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 135601 vehicles
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_040/trajectory/00_traj_1325.5.json.gz
Loading a file takes 51.29s
Creating data frames takes 20.06s
Filling data types and values takes 5.84s

 Processing a file takes 18.46s
Concatenating time series takes 0.41s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_040/trajectory/01_traj_2090.5.json.gz
Loading a file takes 55.50s
Creating data frames takes 23.68s
Filling data types and values takes 5.80s

 Processing a file takes 17.77s
Concatenating time series takes 0.27s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_040/trajectory/02_traj_2826.0.json.gz
Loading a file takes 55.43s
Creating data frames takes 24.68s
Filling data types and values takes 5.86s

 Processing a file takes 17.54s
Concatenating time series takes 0.25s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_040/trajectory/03_traj_3516.0.json.gz
Loading a file takes 53.19s
Creating data frames takes 24.25s
Filling data types and values takes 5.87s

 Processing a file takes 17.28s
Concatenating time series takes 0.40s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_040/trajectory/04_traj_4213.0.json.gz
Loading a file takes 53.82s
Creating data frames takes 21.36s
Filling data types and values takes 5.90s

 Processing a file takes 19.10s
Concatenating time series takes 0.51s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_040/trajectory/05_traj_4913.5.json.gz
Loading a file takes 55.48s
Creating data frames takes 25.57s
Filling data types and values takes 5.93s

 Processing a file takes 28.04s
Concatenating time series takes 0.55s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_040/trajectory/06_traj_5584.0.json.gz
Loading a file takes 57.78s
Creating data frames takes 24.33s
Filling data types and values takes 5.84s

 Processing a file takes 21.39s
Concatenating time series takes 0.64s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_040/trajectory/07_traj_6248.5.json.gz
Loading a file takes 57.01s
Creating data frames takes 23.00s
Filling data types and values takes 6.41s

 Processing a file takes 18.98s
Concatenating time series takes 0.54s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_040/trajectory/08_traj_6921.5.json.gz
Loading a file takes 60.48s
Creating data frames takes 22.89s
Filling data types and values takes 5.91s

 Processing a file takes 18.47s
Concatenating time series takes 0.56s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_040/trajectory/09_traj_end.json.gz
Loading a file takes 53.13s
Creating data frames takes 19.69s
Filling data types and values takes 5.27s

 Processing a file takes 17.52s
Concatenating time series takes 0.64s
Saving all the section time series takes 86.51s
Saving all the junction time series takes 12.47s
Saving network entrance and exit takes 0.10s
Aggregating the raw statistics to different intervals...

