LogViewer
生成的参数组合数量:18
2025-07-02 19:08:38 | INFO | metric_online:run_with_hydra:842 - {'envs': {'env': {'mode': 'prod', 'enable_monitor': False, 'n_jobs': 1}, 'incremental': {'enabled': True, 'lookback_days': 20, 'start_date': None, 'end_date': 'today'}, 'run': {'n_jobs': 1, 'retry_times': 3, 'retry_delay': 2}, 'shard': {'num_shards': 1, 'shard_id': 0}}}
2025-07-02 19:08:39 | INFO | metric_online:run_with_hydra:889 - Total tasks generated: 1
2025-07-02 19:08:39 | INFO | metric_online:run_with_hydra:902 - Starting parallel execution with n_jobs=1...
2025-07-02 19:08:46 | INFO | metric_online:main2:781 - save train test done /root/data/Research1//feature/finalcomd//B8Wstats250412/B8Wstats250412_0--combo52
2025-07-02 19:11:02 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:02 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:03 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:04 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:04 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:04 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:07 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:07 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:09 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:09 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:09 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:10 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:11 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:11 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:11 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:12 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:12 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:12 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:13 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:13 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:14 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:14 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:15 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:15 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:16 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:16 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:17 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:18 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:19 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:19 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:20 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:20 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:20 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:21 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:22 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:22 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:24 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:24 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:24 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:25 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:25 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:26 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:26 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:26 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:27 