添加标签

对向左向右换道数据添加不同的标签

#!/usr/bin/env python
# coding: utf-8

# In[1]:


import csv
import pandas as pd
f2=pd.read_csv("./CL_train41.csv")
f2


# In[2]:


# TR_row=[]
# for i in range(len(f2)):
#     if i==0:
#         continue
#     else:
#         if f2['Vehicle_ID'][i]==f2['Vehicle_ID'][i-1] and f2['Lane_ID'][i]==f2['Lane_ID'][i-1]+1:
#             TR_row.extend(i-a for a in range(40))
# TR_row


# In[3]:


CL_num=int(len(f2)/41)
obj_list=[41*i-1 for i in range(CL_num+1)]
obj_list=obj_list[1:]
obj_list


# In[4]:


TR_row=[]
for i in obj_list:
    if f2['Vehicle_ID'][i]==f2['Vehicle_ID'][i-1] and f2['Lane_ID'][i]==f2['Lane_ID'][i-1]+1:
        TR_row.extend(i-40+a for a in range(40))
TL_row=[]
for i in obj_list:
    if f2['Vehicle_ID'][i]==f2['Vehicle_ID'][i-1] and f2['Lane_ID'][i]==f2['Lane_ID'][i-1]-1:
        TL_row.extend(i-40+a for a in range(40))
TL_row  


# In[5]:


TR40=f2.loc[TR_row]
TR40['label']=2
TL40=f2.loc[TL_row]
TL40['label']=1
TR40


# In[6]:


df_combine = pd.concat([TR40, TL40], ignore_index=True)
df_combine.to_csv("./RL_label.csv",index=False)
# TR40.to_csv("/home/mt/learn/NGSIM数据处理/csv/80/5:15-5:30/TR_label.csv",index=False)


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特征标准化

#!/usr/bin/env python
# coding: utf-8

# In[1]:


import csv
import pandas as pd
f=pd.read_csv("./KL_train40.csv")
f2=pd.read_csv("./RL_label.csv")
# f3=pd.read_csv("/home/mt/learn/NGSIM数据处理/csv/80/算法数据/TR_label.csv")
f


# In[2]:


import numpy as np
def normalize(train):
  train_norm = train.apply(lambda x: (x - np.mean(x)) / (np.max(x) - np.min(x)))
  return train_norm


# In[3]:


F1=f[['Vehicle_ID','Frame_ID','Local_X','Local_Y','v_Class','v_Vel','v_Acc','Lane_ID','x_a','label']]
F2=f2[['Vehicle_ID','Frame_ID','Local_X','Local_Y','v_Class','v_Vel','v_Acc','Lane_ID','x_a','label']]


# In[4]:


df_combine = pd.concat([F1,F2], ignore_index=True)
df_combine.to_csv("./Doubel_label.csv",index=False)
# df_combine=normalize(df_combine)
# df_combine.to_csv("/home/mt/learn/NGSIM数据处理/csv/80/4:00-4:15/frame_id/Doubel_label.csv",index=False)


# In[8]:


df_combine = pd.concat([F1,F2], ignore_index=True)
df_combine.to_csv("/home/mt/learn/NGSIM数据处理/csv/101/8:20-8:35/Doubel_label.csv",index=False)
df_combine=normalize(df_combine)
df_combine.to_csv("/home/mt/learn/NGSIM数据处理/csv/101/8:20-8:35/Double_train.csv",index=False)