| 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 124261 vehicles |
| Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_015/trajectory/00_traj_1344.5.json.gz |
| Loading a file takes 54.99s |
| Creating data frames takes 20.43s |
| Filling data types and values takes 5.81s |
|
|
| Processing a file takes 18.87s |
| Concatenating time series takes 0.47s |
| Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_015/trajectory/01_traj_2230.5.json.gz |
| Loading a file takes 55.79s |
| Creating data frames takes 18.90s |
| Filling data types and values takes 5.01s |
|
|
| Processing a file takes 18.30s |
| Concatenating time series takes 0.28s |
| Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_015/trajectory/02_traj_3066.0.json.gz |
| Loading a file takes 49.33s |
| Creating data frames takes 18.32s |
| Filling data types and values takes 4.94s |
|
|
| Processing a file takes 17.73s |
| Concatenating time series takes 0.31s |
| Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_015/trajectory/03_traj_3860.5.json.gz |
| Loading a file takes 48.28s |
| Creating data frames takes 18.56s |
| Filling data types and values takes 5.12s |
|
|
| Processing a file takes 17.97s |
| Concatenating time series takes 0.38s |
| Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_015/trajectory/04_traj_4653.5.json.gz |
| Loading a file takes 52.41s |
| Creating data frames takes 18.82s |
| Filling data types and values takes 5.06s |
|
|
| Processing a file takes 17.52s |
| Concatenating time series takes 0.45s |
| Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_015/trajectory/05_traj_5432.0.json.gz |
| Loading a file takes 50.93s |
| Creating data frames takes 19.13s |
| Filling data types and values takes 5.35s |
|
|
| Processing a file takes 28.74s |
| Concatenating time series takes 0.45s |
| Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_015/trajectory/06_traj_6200.5.json.gz |
| Loading a file takes 59.32s |
| Creating data frames takes 20.80s |
| Filling data types and values takes 5.32s |
|
|
| Processing a file takes 32.61s |
| Concatenating time series takes 0.58s |
| Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_015/trajectory/07_traj_6942.5.json.gz |
| Loading a file takes 60.89s |
| Creating data frames takes 22.97s |
| Filling data types and values takes 5.65s |
|
|
| Processing a file takes 18.38s |
| Concatenating time series takes 0.68s |
| Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_015/trajectory/08_traj_9937.5.json.gz |
| Loading a file takes 54.91s |
| Creating data frames takes 20.95s |
| Filling data types and values takes 5.69s |
|
|
| Processing a file takes 18.53s |
| Concatenating time series takes 0.49s |
| Working on file /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_015/trajectory/09_traj_end.json.gz |
| Loading a file takes 9.57s |
| Creating data frames takes 3.18s |
| Filling data types and values takes 0.61s |
|
|
| Processing a file takes 4.87s |
| Concatenating time series takes 0.14s |
| Saving all the section time series takes 76.15s |
| Saving all the junction time series takes 10.55s |
| Saving network entrance and exit takes 0.08s |
| Aggregating the raw statistics to different intervals... |
