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south-forecast.2025-03-25.0.log

south-forecast.2025-03-25.0.log 26 KB
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  1. 2025-03-25 08:48:02,492 - module_wrapper.py - WARNING - From E:\compete\app\model\losses.py:10: The name tf.set_random_seed is deprecated. Please use tf.compat.v1.set_random_seed instead.
    2. 

  2.  - _tfmw_add_deprecation_warning
    3. 

  3. 2025-03-25 08:48:02,832 - tf_lstm_train.py - INFO - Program starts execution! - model_training
    4. 

  4. 2025-03-25 08:48:02,886 - data_cleaning.py - INFO - 开始清洗：训练集…… - cleaning
    5. 

  5. 2025-03-25 08:48:02,895 - data_cleaning.py - INFO - 列清洗：清洗的列有：{'HubSpeed', 'HubDireciton'} - data_column_cleaning
    6. 

  6. 2025-03-25 08:48:02,913 - data_cleaning.py - INFO - 行清洗：清洗的行数有：881，缺失的列有： - key_field_row_cleaning
    7. 

  7. 2025-03-25 08:48:02,933 - data_handler.py - INFO - 2022-05-05 23:45:00 ~ 2022-05-09 00:00:00 - missing_time_splite
    8. 

  8. 2025-03-25 08:48:02,933 - data_handler.py - INFO - 缺失点数：288.0 - missing_time_splite
    9. 

  9. 2025-03-25 08:48:02,966 - data_handler.py - INFO - 2022-06-25 07:45:00 ~ 2022-06-25 08:15:00 - missing_time_splite
    10. 

  10. 2025-03-25 08:48:02,966 - data_handler.py - INFO - 缺失点数：1.0 - missing_time_splite
    11. 

  11. 2025-03-25 08:48:02,966 - data_handler.py - INFO - 需要补值的点数：1.0 - missing_time_splite
    12. 

  12. 2025-03-25 08:48:02,967 - data_handler.py - INFO - 2022-06-27 06:45:00 ~ 2022-06-27 07:15:00 - missing_time_splite
    13. 

  13. 2025-03-25 08:48:02,968 - data_handler.py - INFO - 缺失点数：1.0 - missing_time_splite
    14. 

  14. 2025-03-25 08:48:02,968 - data_handler.py - INFO - 需要补值的点数：1.0 - missing_time_splite
    15. 

  15. 2025-03-25 08:48:02,971 - data_handler.py - INFO - 2022-07-01 06:30:00 ~ 2022-07-01 23:45:00 - missing_time_splite
    16. 

  16. 2025-03-25 08:48:02,971 - data_handler.py - INFO - 缺失点数：68.0 - missing_time_splite
    17. 

  17. 2025-03-25 08:48:02,976 - data_handler.py - INFO - 2022-07-08 06:15:00 ~ 2022-07-08 23:45:00 - missing_time_splite
    18. 

  18. 2025-03-25 08:48:02,977 - data_handler.py - INFO - 缺失点数：69.0 - missing_time_splite
    19. 

  19. 2025-03-25 08:48:02,978 - data_handler.py - INFO - 2022-07-09 06:15:00 ~ 2022-07-09 23:45:00 - missing_time_splite
    20. 

  20. 2025-03-25 08:48:02,978 - data_handler.py - INFO - 缺失点数：69.0 - missing_time_splite
    21. 

  21. 2025-03-25 08:48:02,979 - data_handler.py - INFO - 2022-07-10 06:15:00 ~ 2022-07-10 23:45:00 - missing_time_splite
    22. 

  22. 2025-03-25 08:48:02,979 - data_handler.py - INFO - 缺失点数：69.0 - missing_time_splite
    23. 

  23. 2025-03-25 08:48:02,980 - data_handler.py - INFO - 2022-07-11 06:00:00 ~ 2022-07-11 23:45:00 - missing_time_splite
    24. 

  24. 2025-03-25 08:48:02,980 - data_handler.py - INFO - 缺失点数：70.0 - missing_time_splite
    25. 

  25. 2025-03-25 08:48:02,981 - data_handler.py - INFO - 2022-07-12 06:00:00 ~ 2022-07-12 23:45:00 - missing_time_splite
    26. 

  26. 2025-03-25 08:48:02,981 - data_handler.py - INFO - 缺失点数：70.0 - missing_time_splite
    27. 

  27. 2025-03-25 08:48:02,982 - data_handler.py - INFO - 2022-07-13 06:00:00 ~ 2022-07-13 23:45:00 - missing_time_splite
    28. 

  28. 2025-03-25 08:48:02,982 - data_handler.py - INFO - 缺失点数：70.0 - missing_time_splite
    29. 

  29. 2025-03-25 08:48:02,984 - data_handler.py - INFO - 2022-07-14 23:00:00 ~ 2022-07-14 23:45:00 - missing_time_splite
    30. 

  30. 2025-03-25 08:48:02,984 - data_handler.py - INFO - 缺失点数：2.0 - missing_time_splite
    31. 

