File size: 7,592 Bytes
baa3847 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 | 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 141607 vehicles
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_048/trajectory/00_traj_1305.5.json.gz
Loading a file takes 49.96s
Creating data frames takes 20.05s
Filling data types and values takes 5.97s
Processing a file takes 18.94s
Concatenating time series takes 0.39s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_048/trajectory/01_traj_2050.5.json.gz
Loading a file takes 57.77s
Creating data frames takes 25.99s
Filling data types and values takes 6.20s
Processing a file takes 19.35s
Concatenating time series takes 0.31s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_048/trajectory/02_traj_2764.0.json.gz
Loading a file takes 59.50s
Creating data frames takes 22.00s
Filling data types and values takes 6.10s
Processing a file takes 19.03s
Concatenating time series takes 0.26s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_048/trajectory/03_traj_3467.0.json.gz
Loading a file takes 54.33s
Creating data frames takes 25.69s
Filling data types and values takes 6.11s
Processing a file takes 18.73s
Concatenating time series takes 0.37s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_048/trajectory/04_traj_4164.0.json.gz
Loading a file takes 59.21s
Creating data frames takes 21.37s
Filling data types and values takes 5.88s
Processing a file takes 19.50s
Concatenating time series takes 0.34s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_048/trajectory/05_traj_4860.5.json.gz
Loading a file takes 54.85s
Creating data frames takes 20.46s
Filling data types and values takes 5.88s
Processing a file takes 21.54s
Concatenating time series takes 0.53s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_048/trajectory/06_traj_5552.5.json.gz
Loading a file takes 56.57s
Creating data frames takes 20.08s
Filling data types and values takes 5.87s
Processing a file takes 22.75s
Concatenating time series takes 0.58s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_048/trajectory/07_traj_6238.5.json.gz
Loading a file takes 60.33s
Creating data frames takes 21.84s
Filling data types and values takes 5.91s
Processing a file takes 19.11s
Concatenating time series takes 0.68s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_048/trajectory/08_traj_6923.5.json.gz
Loading a file takes 60.08s
Creating data frames takes 21.93s
Filling data types and values takes 6.18s
Processing a file takes 19.46s
Concatenating time series takes 0.58s
Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_048/trajectory/09_traj_end.json.gz
Loading a file takes 53.81s
Creating data frames takes 17.20s
Filling data types and values takes 5.08s
Processing a file takes 18.70s
Concatenating time series takes 0.77s
Saving all the section time series takes 88.14s
Saving all the junction time series takes 12.60s
Saving network entrance and exit takes 0.09s
Aggregating the raw statistics to different intervals...
0%| | 0/1516 [00:00<?, ?it/s]
0%| | 1/1516 [00:00<10:54, 2.32it/s]
2%|β | 29/1516 [00:00<00:21, 69.57it/s]