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:27 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:28 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:28 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:29 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:29 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:29 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:30 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:30 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:30 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:31 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:31 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:31 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:11:32 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
{'obj': 'Sharpe', 'rm': 'MDD', 'model': 'Classic', 'method_mu': 'hist', 'method_cov': 'hist', 'linkage': 'single', 'leaf_order': True, 'codependence': 'pearson', 'lookback_period': 256, 'every': 10, 'nea': 5, 'split_every': False, 'normalize_every': False}

  1%|          | 1/106 [00:08<14:33,  8.32s/it, 2020-01-17 → 2021-02-04]
  2%|▏         | 2/106 [00:14<11:56,  6.89s/it, 2020-02-08 → 2021-02-25]
  3%|▎         | 3/106 [00:20<11:05,  6.46s/it, 2020-02-22 → 2021-03-11]
  4%|▍         | 4/106 [00:26<10:35,  6.23s/it, 2020-03-07 → 2021-03-25]
  5%|▍         | 5/106 [00:31<10:18,  6.12s/it, 2020-03-21 → 2021-04-09]
  6%|▌         | 6/106 [00:38<10:12,  6.12s/it, 2020-04-04 → 2021-04-23]
  7%|▋         | 7/106 [00:44<10:04,  6.10s/it, 2020-04-21 → 2021-05-12]
  8%|▊         | 8/106 [00:50<09:59,  6.11s/it, 2020-05-08 → 2021-05-26]
  8%|▊         | 9/106 [00:56<09:55,  6.14s/it, 2020-05-22 → 2021-06-09]
  9%|▉         | 10/106 [01:02<09:50,  6.15s/it, 2020-06-05 → 2021-06-24]
 10%|█         | 11/106 [01:08<09:43,  6.14s/it, 2020-06-19 → 2021-07-08]
 11%|█▏        | 12/106 [01:14<09:37,  6.14s/it, 2020-07-07 → 2021-07-22]
 12%|█▏        | 13/106 [01:21<09:31,  6.14s/it, 2020-07-21 → 2021-08-05]
 13%|█▎        | 14/106 [01:27<09:25,  6.15s/it, 2020-08-04 → 2021-08-19]
 14%|█▍        | 15/106 [01:33<09:19,  6.15s/it, 2020-08-18 → 2021-09-02]
 15%|█▌        | 16/106 [01:39<09:13,  6.15s/it, 2020-09-01 → 2021-09-16]
 16%|█▌        | 17/106 [01:45<09:08,  6.16s/it, 2020-09-15 → 2021-10-09]
 17%|█▋        | 18/106 [01:51<09:02,  6.17s/it, 2020-09-29 → 2021-10-23]
 18%|█▊        | 19/106 [01:58<08:58,  6.19s/it, 2020-10-21 → 2021-11-06]
 19%|█▉        | 20/106 [02:04<08:48,  6.15s/it, 2020-11-04 → 2021-11-20]
 20%|█▉        | 21/106 [02:10<08:44,  6.17s/it, 2020-11-18 → 2021-12-04]
 21%|██        | 22/106 [02:16<08:41,  6.21s/it, 2020-12-02 → 2021-12-18]
 22%|██▏       | 23/106 [02:22<08:36,  6.22s/it, 2020-12-16 → 2022-01-01]
 23%|██▎       | 24/106 [02:29<08:29,  6.21s/it, 2020-12-30 → 2022-01-18]
 24%|██▎       | 25/106 [02:35<08:20,  6.18s/it, 2021-01-14 → 2022-02-08]
 25%|██▍       | 26/106 [02:41<08:13,  6.17s/it, 2021-01-28 → 2022-02-22]
 25%|██▌       | 27/106 [02:47<08:06,  6.16s/it, 2021-02-11 → 2022-03-08]
 26%|██▋       | 28/106 [02:53<08:00,  6.16s/it, 2021-03-04 → 2022-03-22]
 27%|██▋       | 29/106 [02:59<07:53,  6.15s/it, 2021-03-18 → 2022-04-07]
 28%|██▊       | 30/106 [03:06<07:47,  6.15s/it, 2021-04-01 → 2022-04-21]
