commit

src/python3/pjibot_outdoor/jiqiren_outdoor.py

@@ -113,10 +113,11 @@ class Batchrun:
             return posdata
 
         map_id = get_map_id(posdata_ego)
+        # map_id = 0
         posdata_obs = trans_pos(posdata_obs, map_id)
         posdata_ego = trans_pos(posdata_ego, map_id)
-        posdata_obs['simtime'] = posdata_obs['simtime'].round(1)
-        posdata_ego['simtime'] = posdata_ego['simtime'].round(1)
+        posdata_obs['simtime'] = np.round(posdata_obs['simtime'], decimals=1)
+        posdata_ego['simtime'] = np.round(posdata_ego['simtime'], decimals=1)
 
         # 对障碍物数据进行处理
         def filter_rows(group):
@@ -134,10 +135,9 @@ class Batchrun:
 
             # 2. 创建新的DataFrame，并与原始DataFrame对齐
             new_df = pd.DataFrame(new_simtime, columns=['simtime'])
-
+            new_df['simtime'] = np.round(new_df['simtime'], decimals=1)
             # 3. 将原始DataFrame与新simtime进行合并
             new_df = pd.merge(new_df, df, on='simtime', how='left')
-
             # 4. 对列进行插值（线性插值）
             new_df = new_df.interpolate(method='linear')
 
@@ -464,10 +464,10 @@ class Batchrun:
 
 
 if __name__ == "__main__":
-    # rootPath = "/media/hancheng/Simulation5/anqing/11_5"  # 跟车
+    # rootPath = "/media/hancheng/Simulation5/pujin/pujin_outdoor/11_12"  # 跟车
+    # vehicle_type = "0"
     rootPath = sys.argv[1]
     vehicle_type = sys.argv[2]
-    # vehicle_type = "0"
     # 生成场景
     a = Batchrun(rootPath, "pos_pji.csv")
     a.batchRun(rootPath, vehicle_type)  # 0为占位参数