INFO: Pandarallel will run on 8 workers.
INFO: Pandarallel will use Memory file system to transfer data between the main process and workers.

 Selecting 5.0% vehicles from 138083 vehicles
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_033/trajectory/00_traj_1326.0.json.gz
Loading a file takes 52.62s
Creating data frames takes 19.30s
Filling data types and values takes 5.82s

 Processing a file takes 17.86s
Concatenating time series takes 0.42s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_033/trajectory/01_traj_2110.5.json.gz
Loading a file takes 57.64s
Creating data frames takes 23.71s
Filling data types and values takes 5.92s

 Processing a file takes 17.08s
Concatenating time series takes 0.29s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_033/trajectory/02_traj_2853.0.json.gz
Loading a file takes 58.14s
Creating data frames takes 21.73s
Filling data types and values takes 5.88s

 Processing a file takes 17.08s
Concatenating time series takes 0.39s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_033/trajectory/03_traj_3590.5.json.gz
Loading a file takes 50.76s
Creating data frames takes 22.15s
Filling data types and values takes 5.79s

 Processing a file takes 17.40s
Concatenating time series takes 0.35s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_033/trajectory/04_traj_4325.0.json.gz
Loading a file takes 54.36s
Creating data frames takes 20.85s
Filling data types and values takes 5.55s

 Processing a file takes 17.30s
Concatenating time series takes 0.64s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_033/trajectory/05_traj_5044.0.json.gz
Loading a file takes 51.06s
Creating data frames takes 21.78s
Filling data types and values takes 5.54s

 Processing a file takes 30.63s
Concatenating time series takes 0.58s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_033/trajectory/06_traj_5752.5.json.gz
Loading a file takes 60.39s
Creating data frames takes 21.82s
Filling data types and values takes 5.79s

 Processing a file takes 18.81s
Concatenating time series takes 0.70s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_033/trajectory/07_traj_6445.5.json.gz
Loading a file takes 57.11s
Creating data frames takes 20.93s
Filling data types and values takes 5.91s

 Processing a file takes 18.31s
Concatenating time series takes 0.67s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_033/trajectory/08_traj_7149.5.json.gz
Loading a file takes 55.33s
Creating data frames takes 20.09s
Filling data types and values takes 5.68s

 Processing a file takes 18.08s
Concatenating time series takes 0.47s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_033/trajectory/09_traj_end.json.gz
Loading a file takes 30.10s
Creating data frames takes 9.11s
Filling data types and values takes 2.55s

 Processing a file takes 14.55s
Concatenating time series takes 0.59s
Saving all the section time series takes 82.33s
Saving all the junction time series takes 12.10s
Saving network entrance and exit takes 0.10s
Aggregating the raw statistics to different intervals...

  0%|          | 0/1516 [00:00<?, ?it/s]
  0%|          | 1/1516 [00:00<12:25,  2.03it/s]
  0%|          | 7/1516 [00:00<02:32,  9.89it/s]
  8%|▊         | 118/1516 [00:00<00:06, 201.43it/s]
 11%|█         | 170/1516 [00:01<00:07, 190.71it/s]
 14%|█▎        | 208/1516 [00:01<00:06, 198.91it/s]
 16%|█▌        | 241/1516 [00:01<00:05, 219.10it/s]
 18%|█▊        | 273/1516 [00:01<00:05, 226.49it/s]
 20%|█▉        | 303/1516 [00:01<00:05, 240.35it/s]
 22%|██▏       | 333/1516 [00:02<00:15, 76.53it/s] 
 25%|██▍       | 378/1516 [00:02<00:10, 110.11it/s]
 27%|██▋       | 410/1516 [00:03<00:08, 133.30it/s]
 29%|██▉       | 439/1516 [00:03<00:07, 153.18it/s]
 31%|███       | 468/1516 [00:03<00:06, 161.53it/s]
 33%|███▎      | 494/1516 [00:03<00:06, 158.57it/s]
 34%|███▍      | 517/1516 [00:03<00:06, 163.89it/s]
 36%|███▌      | 539/1516 [00:03<00:05, 166.44it/s]
 37%|███▋      | 559/1516 [00:03<00:05, 165.03it/s]
 38%|███▊      | 582/1516 [00:03<00:05, 176.65it/s]
 40%|███▉      | 602/1516 [00:04<00:05, 174.10it/s]
 41%|████▏     | 626/1516 [00:04<00:04, 189.82it/s]
 43%|████▎     | 649/1516 [00:04<00:04, 199.87it/s]
 44%|████▍     | 672/1516 [00:04<00:04, 207.02it/s]
 46%|████▌     | 695/1516 [00:04<00:03, 209.83it/s]
 47%|████▋     | 719/1516 [00:04<00:03, 217.67it/s]
 49%|████▉     | 742/1516 [00:04<00:03, 217.55it/s]
 50%|█████     | 765/1516 [00:04<00:03, 200.19it/s]
 52%|█████▏    | 786/1516 [00:04<00:03, 188.45it/s]
 53%|█████▎    | 809/1516 [00:05<00:03, 194.16it/s]
 55%|█████▌    | 835/1516 [00:05<00:03, 211.27it/s]
 57%|█████▋    | 860/1516 [00:05<00:03, 217.20it/s]
 59%|█████▊    | 888/1516 [00:05<00:02, 230.59it/s]
 60%|██████    | 912/1516 [00:05<00:02, 229.26it/s]
 62%|██████▏   | 936/1516 [00:05<00:02, 227.65it/s]
 64%|██████▎   | 966/1516 [00:05<00:02, 247.58it/s]
 65%|██████▌   | 991/1516 [00:05<00:02, 240.96it/s]
 67%|██████▋   | 1016/1516 [00:05<00:02, 241.26it/s]
 69%|██████▊   | 1041/1516 [00:06<00:02, 236.06it/s]
 70%|███████   | 1065/1516 [00:06<00:01, 228.90it/s]
 72%|███████▏  | 1092/1516 [00:06<00:01, 235.68it/s]
 74%|███████▎  | 1116/1516 [00:06<00:01, 233.99it/s]
 75%|███████▌  | 1143/1516 [00:06<00:01, 242.59it/s]
 77%|███████▋  | 1168/1516 [00:06<00:01, 243.77it/s]
 79%|███████▉  | 1194/1516 [00:06<00:01, 247.23it/s]
 80%|████████  | 1219/1516 [00:06<00:01, 244.28it/s]
 82%|████████▏ | 1250/1516 [00:06<00:01, 260.76it/s]
 85%|████████▍ | 1282/1516 [00:06<00:00, 275.43it/s]
 86%|████████▋ | 1310/1516 [00:07<00:00, 272.89it/s]
 88%|████████▊ | 1338/1516 [00:07<00:00, 249.77it/s]
 90%|████████▉ | 1364/1516 [00:08<00:02, 69.13it/s] 
 91%|█████████▏| 1385/1516 [00:08<00:01, 82.11it/s]
 93%|█████████▎| 1411/1516 [00:08<00:01, 103.08it/s]
 95%|█████████▍| 1434/1516 [00:08<00:00, 119.44it/s]
 96%|█████████▌| 1459/1516 [00:08<00:00, 140.22it/s]
 98%|█████████▊| 1486/1516 [00:08<00:00, 161.61it/s]
100%|██████████| 1516/1516 [00:08<00:00, 170.27it/s]
Constructing time series for each modality ...
Saving aggregated time series to /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_033/timeseries/agg_timeseries.pkl
Extracting samples from time series ...
number of samples: 20
Packing the samples into numpy arrays ...