 29%|██▉       | 31/106 [03:12<07:40,  6.14s/it, 2021-04-16 → 2022-05-10]
 30%|███       | 32/106 [03:18<07:31,  6.11s/it, 2021-04-30 → 2022-05-24]
 31%|███       | 33/106 [03:24<07:25,  6.10s/it, 2021-05-19 → 2022-06-08]
 32%|███▏      | 34/106 [03:30<07:20,  6.12s/it, 2021-06-02 → 2022-06-22]
 33%|███▎      | 35/106 [03:36<07:15,  6.14s/it, 2021-06-17 → 2022-07-06]
 34%|███▍      | 36/106 [03:42<07:10,  6.15s/it, 2021-07-01 → 2022-07-20]
 35%|███▍      | 37/106 [03:48<07:03,  6.14s/it, 2021-07-15 → 2022-08-03]
 36%|███▌      | 38/106 [03:55<06:57,  6.14s/it, 2021-07-29 → 2022-08-17]
 37%|███▋      | 39/106 [04:01<06:52,  6.15s/it, 2021-08-12 → 2022-08-31]
 38%|███▊      | 40/106 [04:07<06:45,  6.14s/it, 2021-08-26 → 2022-09-15]
 39%|███▊      | 41/106 [04:13<06:39,  6.14s/it, 2021-09-09 → 2022-09-29]
 40%|███▉      | 42/106 [04:19<06:30,  6.11s/it, 2021-09-25 → 2022-10-20]
 41%|████      | 43/106 [04:25<06:26,  6.13s/it, 2021-10-16 → 2022-11-03]
 42%|████▏     | 44/106 [04:31<06:20,  6.14s/it, 2021-10-30 → 2022-11-17]
 42%|████▏     | 45/106 [04:37<06:14,  6.14s/it, 2021-11-13 → 2022-12-01]
 43%|████▎     | 46/106 [04:44<06:12,  6.21s/it, 2021-11-27 → 2022-12-15]
 44%|████▍     | 47/106 [04:50<06:05,  6.19s/it, 2021-12-11 → 2022-12-29]
 45%|████▌     | 48/106 [04:56<05:57,  6.17s/it, 2021-12-25 → 2023-01-13]
 46%|████▌     | 49/106 [05:02<05:48,  6.11s/it, 2022-01-11 → 2023-02-03]
 47%|████▋     | 50/106 [05:08<05:39,  6.07s/it, 2022-01-25 → 2023-02-17]
 48%|████▊     | 51/106 [05:14<05:31,  6.02s/it, 2022-02-15 → 2023-03-03]
 49%|████▉     | 52/106 [05:20<05:24,  6.02s/it, 2022-03-01 → 2023-03-17]
 50%|█████     | 53/106 [05:26<05:21,  6.07s/it, 2022-03-15 → 2023-03-31]
 51%|█████     | 54/106 [05:32<05:17,  6.11s/it, 2022-03-29 → 2023-04-15]
 52%|█████▏    | 55/106 [05:38<05:11,  6.11s/it, 2022-04-14 → 2023-04-29]
 53%|█████▎    | 56/106 [05:45<05:07,  6.15s/it, 2022-04-28 → 2023-05-18]
 54%|█████▍    | 57/106 [05:51<05:02,  6.17s/it, 2022-05-17 → 2023-06-01]
 55%|█████▍    | 58/106 [05:57<04:55,  6.15s/it, 2022-05-31 → 2023-06-15]
 56%|█████▌    | 59/106 [06:03<04:51,  6.20s/it, 2022-06-15 → 2023-07-01]
 57%|█████▋    | 60/106 [06:09<04:43,  6.17s/it, 2022-06-29 → 2023-07-15]
 58%|█████▊    | 61/106 [06:16<04:36,  6.14s/it, 2022-07-13 → 2023-07-29]
 58%|█████▊    | 62/106 [06:22<04:29,  6.13s/it, 2022-07-27 → 2023-08-12]
 59%|█████▉    | 63/106 [06:28<04:24,  6.15s/it, 2022-08-10 → 2023-08-26]
 60%|██████    | 64/106 [06:34<04:17,  6.14s/it, 2022-08-24 → 2023-09-09]
 61%|██████▏   | 65/106 [06:40<04:09,  6.09s/it, 2022-09-07 → 2023-09-23]
 62%|██████▏   | 66/106 [06:46<04:02,  6.07s/it, 2022-09-22 → 2023-10-17]
 63%|██████▎   | 67/106 [06:52<03:56,  6.06s/it, 2022-10-13 → 2023-10-31]
 64%|██████▍   | 68/106 [06:58<03:51,  6.08s/it, 2022-10-27 → 2023-11-14]
 65%|██████▌   | 69/106 [07:04<03:47,  6.15s/it, 2022-11-10 → 2023-11-28]
 66%|██████▌   | 70/106 [07:11<03:42,  6.19s/it, 2022-11-24 → 2023-12-12]
 67%|██████▋   | 71/106 [07:18<03:43,  6.39s/it, 2022-12-08 → 2023-12-26]
 68%|██████▊   | 72/106 [07:24<03:35,  6.35s/it, 2022-12-22 → 2024-01-10]
 69%|██████▉   | 73/106 [07:30<03:28,  6.31s/it, 2023-01-06 → 2024-01-24]
 70%|██████▉   | 74/106 [07:36<03:21,  6.28s/it, 2023-01-20 → 2024-02-07]
