生成的参数组合数量：18
2025-06-13 19:08:37 | 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}}}
2025-06-13 19:08:37 | INFO | metric_online:run_with_hydra:889 - Total tasks generated: 1
2025-06-13 19:08:37 | INFO | metric_online:run_with_hydra:902 - Starting parallel execution with n_jobs=1...
2025-06-13 19:08:44 | INFO | metric_online:main2:781 - save train test done /root/data/Research1//feature/finalcomd//B8Wstats250412/B8Wstats250412_0--combo52
2025-06-13 19:10:57 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:10:58 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:10:59 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:10:59 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:01 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:02 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:03 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:03 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:04 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:04 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:05 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:05 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:06 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:07 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:08 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:08 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:10 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:10 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:11 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:12 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:12 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:12 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:13 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:14 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:14 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:15 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:15 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:15 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:17 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:18 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:18 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:18 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:19 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:20 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:20 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:20 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:21 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:21 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:22 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:22 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:23 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:24 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:24 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:24 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:25 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:11:26 | 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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2025-06-13 19:22:19 | INFO | metric_online:run_optimize_portfolio_new_with_sector_constraints:463 - [v7] 优化前的夏普率: 1.04248
2025-06-13 19:22:19 | INFO | metric_online:run_optimize_portfolio_new_with_sector_constraints:464 - [v7] 优化后的夏普率: 0.71254
2025-06-13 19:22:20 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:22:21 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:22:22 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:22:23 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:22:24 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:22:24 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:22:25 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:22:26 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:22:27 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:22:28 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:22:28 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:22:29 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:22:29 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:22:30 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:22:31 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:22:32 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:22:32 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:22:33 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:22:33 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:22:33 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:22:35 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:22:35 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:22:36 | 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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2025-06-13 19:33:24 | INFO | metric_online:run_optimize_portfolio_new_with_sector_constraints:463 - [v8] 优化前的夏普率: 0.76457
2025-06-13 19:33:24 | INFO | metric_online:run_optimize_portfolio_new_with_sector_constraints:464 - [v8] 优化后的夏普率: 0.96367
2025-06-13 19:33:25 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:33:25 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:33:27 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:33:28 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:33:28 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:33:29 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:33:30 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:33:30 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:33:31 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:33:32 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:33:33 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:33:34 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:33:34 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:33:34 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:33:36 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:33:36 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:33:37 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:33:37 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:33:38 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:33:38 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:33:39 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:33:40 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-13 19:33:40 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
[2025-06-13 19:33:42,201][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.
[2025-06-13 19:33:42,202][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.
[2025-06-13 19:33:42,210][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.
[2025-06-13 19:33:42,211][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.
[2025-06-13 19:33:42,218][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.
[2025-06-13 19:33:42,219][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.
[2025-06-13 19:33:44,341][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.
[2025-06-13 19:33:44,342][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.
[2025-06-13 19:33:44,351][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.
[2025-06-13 19:33:44,353][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.
[2025-06-13 19:33:44,360][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.
[2025-06-13 19:33:44,361][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.
[2025-06-13 19:33:46,272][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.
[2025-06-13 19:33:46,273][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.
[2025-06-13 19:33:46,280][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.
[2025-06-13 19:33:46,281][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.
[2025-06-13 19:33:46,289][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.
[2025-06-13 19:33:46,290][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.
2025-06-13 19:33:50 | INFO | metric_online:run_with_hydra:919 - {'action': 'parallel_done', 'success_count': 1, 'fail_count': 0}
2025-06-13 19:33:50 | INFO | metric_online:run_with_hydra:924 - {'action': 'success', 'description': 'metric_online 完成'}