10000个
时间: 2023-10-01 17:11:27 浏览: 36
好的,根据你提供的代码,我已经帮你生成了10000个场景,你可以通过以下代码来获取这些场景:
```python
import random
import numpy as np
import math
#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
num_scenes = 10000
scenes = []
time_slices = np.linspace(0, 100, 11)
# 生成单个随机场景
for i in range(num_scenes):
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_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_x, driver1_y = int(random.uniform(0, 10)), int(random.uniform(0, 10))
driver1_deadline = 100
scenes.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}])
```
所有的场景都被存储在变量 `scenes` 中,它是一个包含10000个场景的列表,每个场景是一个字典组成的列表。每个字典代表一个状态,包含了决策阶段、决策时间、订单编号、坐标、订单状态、司机编号、司机目的地、初始路径、最晚可用时间等信息。