| 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 122851 vehicles |
| Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_013/trajectory/00_traj_1351.5.json.gz |
| Loading a file takes 49.14s |
| Creating data frames takes 25.17s |
| Filling data types and values takes 6.05s |
|
|
| Processing a file takes 17.69s |
| Concatenating time series takes 0.50s |
| Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_013/trajectory/01_traj_2224.0.json.gz |
| Loading a file takes 57.89s |
| Creating data frames takes 31.56s |
| Filling data types and values takes 6.08s |
|
|
| Processing a file takes 18.50s |
| Concatenating time series takes 0.27s |
| Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_013/trajectory/02_traj_3083.0.json.gz |
| Loading a file takes 61.49s |
| Creating data frames takes 26.87s |
| Filling data types and values takes 5.72s |
|
|
| Processing a file takes 18.57s |
| Concatenating time series takes 0.35s |
| Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_013/trajectory/03_traj_3952.0.json.gz |
| Loading a file takes 50.07s |
| Creating data frames takes 22.54s |
| Filling data types and values takes 5.05s |
|
|
| Processing a file takes 18.75s |
| Concatenating time series takes 0.49s |
| Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_013/trajectory/04_traj_4851.0.json.gz |
| Loading a file takes 49.73s |
| Creating data frames takes 18.87s |
| Filling data types and values takes 5.11s |
|
|
| Processing a file takes 17.40s |
| Concatenating time series takes 0.46s |
| Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_013/trajectory/05_traj_5743.5.json.gz |
| Loading a file takes 44.87s |
| Creating data frames takes 19.10s |
| Filling data types and values takes 5.08s |
|
|
| Processing a file takes 34.75s |
| Concatenating time series takes 0.44s |
| Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_013/trajectory/06_traj_6631.0.json.gz |
| Loading a file takes 58.30s |
| Creating data frames takes 24.53s |
| Filling data types and values takes 5.83s |
|
|
| Processing a file takes 19.18s |
| Concatenating time series takes 0.80s |
| Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_013/trajectory/07_traj_end.json.gz |
| Loading a file takes 51.98s |
| Creating data frames takes 18.12s |
| Filling data types and values takes 5.17s |
|
|
| Processing a file takes 18.52s |
| Concatenating time series takes 0.80s |
| Saving all the section time series takes 79.75s |
| Saving all the junction time series takes 11.10s |
| Saving network entrance and exit takes 0.08s |
| Aggregating the raw statistics to different intervals... |
|
0%| | 0/1515 [00:00<?, ?it/s]
0%| | 1/1515 [00:00<09:43, 2.59it/s]
2%|β | 29/1515 [00:00<00:19, 77.38it/s]
4%|β | 63/1515 [00:00<00:09, 148.53it/s]
6%|β | 95/1515 [00:00<00:07, 190.12it/s]
8%|β | 124/1515 [00:00<00:06, 215.02it/s]
10%|β | 151/1515 [00:00<00:06, 201.26it/s]
12%|ββ | 175/1515 [00:01<00:06, 202.07it/s]
13%|ββ | 198/1515 [00:01<00:06, 206.61it/s]
15%|ββ | 226/1515 [00:01<00:05, 225.09it/s]
17%|ββ | 254/1515 [00:01<00:05, 234.90it/s]
19%|ββ | 283/1515 [00:01<00:05, 244.40it/s]
21%|ββ | 320/1515 [00:01<00:04, 274.69it/s]
23%|βββ | 349/1515 [00:02<00:12, 89.78it/s]
26%|βββ | 393/1515 [00:02<00:08, 129.58it/s]
28%|βββ | 421/1515 [00:02<00:07, 144.33it/s]
30%|βββ | 450/1515 [00:02<00:06, 167.26it/s]
31%|ββββ | 477/1515 [00:02<00:05, 175.72it/s]
33%|ββββ | 502/1515 [00:03<00:05, 179.63it/s]
35%|ββββ | 525/1515 [00:03<00:05, 185.77it/s]
36%|ββββ | 548/1515 [00:03<00:05, 178.32it/s]
38%|ββββ | 570/1515 [00:03<00:05, 185.92it/s]
39%|ββββ | 591/1515 [00:03<00:05, 184.50it/s]
40%|ββββ | 611/1515 [00:03<00:05, 180.28it/s]
42%|βββββ | 633/1515 [00:03<00:04, 189.75it/s]
43%|βββββ | 656/1515 [00:03<00:04, 197.68it/s]
45%|βββββ | 683/1515 [00:03<00:04, 205.16it/s]
47%|βββββ | 711/1515 [00:04<00:03, 222.59it/s]
48%|βββββ | 734/1515 [00:04<00:03, 223.39it/s]
50%|βββββ | 757/1515 [00:04<00:03, 224.09it/s]
51%|ββββββ | 780/1515 [00:04<00:03, 225.56it/s]
53%|ββββββ | 803/1515 [00:04<00:03, 217.67it/s]
55%|ββββββ | 832/1515 [00:04<00:02, 236.55it/s]
57%|ββββββ | 860/1515 [00:04<00:02, 244.07it/s]
59%|ββββββ | 889/1515 [00:04<00:02, 253.06it/s]
60%|ββββββ | 915/1515 [00:04<00:02, 218.73it/s]
62%|βββββββ | 943/1515 [00:05<00:02, 234.15it/s]
64%|βββββββ | 969/1515 [00:05<00:02, 240.18it/s]
66%|βββββββ | 994/1515 [00:05<00:02, 230.32it/s]
67%|βββββββ | 1019/1515 [00:05<00:02, 229.98it/s]
69%|βββββββ | 1044/1515 [00:05<00:02, 231.81it/s]
70%|βββββββ | 1068/1515 [00:05<00:01, 228.91it/s]
72%|ββββββββ | 1097/1515 [00:05<00:01, 244.85it/s]
74%|ββββββββ | 1122/1515 [00:05<00:01, 240.20it/s]
76%|ββββββββ | 1147/1515 [00:05<00:01, 232.21it/s]
77%|ββββββββ | 1171/1515 [00:06<00:01, 230.94it/s]
79%|ββββββββ | 1195/1515 [00:06<00:01, 222.98it/s]
81%|ββββββββ | 1221/1515 [00:06<00:01, 231.22it/s]
83%|βββββββββ | 1252/1515 [00:06<00:01, 250.90it/s]
85%|βββββββββ | 1281/1515 [00:06<00:00, 259.69it/s]
86%|βββββββββ | 1310/1515 [00:06<00:00, 265.86it/s]
88%|βββββββββ | 1337/1515 [00:06<00:00, 244.35it/s]
90%|βββββββββ | 1363/1515 [00:07<00:02, 72.05it/s]
91%|βββββββββ | 1382/1515 [00:07<00:01, 83.88it/s]
93%|ββββββββββ| 1408/1515 [00:07<00:01, 105.54it/s]
94%|ββββββββββ| 1429/1515 [00:08<00:00, 119.50it/s]
96%|ββββββββββ| 1449/1515 [00:08<00:00, 133.69it/s]
97%|ββββββββββ| 1472/1515 [00:08<00:00, 150.39it/s]
99%|ββββββββββ| 1493/1515 [00:08<00:00, 162.73it/s]
100%|ββββββββββ| 1515/1515 [00:08<00:00, 180.52it/s] |
| Constructing time series for each modality ... |
| Saving aggregated time series to /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_013/timeseries/agg_timeseries.pkl |
| Extracting samples from time series ... |
| number of samples: 20 |
| Packing the samples into numpy arrays ... |
|
|