|
0%| | 0/1522 [00:00<?, ?it/s]
0%| | 1/1522 [00:00<09:05, 2.79it/s]
1%| | 8/1522 [00:00<01:19, 19.12it/s]
4%|β | 63/1522 [00:00<00:09, 156.60it/s]
7%|β | 104/1522 [00:00<00:06, 224.09it/s]
9%|β | 136/1522 [00:00<00:06, 201.94it/s]
11%|β | 163/1522 [00:01<00:06, 209.69it/s]
12%|ββ | 189/1522 [00:01<00:06, 218.80it/s]
14%|ββ | 218/1522 [00:01<00:05, 236.68it/s]
16%|ββ | 245/1522 [00:01<00:05, 243.85it/s]
18%|ββ | 272/1522 [00:01<00:05, 243.50it/s]
20%|ββ | 298/1522 [00:01<00:05, 220.53it/s]
21%|ββ | 322/1522 [00:02<00:17, 70.05it/s]
23%|βββ | 350/1522 [00:02<00:12, 91.47it/s]
25%|βββ | 388/1522 [00:02<00:08, 126.98it/s]
28%|βββ | 419/1522 [00:02<00:07, 152.93it/s]
29%|βββ | 447/1522 [00:02<00:06, 172.55it/s]
31%|βββ | 473/1522 [00:03<00:05, 179.56it/s]
33%|ββββ | 497/1522 [00:03<00:05, 179.58it/s]
34%|ββββ | 520/1522 [00:03<00:05, 171.67it/s]
36%|ββββ | 541/1522 [00:03<00:05, 166.24it/s]
37%|ββββ | 561/1522 [00:03<00:05, 170.99it/s]
38%|ββββ | 584/1522 [00:03<00:05, 183.81it/s]
40%|ββββ | 604/1522 [00:03<00:05, 166.26it/s]
41%|βββββ | 629/1522 [00:03<00:04, 185.26it/s]
43%|βββββ | 656/1522 [00:04<00:04, 205.84it/s]
45%|βββββ | 678/1522 [00:04<00:04, 208.35it/s]
46%|βββββ | 700/1522 [00:04<00:04, 195.20it/s]
47%|βββββ | 721/1522 [00:04<00:04, 198.05it/s]
49%|βββββ | 745/1522 [00:04<00:03, 207.38it/s]
50%|βββββ | 767/1522 [00:04<00:03, 195.40it/s]
52%|ββββββ | 790/1522 [00:04<00:03, 204.61it/s]
53%|ββββββ | 811/1522 [00:04<00:03, 193.80it/s]
55%|ββββββ | 839/1522 [00:04<00:03, 214.63it/s]
57%|ββββββ | 864/1522 [00:05<00:02, 224.06it/s]
59%|ββββββ | 891/1522 [00:05<00:02, 235.19it/s]
60%|ββββββ | 915/1522 [00:05<00:02, 221.01it/s]
62%|βββββββ | 941/1522 [00:05<00:02, 230.27it/s]
64%|βββββββ | 969/1522 [00:05<00:02, 236.65it/s]
65%|βββββββ | 993/1522 [00:05<00:02, 236.80it/s]
67%|βββββββ | 1017/1522 [00:05<00:02, 236.90it/s]
68%|βββββββ | 1041/1522 [00:05<00:02, 222.45it/s]
70%|βββββββ | 1064/1522 [00:05<00:02, 222.19it/s]
71%|ββββββββ | 1088/1522 [00:06<00:01, 225.75it/s]
73%|ββββββββ | 1111/1522 [00:06<00:01, 222.36it/s]
75%|ββββββββ | 1134/1522 [00:06<00:01, 208.47it/s]
76%|ββββββββ | 1164/1522 [00:06<00:01, 232.38it/s]
78%|ββββββββ | 1188/1522 [00:06<00:01, 234.14it/s]
80%|ββββββββ | 1212/1522 [00:06<00:01, 229.81it/s]
81%|βββββββββ | 1240/1522 [00:06<00:01, 236.35it/s]
83%|βββββββββ | 1270/1522 [00:06<00:01, 250.60it/s]
85%|βββββββββ | 1297/1522 [00:06<00:00, 254.17it/s]
87%|βββββββββ | 1323/1522 [00:07<00:00, 239.28it/s]
89%|βββββββββ | 1348/1522 [00:07<00:00, 233.63it/s]
90%|βββββββββ | 1372/1522 [00:08<00:02, 57.71it/s]
92%|ββββββββββ| 1393/1522 [00:08<00:01, 69.66it/s]
94%|ββββββββββ| 1428/1522 [00:08<00:00, 99.88it/s]
95%|ββββββββββ| 1450/1522 [00:08<00:00, 113.35it/s]
97%|ββββββββββ| 1472/1522 [00:08<00:00, 129.74it/s]
99%|ββββββββββ| 1504/1522 [00:08<00:00, 160.59it/s]
100%|ββββββββββ| 1522/1522 [00:08<00:00, 170.11it/s] |
| Constructing time series for each modality ... |
| Saving aggregated time series to /home/weijiang/Projects/Netsanut/datasets/simbarca/simulation_sessions/session_015/timeseries/agg_timeseries.pkl |
| Extracting samples from time series ... |
| number of samples: 20 |
| Packing the samples into numpy arrays ... |
|
|