 71%|███████   | 75/106 [07:43<03:14,  6.27s/it, 2023-02-10 → 2024-02-29]
 72%|███████▏  | 76/106 [07:49<03:07,  6.26s/it, 2023-02-24 → 2024-03-14]
 73%|███████▎  | 77/106 [07:55<03:01,  6.27s/it, 2023-03-10 → 2024-03-28]
 74%|███████▎  | 78/106 [08:01<02:55,  6.28s/it, 2023-03-24 → 2024-04-13]
 75%|███████▍  | 79/106 [08:08<02:49,  6.26s/it, 2023-04-08 → 2024-04-27]
 75%|███████▌  | 80/106 [08:14<02:42,  6.26s/it, 2023-04-22 → 2024-05-16]
 76%|███████▋  | 81/106 [08:20<02:37,  6.28s/it, 2023-05-11 → 2024-05-30]
 77%|███████▋  | 82/106 [08:26<02:30,  6.28s/it, 2023-05-25 → 2024-06-14]
 78%|███████▊  | 83/106 [08:33<02:24,  6.28s/it, 2023-06-08 → 2024-06-28]
 79%|███████▉  | 84/106 [08:39<02:17,  6.27s/it, 2023-06-22 → 2024-07-12]
 80%|████████  | 85/106 [08:45<02:12,  6.29s/it, 2023-07-08 → 2024-07-26]
 81%|████████  | 86/106 [08:52<02:06,  6.32s/it, 2023-07-22 → 2024-08-09]
 82%|████████▏ | 87/106 [08:58<02:00,  6.32s/it, 2023-08-05 → 2024-08-23]
 83%|████████▎ | 88/106 [09:04<01:53,  6.33s/it, 2023-08-19 → 2024-09-06]
 84%|████████▍ | 89/106 [09:11<01:47,  6.33s/it, 2023-09-02 → 2024-09-24]
 85%|████████▍ | 90/106 [09:17<01:40,  6.30s/it, 2023-09-16 → 2024-10-15]
 86%|████████▌ | 91/106 [09:23<01:34,  6.32s/it, 2023-10-10 → 2024-10-29]
 87%|████████▋ | 92/106 [09:30<01:28,  6.30s/it, 2023-10-24 → 2024-11-12]
 88%|████████▊ | 93/106 [09:36<01:22,  6.34s/it, 2023-11-07 → 2024-11-26]
 89%|████████▊ | 94/106 [09:42<01:16,  6.36s/it, 2023-11-21 → 2024-12-10]
 90%|████████▉ | 95/106 [09:49<01:10,  6.37s/it, 2023-12-05 → 2024-12-24]
 91%|█████████ | 96/106 [09:55<01:03,  6.39s/it, 2023-12-19 → 2025-01-08]
 92%|█████████▏| 97/106 [10:02<00:57,  6.38s/it, 2024-01-03 → 2025-01-22]
 92%|█████████▏| 98/106 [10:08<00:51,  6.38s/it, 2024-01-17 → 2025-02-13]
 93%|█████████▎| 99/106 [10:14<00:44,  6.40s/it, 2024-01-31 → 2025-02-27]
 94%|█████████▍| 100/106 [10:21<00:38,  6.41s/it, 2024-02-22 → 2025-03-13]
 95%|█████████▌| 101/106 [10:27<00:32,  6.40s/it, 2024-03-07 → 2025-03-27]
 96%|█████████▌| 102/106 [10:34<00:25,  6.39s/it, 2024-03-21 → 2025-04-11]
 97%|█████████▋| 103/106 [10:40<00:19,  6.40s/it, 2024-04-04 → 2025-04-26]
 98%|█████████▊| 104/106 [10:46<00:12,  6.38s/it, 2024-04-20 → 2025-05-15]
 99%|█████████▉| 105/106 [10:53<00:06,  6.35s/it, 2024-05-09 → 2025-06-18]
100%|██████████| 106/106 [10:59<00:00,  6.32s/it, 2024-05-09 → 2025-06-18]
100%|██████████| 106/106 [10:59<00:00,  6.22s/it, 2024-05-09 → 2025-06-18]
2025-07-02 19:22:33 | INFO | metric_online:run_optimize_portfolio_new_with_sector_constraints:463 - [v7] 优化前的夏普率: 1.04832
2025-07-02 19:22:33 | INFO | metric_online:run_optimize_portfolio_new_with_sector_constraints:464 - [v7] 优化后的夏普率: 0.78974
2025-07-02 19:22:34 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:22:35 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:22:35 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:22:37 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:22:38 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:22:38 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:22:39 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:22:39 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:22:40 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:22:40 