关于heads.npy中的数据是怎么生成的
HeYuwei9 opened this issue · comments
请问[depature, total_dis, total_time, total_len, avg_dis, avg_speed, sid, eid]这些属性是怎么计算的呢？
heads.npy中的数量和轨迹数量相同，是哪一个时间的chengdu数据呀
期待收到您的回复，这将对我很有帮助！
你好，[depature, total_dis, total_time, total_len, avg_dis, avg_speed]均为数据自带的属性，sid, eid可以理解为将城市划为网格状后，对应的起点终点编码。这里面提供的heads.npy数据是随机采样了一部分，没有具体对应哪一时间段。谢谢！
这些属性可以通过计算得到，数据集需要授权才能公开，很抱歉。获取你可以参考这个https://github.com/Yasoz/SynMob
Hi there, thank you so much for making your code available.
I have access to the Didi Chuxing dataset and also had some questions regarding the properties within the head.npy dataset. Since departure is a categorical feature (288 range), is this the day divided into 5 minute intervals? Also could you explain what the total_len feature is measuring if we already have total_dis, and total_time?
Thanks in advance!
Thanks for your interest.
Yes, we divide the departure time into 5-minute intervals, so it has 288 categorical. The total_len feature is used to record the length of GPS points. total_dis and total_time are denoted by the distance and travel time for a trip, respectively.
Hi there, thank you so much for making your code available.
I have access to the Didi Chuxing dataset and also had some questions regarding the properties within the head.npy dataset. Since departure is a categorical feature (288 range), is this the day divided into 5 minute intervals? Also could you explain what the total_len feature is measuring if we already have total_dis, and total_time?
Thanks in advance!