  0%|          | 0/1520 [00:00<?, ?it/s]
  0%|          | 1/1520 [00:00<11:01,  2.30it/s]
  2%|▏         | 24/1520 [00:00<00:26, 56.41it/s]
  4%|▍         | 59/1520 [00:00<00:11, 130.76it/s]
  6%|▌         | 94/1520 [00:00<00:07, 188.38it/s]
  8%|▊         | 122/1520 [00:00<00:06, 208.16it/s]
 10%|█         | 152/1520 [00:00<00:06, 226.25it/s]
 12%|█▏        | 179/1520 [00:01<00:06, 218.17it/s]
 13%|█▎        | 204/1520 [00:01<00:06, 219.07it/s]
 15%|█▌        | 233/1520 [00:01<00:05, 235.56it/s]
 17%|█▋        | 263/1520 [00:01<00:05, 241.46it/s]
 19%|█▉        | 291/1520 [00:01<00:04, 247.87it/s]
 21%|██        | 317/1520 [00:02<00:15, 76.15it/s] 
 23%|██▎       | 349/1520 [00:02<00:11, 101.66it/s]
 25%|██▌       | 382/1520 [00:02<00:08, 131.03it/s]
 27%|██▋       | 411/1520 [00:02<00:07, 154.57it/s]
 29%|██▉       | 437/1520 [00:02<00:06, 172.38it/s]
 30%|███       | 463/1520 [00:03<00:05, 186.52it/s]
 32%|███▏      | 488/1520 [00:03<00:05, 193.68it/s]
 34%|███▎      | 512/1520 [00:03<00:05, 200.04it/s]
 35%|███▌      | 536/1520 [00:03<00:05, 192.51it/s]
 37%|███▋      | 558/1520 [00:03<00:05, 181.64it/s]
 38%|███▊      | 578/1520 [00:03<00:05, 183.54it/s]
 40%|███▉      | 601/1520 [00:03<00:04, 188.81it/s]
 41%|████      | 625/1520 [00:03<00:04, 201.50it/s]
 43%|████▎     | 652/1520 [00:03<00:04, 209.47it/s]
 45%|████▌     | 684/1520 [00:04<00:03, 234.90it/s]
 47%|████▋     | 709/1520 [00:04<00:03, 228.08it/s]
 48%|████▊     | 733/1520 [00:04<00:03, 221.29it/s]
 50%|████▉     | 756/1520 [00:04<00:03, 216.34it/s]
 51%|█████     | 778/1520 [00:04<00:03, 210.28it/s]
 53%|█████▎    | 800/1520 [00:04<00:03, 211.25it/s]
 54%|█████▍    | 822/1520 [00:04<00:03, 213.29it/s]
 56%|█████▌    | 844/1520 [00:04<00:03, 212.64it/s]
 57%|█████▋    | 867/1520 [00:04<00:03, 208.39it/s]
 59%|█████▉    | 893/1520 [00:05<00:02, 217.43it/s]
 60%|██████    | 917/1520 [00:05<00:02, 222.56it/s]
 62%|██████▏   | 940/1520 [00:05<00:02, 222.24it/s]
 64%|██████▍   | 970/1520 [00:05<00:02, 230.82it/s]
 66%|██████▌   | 998/1520 [00:05<00:02, 243.40it/s]
 67%|██████▋   | 1023/1520 [00:05<00:02, 232.75it/s]
 69%|██████▉   | 1047/1520 [00:05<00:02, 221.10it/s]
 71%|███████   | 1072/1520 [00:05<00:01, 224.52it/s]
 73%|███████▎  | 1105/1520 [00:05<00:01, 246.12it/s]
 74%|███████▍  | 1130/1520 [00:06<00:01, 238.90it/s]
 76%|███████▌  | 1156/1520 [00:06<00:01, 240.30it/s]
 78%|███████▊  | 1183/1520 [00:06<00:01, 231.45it/s]
 80%|███████▉  | 1213/1520 [00:06<00:01, 248.42it/s]
 82%|████████▏ | 1243/1520 [00:06<00:01, 253.16it/s]
 84%|████████▎ | 1271/1520 [00:06<00:00, 259.02it/s]
 85%|████████▌ | 1298/1520 [00:06<00:00, 261.85it/s]
 87%|████████▋ | 1325/1520 [00:06<00:00, 242.66it/s]
 89%|████████▉ | 1350/1520 [00:06<00:00, 220.66it/s]
 90%|█████████ | 1373/1520 [00:08<00:02, 62.64it/s] 
 92%|█████████▏| 1393/1520 [00:08<00:01, 74.69it/s]
 93%|█████████▎| 1419/1520 [00:08<00:01, 95.79it/s]
 95%|█████████▌| 1444/1520 [00:08<00:00, 116.78it/s]
 96%|█████████▋| 1466/1520 [00:08<00:00, 133.52it/s]
 98%|█████████▊| 1489/1520 [00:08<00:00, 152.04it/s]
100%|██████████| 1520/1520 [00:08<00:00, 175.61it/s]
Constructing time series for each modality ...
Saving aggregated time series to /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_040/timeseries/agg_timeseries.pkl
Extracting samples from time series ...
number of samples: 20
Packing the samples into numpy arrays ...