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:22:41 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:22:41 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:22:42 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:22:43 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:22:43 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:22:44 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:22:44 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:22:45 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:22:46 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:22:46 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:22:47 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:22:47 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:22:47 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:22:48 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:22:48 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:22:49 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:22:49 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:22:50 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:22:50 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
{'obj': 'Sharpe', 'rm': 'MDD', 'model': 'Classic', 'method_mu': 'hist', 'method_cov': 'hist', 'linkage': 'single', 'leaf_order': True, 'codependence': 'pearson', 'lookback_period': 256, 'every': 10, 'nea': 5, 'split_every': False, 'normalize_every': False}

  1%|          | 1/106 [00:05<10:26,  5.96s/it, 2020-01-18 → 2021-02-05]
  2%|▏         | 2/106 [00:11<10:23,  6.00s/it, 2020-02-11 → 2021-02-26]
  3%|▎         | 3/106 [00:18<10:24,  6.06s/it, 2020-02-25 → 2021-03-12]
  4%|▍         | 4/106 [00:24<10:11,  5.99s/it, 2020-03-10 → 2021-03-26]
  5%|▍         | 5/106 [00:29<10:02,  5.97s/it, 2020-03-24 → 2021-04-10]
  6%|▌         | 6/106 [00:35<10:00,  6.00s/it, 2020-04-08 → 2021-04-24]
  7%|▋         | 7/106 [00:42<09:55,  6.01s/it, 2020-04-22 → 2021-05-13]
  8%|▊         | 8/106 [00:48<09:53,  6.06s/it, 2020-05-09 → 2021-05-27]
  8%|▊         | 9/106 [00:54<09:51,  6.09s/it, 2020-05-23 → 2021-06-10]
  9%|▉         | 10/106 [01:00<09:43,  6.07s/it, 2020-06-06 → 2021-06-25]
 10%|█         | 11/106 [01:06<09:40,  6.11s/it, 2020-06-20 → 2021-07-09]
 11%|█▏        | 12/106 [01:12<09:35,  6.12s/it, 2020-07-08 → 2021-07-23]
 12%|█▏        | 13/106 [01:18<09:32,  6.16s/it, 2020-07-22 → 2021-08-06]
 13%|█▎        | 14/106 [01:25<09:25,  6.15s/it, 2020-08-05 → 2021-08-20]
 14%|█▍        | 15/106 [01:31<09:18,  6.14s/it, 2020-08-19 → 2021-09-03]
 15%|█▌        | 16/106 [01:37<09:09,  6.10s/it, 2020-09-02 → 2021-09-17]
 16%|█▌        | 17/106 [01:43<09:01,  6.09s/it, 2020-09-16 → 2021-10-12]
 17%|█▋        | 18/106 [01:49<08:55,  6.08s/it, 2020-09-30 → 2021-10-26]
 18%|█▊        | 19/106 [01:55<08:50,  6.09s/it, 2020-10-22 → 2021-11-09]
 19%|█▉        | 20/106 [02:01<08:46,  6.12s/it, 2020-11-05 → 2021-11-23]
 20%|█▉        | 21/106 [02:07<08:42,  6.14s/it, 2020-11-19 → 2021-12-07]
 21%|██        | 22/106 [02:14<08:38,  6.17s/it, 2020-12-03 → 2021-12-21]
 22%|██▏       | 23/106 [02:20<08:32,  6.18s/it, 2020-12-17 → 2022-01-05]
 23%|██▎       | 24/106 [02:26<08:27,  6.19s/it, 2020-12-31 → 2022-01-19]
