生成的参数组合数量：18
2025-06-10 19:08:27 | 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}}}
2025-06-10 19:08:27 | INFO | metric_online:run_with_hydra:889 - Total tasks generated: 1
2025-06-10 19:08:27 | INFO | metric_online:run_with_hydra:902 - Starting parallel execution with n_jobs=1...
2025-06-10 19:08:34 | INFO | metric_online:main2:781 - save train test done /root/data/Research1//feature/finalcomd//B8Wstats250412/B8Wstats250412_0--combo52
2025-06-10 19:10:40 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:40 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:41 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:41 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:44 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:44 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:44 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:45 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:46 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:47 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:47 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:48 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:48 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:48 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:50 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:50 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:51 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:51 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:53 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:53 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:56 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:56 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:56 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:57 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:57 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:57 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:58 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:58 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:58 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:59 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:59 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:10:59 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:11:00 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:11:00 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:11:00 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:11:01 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:11:01 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:11:01 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:11:02 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:11:03 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:11:05 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:11:05 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:11:05 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:11:06 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:11:07 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:11:07 | 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}
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2025-06-10 19:21:56 | INFO | metric_online:run_optimize_portfolio_new_with_sector_constraints:463 - [v7] 优化前的夏普率: 1.04248
2025-06-10 19:21:56 | INFO | metric_online:run_optimize_portfolio_new_with_sector_constraints:464 - [v7] 优化后的夏普率: 0.71254
2025-06-10 19:21:56 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:21:57 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:21:59 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:21:59 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:22:00 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:22:01 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:22:01 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:22:02 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:22:03 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:22:04 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:22:05 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:22:06 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:22:06 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:22:06 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:22:07 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:22:07 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:22:08 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:22:08 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:22:08 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:22:09 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:22:11 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:22:11 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:22:12 | 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}
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2025-06-10 19:32:53 | INFO | metric_online:run_optimize_portfolio_new_with_sector_constraints:463 - [v8] 优化前的夏普率: 0.76457
2025-06-10 19:32:53 | INFO | metric_online:run_optimize_portfolio_new_with_sector_constraints:464 - [v8] 优化后的夏普率: 0.96367
2025-06-10 19:32:53 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:32:54 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:32:55 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:32:56 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:32:57 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:32:57 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:32:58 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:32:59 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:32:59 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:33:01 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:33:02 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:33:03 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:33:03 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:33:03 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:33:04 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:33:04 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:33:05 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:33:05 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:33:05 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:33:06 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:33:07 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:33:08 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-10 19:33:09 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
[2025-06-10 19:33:10,299][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.
[2025-06-10 19:33:10,300][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.
[2025-06-10 19:33:10,308][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.
[2025-06-10 19:33:10,309][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.
[2025-06-10 19:33:10,316][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.
[2025-06-10 19:33:10,317][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.
[2025-06-10 19:33:12,255][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.
[2025-06-10 19:33:12,256][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.
[2025-06-10 19:33:12,264][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.
[2025-06-10 19:33:12,265][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.
[2025-06-10 19:33:12,272][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.
[2025-06-10 19:33:12,273][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.
[2025-06-10 19:33:14,056][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.
[2025-06-10 19:33:14,058][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.
[2025-06-10 19:33:14,064][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.
[2025-06-10 19:33:14,065][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.
[2025-06-10 19:33:14,072][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.
[2025-06-10 19:33:14,073][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.
2025-06-10 19:33:17 | INFO | metric_online:run_with_hydra:919 - {'action': 'parallel_done', 'success_count': 1, 'fail_count': 0}
2025-06-10 19:33:17 | INFO | metric_online:run_with_hydra:924 - {'action': 'success', 'description': 'metric_online 完成'}