import random import numpy as np import math from sklearn.cluster import KMeans #定义状态空间，每个时间片是一个决策阶段，时间片结束点的时刻为决策点 # 划分时间片，划分成了从0-100min的10个决策片，也就是我们整个过程的决策点，在每个时间片的右区间做出决策 scene = [] time_slices = np.linspace(0, 100, 11) # def calculate_distance(p1, p2): # # 计算两点之间的欧几里得距离 # return ((p1[0] - p2[0]) ** 2 + (p1[1] - p2[1]) ** 2) ** 0.5 # 生成随机场景 for i in range(len(time_slices) - 1): start_time, end_time = time_slices[i], time_slices[i + 1] order_counts = np.random.poisson(4) # 每个时间段平均有4个订单 driver_counts = np.random.poisson(2) # 每个时间段平均有2个司机 decision_id = i + 1 decision_time = time_slices[i + 1] for j in range(order_counts): order_id =j+1 #order_time = int(random.uniform(start_time, end_time)) order_x, order_y = int(random.uniform(0, 10)), int(random.uniform(0, 10)) order_state = 1 for m in range(driver_counts): driver1_id = m + 1 # driver1_time = int(random.uniform(start_time, end_time)) driver1_x, driver1_y = int(random.uniform(0, 10)), int(random.uniform(0, 10)) driver1_deadline = 100 scene.append({"决策阶段":decision_id,"决策时间":decision_time,"订单编号":order_id,"坐标":(order_x, order_y),"订单状态":order_state},"司机编号":driver1_id,"司机目的地":(driver1_x, driver1_y),"初始路径":[(0,0),(driver1_x, driver1_y)],"最晚可用时间":driver1_deadline})

There seems to be a syntax error in your code. You need to properly format your code by adding indentation after the for loop statements. Here's the corrected code:

import random
import numpy as np
import math
from sklearn.cluster import KMeans

#定义状态空间，每个时间片是一个决策阶段，时间片结束点的时刻为决策点
# 划分时间片，划分成了从0-100min的10个决策片，也就是我们整个过程的决策点，在每个时间片的右区间做出决策
scene = []
time_slices = np.linspace(0, 100, 11)

# def calculate_distance(p1, p2):
#     # 计算两点之间的欧几里得距离
#     return ((p1[0] - p2[0]) ** 2 + (p1[1] - p2[1]) ** 2) ** 0.5

# 生成随机场景
for i in range(len(time_slices) - 1):
    start_time, end_time = time_slices[i], time_slices[i + 1]
    order_counts = np.random.poisson(4)  # 每个时间段平均有4个订单
    driver_counts = np.random.poisson(2)  # 每个时间段平均有2个司机
    decision_id = i + 1
    decision_time = time_slices[i + 1]
    for j in range(order_counts):
        order_id =j+1
        #order_time = int(random.uniform(start_time, end_time))
        order_x, order_y = int(random.uniform(0, 10)), int(random.uniform(0, 10))
        order_state = 1
        for m in range(driver_counts):
            driver1_id = m + 1
            # driver1_time = int(random.uniform(start_time, end_time))
            driver1_x, driver1_y = int(random.uniform(0, 10)), int(random.uniform(0, 10))
            driver1_deadline = 100
            scene.append({"决策阶段":decision_id,"决策时间":decision_time,"订单编号":order_id,"坐标":(order_x, order_y),"订单状态":order_state,"司机编号":driver1_id,"司机目的地":(driver1_x, driver1_y),"初始路径":[(0,0),(driver1_x, driver1_y)],"最晚可用时间":driver1_deadline})