3%|β | 47/1516 [00:00<00:15, 97.35it/s]
5%|β | 81/1516 [00:00<00:09, 158.26it/s]
8%|β | 117/1516 [00:00<00:06, 207.87it/s]
10%|β | 147/1516 [00:00<00:06, 227.83it/s]
11%|ββ | 174/1516 [00:01<00:05, 230.79it/s]
13%|ββ | 200/1516 [00:01<00:05, 232.30it/s]
15%|ββ | 225/1516 [00:01<00:05, 236.46it/s]
17%|ββ | 253/1516 [00:01<00:05, 242.28it/s]
18%|ββ | 279/1516 [00:01<00:05, 240.23it/s]
20%|ββ | 307/1516 [00:01<00:04, 245.97it/s]
22%|βββ | 333/1516 [00:02<00:16, 73.14it/s]
24%|βββ | 365/1516 [00:02<00:11, 99.02it/s]
27%|βββ | 402/1516 [00:02<00:08, 133.28it/s]
28%|βββ | 428/1516 [00:02<00:07, 149.55it/s]
30%|βββ | 453/1516 [00:03<00:06, 163.46it/s]
32%|ββββ | 478/1516 [00:03<00:06, 169.07it/s]
33%|ββββ | 501/1516 [00:03<00:05, 174.09it/s]
34%|ββββ | 523/1516 [00:03<00:05, 168.23it/s]
36%|ββββ | 543/1516 [00:03<00:05, 163.46it/s]
37%|ββββ | 562/1516 [00:03<00:06, 152.25it/s]
39%|ββββ | 589/1516 [00:03<00:05, 173.64it/s]
40%|ββββ | 612/1516 [00:03<00:05, 177.74it/s]
42%|βββββ | 644/1516 [00:04<00:04, 212.03it/s]
44%|βββββ | 673/1516 [00:04<00:03, 229.63it/s]
46%|βββββ | 699/1516 [00:04<00:03, 233.62it/s]
48%|βββββ | 724/1516 [00:04<00:03, 237.70it/s]
49%|βββββ | 750/1516 [00:04<00:03, 232.55it/s]
51%|βββββ | 774/1516 [00:04<00:03, 215.72it/s]
53%|ββββββ | 797/1516 [00:04<00:03, 206.75it/s]
54%|ββββββ | 819/1516 [00:04<00:03, 206.04it/s]
55%|ββββββ | 840/1516 [00:04<00:03, 204.77it/s]
57%|ββββββ | 864/1516 [00:05<00:03, 213.88it/s]
59%|ββββββ | 888/1516 [00:05<00:02, 220.56it/s]
60%|ββββββ | 911/1516 [00:05<00:02, 206.78it/s]
61%|βββββββ | 932/1516 [00:05<00:02, 200.16it/s]
63%|βββββββ | 961/1516 [00:05<00:02, 220.62it/s]
65%|βββββββ | 985/1516 [00:05<00:02, 222.53it/s]
66%|βββββββ | 1008/1516 [00:05<00:02, 208.31it/s]
68%|βββββββ | 1030/1516 [00:05<00:02, 209.54it/s]
69%|βββββββ | 1052/1516 [00:05<00:02, 208.72it/s]
71%|βββββββ | 1079/1516 [00:06<00:01, 223.97it/s]
73%|ββββββββ | 1102/1516 [00:06<00:01, 220.43it/s]
74%|ββββββββ | 1127/1516 [00:06<00:01, 216.46it/s]
76%|ββββββββ | 1153/1516 [00:06<00:01, 226.26it/s]
78%|ββββββββ | 1183/1516 [00:06<00:01, 246.86it/s]
80%|ββββββββ | 1208/1516 [00:06<00:01, 243.65it/s]
82%|βββββββββ | 1238/1516 [00:06<00:01, 258.49it/s]
84%|βββββββββ | 1268/1516 [00:06<00:00, 269.90it/s]
85%|βββββββββ | 1296/1516 [00:06<00:00, 263.92it/s]
87%|βββββββββ | 1323/1516 [00:07<00:00, 248.53it/s]
89%|βββββββββ | 1349/1516 [00:07<00:00, 227.69it/s]
91%|βββββββββ | 1373/1516 [00:08<00:02, 59.26it/s]
92%|ββββββββββ| 1397/1516 [00:08<00:01, 73.71it/s]
94%|ββββββββββ| 1420/1516 [00:08<00:01, 90.47it/s]
95%|ββββββββββ| 1443/1516 [00:08<00:00, 108.07it/s]
97%|ββββββββββ| 1463/1516 [00:08<00:00, 122.33it/s]
98%|ββββββββββ| 1485/1516 [00:08<00:00, 140.29it/s]
100%|ββββββββββ| 1516/1516 [00:08<00:00, 169.01it/s]
Constructing time series for each modality ...
Saving aggregated time series to /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_048/timeseries/agg_timeseries.pkl
Extracting samples from time series ...
number of samples: 20
Packing the samples into numpy arrays ...
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