, 'w')
file.truncate()
weight = buildWeight.buildWeight(roadMat, 1e5)
# print(weight.shape)
D, path = floyd.floyd(weight)
for i in range(0, car_amount):
R = floyd.router(D, path, from_car[i], to_car[i])
R1 = [] # 用R1存储道路编号carId
# 实现节点到道路编号的索引查找
for m in range(0, len(R) - 1):
for l in range(0, len(roadId)):
#if from_.tolist().index(R[m])==to_.tolist().index(R[m+1]) or from_.tolist().index(R[m+1])==to_.tolist().index(R[m]):
if from_[l] + to_[l] == R[m] + R[m + 1] and from_[l] - R[
m] + to_[l] - R[m + 1] == 0:
R1.append(roadId[l])
break
if planTime[i] < 3:
planTime1 = planTime[i]
else:
planTime1 = planTime[i] + np.random.randint(1, 500)
R1.insert(0, planTime1)
R1.insert(0, carId[i])
#R.insert(0,'(')
#R.append('/n')
file.write(str(tuple(R1)) + '\n')
maxSpeed=carMat[:,3]
from_car=carMat[:,1]
to_car=carMat[:,2]
planTime=carMat[:,4]
carId=carMat[:,0]
car_amount=len(from_car)
'''
初始化权重矩阵，并运行floyd最短路径寻找程序
'''
start = time.time() # 计算耗时，单位为s
R_all=[]
file=open('answer.txt','w')
file.truncate()
with open('./answer.txt', 'a+') as file:
for i in range(0,car_amount):
weight=buildWeight.buildWeight(roadMat,maxSpeed[i])
#print(weight.shape)
D,path=floyd.floyd(weight)
R=floyd.router(D,path,from_car[i],to_car[i])
R.insert(0, planTime[i])
R.insert(0, carId[i])
#R.insert(0,'(')
#R.append('/n')
file.write(str(tuple(R)) + '\n')
#np.savetxt("answer.txt", R_all)
end = time.time()
print(end-start)