 24%|██▎       | 25/106 [02:32<08:22,  6.21s/it, 2021-01-15 → 2022-02-09]
 25%|██▍       | 26/106 [02:38<08:14,  6.18s/it, 2021-01-29 → 2022-02-23]
 25%|██▌       | 27/106 [02:44<08:05,  6.15s/it, 2021-02-19 → 2022-03-09]
 26%|██▋       | 28/106 [02:51<07:59,  6.15s/it, 2021-03-05 → 2022-03-23]
 27%|██▋       | 29/106 [02:57<07:54,  6.16s/it, 2021-03-19 → 2022-04-08]
 28%|██▊       | 30/106 [03:03<07:47,  6.15s/it, 2021-04-02 → 2022-04-22]
 29%|██▉       | 31/106 [03:09<07:42,  6.17s/it, 2021-04-17 → 2022-05-11]
 30%|███       | 32/106 [03:15<07:35,  6.15s/it, 2021-05-01 → 2022-05-25]
 31%|███       | 33/106 [03:21<07:28,  6.14s/it, 2021-05-20 → 2022-06-09]
 32%|███▏      | 34/106 [03:27<07:22,  6.14s/it, 2021-06-03 → 2022-06-23]
 33%|███▎      | 35/106 [03:34<07:15,  6.13s/it, 2021-06-18 → 2022-07-07]
 34%|███▍      | 36/106 [03:40<07:08,  6.12s/it, 2021-07-02 → 2022-07-21]
 35%|███▍      | 37/106 [03:46<07:01,  6.10s/it, 2021-07-16 → 2022-08-04]
 36%|███▌      | 38/106 [03:52<06:54,  6.10s/it, 2021-07-30 → 2022-08-18]
 37%|███▋      | 39/106 [03:58<06:49,  6.11s/it, 2021-08-13 → 2022-09-01]
 38%|███▊      | 40/106 [04:04<06:41,  6.08s/it, 2021-08-27 → 2022-09-16]
 39%|███▊      | 41/106 [04:10<06:35,  6.08s/it, 2021-09-10 → 2022-09-30]
 40%|███▉      | 42/106 [04:16<06:30,  6.11s/it, 2021-09-28 → 2022-10-21]
 41%|████      | 43/106 [04:22<06:24,  6.11s/it, 2021-10-19 → 2022-11-04]
 42%|████▏     | 44/106 [04:29<06:19,  6.12s/it, 2021-11-02 → 2022-11-18]
 42%|████▏     | 45/106 [04:35<06:14,  6.14s/it, 2021-11-16 → 2022-12-02]
 43%|████▎     | 46/106 [04:41<06:08,  6.15s/it, 2021-11-30 → 2022-12-16]
 44%|████▍     | 47/106 [04:47<06:00,  6.11s/it, 2021-12-14 → 2022-12-30]
 45%|████▌     | 48/106 [04:53<05:53,  6.10s/it, 2021-12-28 → 2023-01-14]
 46%|████▌     | 49/106 [04:59<05:44,  6.05s/it, 2022-01-12 → 2023-02-04]
 47%|████▋     | 50/106 [05:05<05:35,  5.99s/it, 2022-01-26 → 2023-02-18]
 48%|████▊     | 51/106 [05:11<05:27,  5.95s/it, 2022-02-16 → 2023-03-04]
 49%|████▉     | 52/106 [05:17<05:23,  5.99s/it, 2022-03-02 → 2023-03-18]
 50%|█████     | 53/106 [05:23<05:20,  6.05s/it, 2022-03-16 → 2023-04-01]
 51%|█████     | 54/106 [05:29<05:16,  6.09s/it, 2022-03-30 → 2023-04-18]
 52%|█████▏    | 55/106 [05:35<05:12,  6.12s/it, 2022-04-15 → 2023-05-05]
 53%|█████▎    | 56/106 [05:41<05:06,  6.13s/it, 2022-04-29 → 2023-05-19]
 54%|█████▍    | 57/106 [05:47<04:59,  6.11s/it, 2022-05-18 → 2023-06-02]
 55%|█████▍    | 58/106 [05:54<04:55,  6.15s/it, 2022-06-01 → 2023-06-16]
 56%|█████▌    | 59/106 [06:00<04:50,  6.19s/it, 2022-06-16 → 2023-07-04]
 57%|█████▋    | 60/106 [06:06<04:44,  6.19s/it, 2022-06-30 → 2023-07-18]
 58%|█████▊    | 61/106 [06:12<04:38,  6.18s/it, 2022-07-14 → 2023-08-01]
 58%|█████▊    | 62/106 [06:19<04:32,  6.20s/it, 2022-07-28 → 2023-08-15]
 59%|█████▉    | 63/106 [06:25<04:26,  6.21s/it, 2022-08-11 → 2023-08-29]
 60%|██████    | 64/106 [06:31<04:21,  6.23s/it, 2022-08-25 → 2023-09-12]
 61%|██████▏   | 65/106 [06:37<04:13,  6.19s/it, 2022-09-08 → 2023-09-26]
 62%|██████▏   | 66/106 [06:43<04:06,  6.15s/it, 2022-09-23 → 2023-10-18]
 63%|██████▎   | 67/106 [06:49<04:00,  6.16s/it, 2022-10-14 → 2023-11-01]
 64%|██████▍   | 68/106 [06:56<03:55,  6.19s/it, 2022-10-28 → 2023-11-15]
