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 115278 vehicles
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_001/trajectory/00_traj_1344.5.json.gz
Loading a file takes 52.48s
Creating data frames takes 21.41s
Filling data types and values takes 5.82s

 Processing a file takes 18.72s
Concatenating time series takes 0.44s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_001/trajectory/01_traj_2309.0.json.gz
Loading a file takes 55.93s
Creating data frames takes 22.04s
Filling data types and values takes 5.84s

 Processing a file takes 19.20s
Concatenating time series takes 0.30s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_001/trajectory/02_traj_3231.0.json.gz
Loading a file takes 57.21s
Creating data frames takes 21.59s
Filling data types and values takes 5.70s

 Processing a file takes 18.14s
Concatenating time series takes 0.28s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_001/trajectory/03_traj_4124.0.json.gz
Loading a file takes 53.81s
Creating data frames takes 21.70s
Filling data types and values takes 5.77s

 Processing a file takes 17.63s
Concatenating time series takes 0.36s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_001/trajectory/04_traj_4997.5.json.gz
Loading a file takes 55.19s
Creating data frames takes 21.92s
Filling data types and values takes 5.53s

 Processing a file takes 17.13s
Concatenating time series takes 0.50s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_001/trajectory/05_traj_5833.5.json.gz
Loading a file takes 51.22s
Creating data frames takes 20.27s
Filling data types and values takes 5.56s

 Processing a file takes 28.84s
Concatenating time series takes 0.52s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_001/trajectory/06_traj_6636.0.json.gz
Loading a file takes 56.77s
Creating data frames takes 20.72s
Filling data types and values takes 5.48s

 Processing a file takes 35.11s
Concatenating time series takes 0.50s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_001/trajectory/07_traj_7502.0.json.gz
Loading a file takes 58.31s
Creating data frames takes 21.64s
Filling data types and values takes 5.80s

 Processing a file takes 18.65s
Concatenating time series takes 0.82s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_001/trajectory/08_traj_end.json.gz
Loading a file takes 29.98s
Creating data frames takes 10.93s
Filling data types and values takes 3.02s

 Processing a file takes 12.28s
Concatenating time series takes 0.23s
Saving all the section time series takes 80.92s
Saving all the junction time series takes 11.11s
Saving network entrance and exit takes 0.08s
Aggregating the raw statistics to different intervals...

  0%|          | 0/1520 [00:00<?, ?it/s]
  0%|          | 1/1520 [00:00<09:52,  2.56it/s]
  1%|          | 13/1520 [00:00<00:44, 33.98it/s]
  2%|▏         | 35/1520 [00:00<00:17, 82.58it/s]
  5%|▍         | 75/1520 [00:00<00:08, 170.13it/s]
  7%|▋         | 112/1520 [00:00<00:06, 220.71it/s]
  9%|▉         | 140/1520 [00:00<00:06, 222.59it/s]
 11%|█         | 166/1520 [00:01<00:06, 222.75it/s]
 13%|█▎        | 191/1520 [00:01<00:06, 214.51it/s]
 14%|█▍        | 218/1520 [00:01<00:05, 223.72it/s]
 16%|█▋        | 248/1520 [00:01<00:05, 238.51it/s]
 18%|█▊        | 273/1520 [00:01<00:05, 236.84it/s]
 20%|█▉        | 298/1520 [00:01<00:05, 235.16it/s]
 21%|██        | 322/1520 [00:02<00:17, 70.20it/s] 
 23%|██▎       | 351/1520 [00:02<00:12, 92.86it/s]
 25%|██▌       | 387/1520 [00:02<00:09, 124.07it/s]
 28%|██▊       | 426/1520 [00:02<00:06, 163.52it/s]
 30%|██▉       | 454/1520 [00:03<00:05, 181.66it/s]
 32%|███▏      | 481/1520 [00:03<00:05, 184.98it/s]
 33%|███▎      | 506/1520 [00:03<00:05, 187.75it/s]
 35%|███▍      | 530/1520 [00:03<00:05, 195.30it/s]
 36%|███▋      | 553/1520 [00:03<00:05, 188.24it/s]
 38%|███▊      | 577/1520 [00:03<00:04, 194.34it/s]
 39%|███▉      | 599/1520 [00:03<00:04, 191.89it/s]
 41%|████      | 622/1520 [00:03<00:04, 197.97it/s]
 42%|████▏     | 643/1520 [00:03<00:04, 195.42it/s]
 44%|████▍     | 671/1520 [00:04<00:03, 213.68it/s]
 46%|████▌     | 694/1520 [00:04<00:03, 212.95it/s]
 47%|████▋     | 720/1520 [00:04<00:03, 225.22it/s]
 49%|████▉     | 743/1520 [00:04<00:03, 226.51it/s]
 50%|█████     | 766/1520 [00:04<00:03, 215.14it/s]
 52%|█████▏    | 788/1520 [00:04<00:03, 213.73it/s]
 53%|█████▎    | 810/1520 [00:04<00:03, 215.19it/s]
 55%|█████▍    | 835/1520 [00:04<00:03, 223.87it/s]
 57%|█████▋    | 862/1520 [00:04<00:02, 236.54it/s]
 58%|█████▊    | 886/1520 [00:05<00:02, 228.20it/s]
 60%|█████▉    | 909/1520 [00:05<00:02, 225.22it/s]
 61%|██████▏   | 932/1520 [00:05<00:02, 221.26it/s]
 63%|██████▎   | 965/1520 [00:05<00:02, 249.67it/s]
 65%|██████▌   | 991/1520 [00:05<00:02, 247.68it/s]
 67%|██████▋   | 1017/1520 [00:05<00:02, 250.32it/s]
 69%|██████▊   | 1043/1520 [00:05<00:01, 239.61it/s]
 70%|███████   | 1068/1520 [00:05<00:01, 238.32it/s]
 72%|███████▏  | 1092/1520 [00:05<00:01, 228.19it/s]
 73%|███████▎  | 1115/1520 [00:06<00:01, 221.63it/s]
 75%|███████▍  | 1139/1520 [00:06<00:01, 223.07it/s]
 77%|███████▋  | 1170/1520 [00:06<00:01, 245.19it/s]
 79%|███████▊  | 1195/1520 [00:06<00:01, 233.12it/s]
 80%|████████  | 1219/1520 [00:06<00:01, 226.66it/s]
 82%|████████▏ | 1253/1520 [00:06<00:01, 257.94it/s]
 84%|████████▍ | 1280/1520 [00:06<00:00, 253.35it/s]
 86%|████████▋ | 1313/1520 [00:06<00:00, 251.30it/s]
 88%|████████▊ | 1339/1520 [00:06<00:00, 252.93it/s]
 90%|████████▉ | 1365/1520 [00:07<00:02, 68.60it/s] 
 92%|█████████▏| 1391/1520 [00:08<00:01, 85.40it/s]
 93%|█████████▎| 1416/1520 [00:08<00:01, 103.85it/s]
 95%|█████████▍| 1442/1520 [00:08<00:00, 120.77it/s]
 97%|█████████▋| 1467/1520 [00:08<00:00, 139.47it/s]
 98%|█████████▊| 1492/1520 [00:08<00:00, 155.04it/s]
100%|██████████| 1520/1520 [00:08<00:00, 176.46it/s]
Constructing time series for each modality ...
Saving aggregated time series to /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_001/timeseries/agg_timeseries.pkl
Extracting samples from time series ...
number of samples: 20
Packing the samples into numpy arrays ...