 65%|██████▌   | 69/106 [07:02<03:50,  6.23s/it, 2022-11-11 → 2023-11-29]
 66%|██████▌   | 70/106 [07:08<03:44,  6.24s/it, 2022-11-25 → 2023-12-13]
 67%|██████▋   | 71/106 [07:15<03:38,  6.24s/it, 2022-12-09 → 2023-12-27]
 68%|██████▊   | 72/106 [07:21<03:31,  6.23s/it, 2022-12-23 → 2024-01-11]
 69%|██████▉   | 73/106 [07:27<03:25,  6.23s/it, 2023-01-07 → 2024-01-25]
 70%|██████▉   | 74/106 [07:33<03:20,  6.27s/it, 2023-01-21 → 2024-02-08]
 71%|███████   | 75/106 [07:40<03:14,  6.28s/it, 2023-02-11 → 2024-03-01]
 72%|███████▏  | 76/106 [07:46<03:08,  6.27s/it, 2023-02-25 → 2024-03-15]
 73%|███████▎  | 77/106 [07:52<03:01,  6.27s/it, 2023-03-11 → 2024-03-29]
 74%|███████▎  | 78/106 [07:59<02:56,  6.32s/it, 2023-03-25 → 2024-04-16]
 75%|███████▍  | 79/106 [08:05<02:50,  6.30s/it, 2023-04-11 → 2024-04-30]
 75%|███████▌  | 80/106 [08:11<02:43,  6.28s/it, 2023-04-25 → 2024-05-17]
 76%|███████▋  | 81/106 [08:18<02:38,  6.33s/it, 2023-05-12 → 2024-05-31]
 77%|███████▋  | 82/106 [08:24<02:31,  6.33s/it, 2023-05-26 → 2024-06-15]
 78%|███████▊  | 83/106 [08:30<02:24,  6.30s/it, 2023-06-09 → 2024-06-29]
 79%|███████▉  | 84/106 [08:36<02:19,  6.32s/it, 2023-06-27 → 2024-07-13]
 80%|████████  | 85/106 [08:43<02:12,  6.32s/it, 2023-07-11 → 2024-07-27]
 81%|████████  | 86/106 [08:49<02:06,  6.33s/it, 2023-07-25 → 2024-08-10]
 82%|████████▏ | 87/106 [08:56<02:00,  6.34s/it, 2023-08-08 → 2024-08-24]
 83%|████████▎ | 88/106 [09:02<01:54,  6.36s/it, 2023-08-22 → 2024-09-07]
 84%|████████▍ | 89/106 [09:08<01:48,  6.38s/it, 2023-09-05 → 2024-09-25]
 85%|████████▍ | 90/106 [09:15<01:41,  6.35s/it, 2023-09-19 → 2024-10-16]
 86%|████████▌ | 91/106 [09:21<01:34,  6.31s/it, 2023-10-11 → 2024-10-30]
 87%|████████▋ | 92/106 [09:27<01:28,  6.29s/it, 2023-10-25 → 2024-11-13]
 88%|████████▊ | 93/106 [09:33<01:22,  6.33s/it, 2023-11-08 → 2024-11-27]
 89%|████████▊ | 94/106 [09:40<01:15,  6.30s/it, 2023-11-22 → 2024-12-11]
 90%|████████▉ | 95/106 [09:46<01:09,  6.33s/it, 2023-12-06 → 2024-12-25]
 91%|█████████ | 96/106 [09:53<01:03,  6.37s/it, 2023-12-20 → 2025-01-09]
 92%|█████████▏| 97/106 [09:59<00:57,  6.37s/it, 2024-01-04 → 2025-01-23]
 92%|█████████▏| 98/106 [10:05<00:51,  6.38s/it, 2024-01-18 → 2025-02-14]
 93%|█████████▎| 99/106 [10:12<00:44,  6.35s/it, 2024-02-01 → 2025-02-28]
 94%|█████████▍| 100/106 [10:18<00:37,  6.32s/it, 2024-02-23 → 2025-03-14]
 95%|█████████▌| 101/106 [10:24<00:31,  6.29s/it, 2024-03-08 → 2025-03-28]
 96%|█████████▌| 102/106 [10:30<00:25,  6.27s/it, 2024-03-22 → 2025-04-15]
 97%|█████████▋| 103/106 [10:37<00:19,  6.35s/it, 2024-04-09 → 2025-04-29]
 98%|█████████▊| 104/106 [10:43<00:12,  6.35s/it, 2024-04-23 → 2025-05-16]
 99%|█████████▉| 105/106 [10:50<00:06,  6.34s/it, 2024-05-10 → 2025-06-19]
100%|██████████| 106/106 [10:56<00:00,  6.35s/it, 2024-05-10 → 2025-06-19]
100%|██████████| 106/106 [10:56<00:00,  6.19s/it, 2024-05-10 → 2025-06-19]
2025-07-02 19:33:47 | INFO | metric_online:run_optimize_portfolio_new_with_sector_constraints:463 - [v8] 优化前的夏普率: 0.82435
2025-07-02 19:33:47 | INFO | metric_online:run_optimize_portfolio_new_with_sector_constraints:464 - [v8] 优化后的夏普率: 1.01102
2025-07-02 19:33:48 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:33:48 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:33:49 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:33:50 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:33:52 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:33:52 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:33:53 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:33:53 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:33:54 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:33:54 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:33:55 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:33:55 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:33:56 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:33:57 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:33:57 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:33:58 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:33:58 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:33:59 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:34:00 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:34:00 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:34:01 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:34:01 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:34:02 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:34:02 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:34:03 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:34:03 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:34:04 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:34:04 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-07-02 19:34:04 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
[2025-07-02 19:34:06,138][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-07-02 19:34:06,139][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-07-02 19:34:06,147][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-07-02 19:34:06,148][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-07-02 19:34:06,155][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-07-02 19:34:06,156][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-07-02 19:34:08,109][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-07-02 19:34:08,110][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-07-02 19:34:08,118][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-07-02 19:34:08,119][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-07-02 19:34:08,126][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-07-02 19:34:08,127][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-07-02 19:34:09,839][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-07-02 19:34:09,840][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-07-02 19:34:09,847][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-07-02 19:34:09,848][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-07-02 19:34:09,855][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-07-02 19:34:09,856][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
2025-07-02 19:34:13 | INFO | metric_online:run_with_hydra:919 - {'action': 'parallel_done', 'success_count': 1, 'fail_count': 0}
2025-07-02 19:34:13 | INFO | metric_online:run_with_hydra:924 - {'action': 'success', 'description': 'metric_online 完成'}