  31. 2025-03-25 08:48:02,984 - data_handler.py - INFO - 需要补值的点数：2.0 - missing_time_splite
    32. 

  32. 2025-03-25 08:48:02,997 - data_handler.py - INFO - 2022-08-01 20:00:00 ~ 2022-08-01 23:45:00 - missing_time_splite
    33. 

  33. 2025-03-25 08:48:02,997 - data_handler.py - INFO - 缺失点数：14.0 - missing_time_splite
    34. 

  34. 2025-03-25 08:48:02,999 - data_handler.py - INFO - 2022-08-02 21:00:00 ~ 2022-08-02 23:45:00 - missing_time_splite
    35. 

  35. 2025-03-25 08:48:02,999 - data_handler.py - INFO - 缺失点数：10.0 - missing_time_splite
    36. 

  36. 2025-03-25 08:48:03,000 - data_handler.py - INFO - 2022-08-04 00:00:00 ~ 2022-08-04 23:15:00 - missing_time_splite
    37. 

  37. 2025-03-25 08:48:03,001 - data_handler.py - INFO - 缺失点数：92.0 - missing_time_splite
    38. 

  38. 2025-03-25 08:48:03,001 - data_handler.py - INFO - 2022-08-05 00:00:00 ~ 2022-08-05 23:15:00 - missing_time_splite
    39. 

  39. 2025-03-25 08:48:03,001 - data_handler.py - INFO - 缺失点数：92.0 - missing_time_splite
    40. 

  40. 2025-03-25 08:48:03,002 - data_handler.py - INFO - 2022-08-06 00:00:00 ~ 2022-08-06 23:15:00 - missing_time_splite
    41. 

  41. 2025-03-25 08:48:03,002 - data_handler.py - INFO - 缺失点数：92.0 - missing_time_splite
    42. 

  42. 2025-03-25 08:48:03,003 - data_handler.py - INFO - 2022-08-07 00:00:00 ~ 2022-08-07 23:15:00 - missing_time_splite
    43. 

  43. 2025-03-25 08:48:03,003 - data_handler.py - INFO - 缺失点数：92.0 - missing_time_splite
    44. 

  44. 2025-03-25 08:48:03,005 - data_handler.py - INFO - 数据总数：8207, 时序缺失的间隔：3, 其中，较长的时间间隔：14 - missing_time_splite
    45. 

  45. 2025-03-25 08:48:03,005 - data_handler.py - INFO - 需要补值的总点数：4.0 - missing_time_splite
    46. 

  46. 2025-03-25 08:48:03,005 - data_handler.py - INFO - 再次测算，需要插值的总点数为：4.0 - fill_train_data
    47. 

  47. 2025-03-25 08:48:03,014 - data_handler.py - INFO - 2022-05-02 08:00:00 ~ 2022-05-05 23:45:00 有 352 个点, 填补 0 个点. - data_fill
    48. 

  48. 2025-03-25 08:48:03,017 - data_handler.py - INFO - 2022-05-09 00:00:00 ~ 2022-07-01 06:30:00 有 5115 个点, 填补 2 个点. - data_fill
    49. 

  49. 2025-03-25 08:48:03,019 - data_handler.py - INFO - 2022-07-01 23:45:00 ~ 2022-07-08 06:15:00 有 603 个点, 填补 0 个点. - data_fill
    50. 

  50. 2025-03-25 08:48:03,020 - data_handler.py - INFO - 2022-07-08 23:45:00 ~ 2022-07-09 06:15:00 有 27 个点, 填补 0 个点. - data_fill
    51. 

  51. 2025-03-25 08:48:03,021 - data_handler.py - INFO - 2022-07-09 23:45:00 ~ 2022-07-10 06:15:00 有 27 个点, 填补 0 个点. - data_fill
    52. 

  52. 2025-03-25 08:48:03,022 - data_handler.py - INFO - 2022-07-10 23:45:00 ~ 2022-07-11 06:00:00 有 26 个点, 填补 0 个点. - data_fill
    53. 

  53. 2025-03-25 08:48:03,023 - data_handler.py - INFO - 2022-07-11 23:45:00 ~ 2022-07-12 06:00:00 有 26 个点, 填补 0 个点. - data_fill
    54. 

  54. 2025-03-25 08:48:03,024 - data_handler.py - INFO - 2022-07-12 23:45:00 ~ 2022-07-13 06:00:00 有 26 个点, 填补 0 个点. - data_fill
    55. 

  55. 2025-03-25 08:48:03,026 - data_handler.py - INFO - 2022-07-13 23:45:00 ~ 2022-08-01 20:00:00 有 1810 个点, 填补 2 个点. - data_fill
    56. 

  56. 2025-03-25 08:48:03,027 - data_handler.py - INFO - 2022-08-01 23:45:00 ~ 2022-08-02 21:00:00 有 86 个点, 填补 0 个点. - data_fill
    57. 

  57. 2025-03-25 08:48:03,028 - data_handler.py - INFO - 2022-08-02 23:45:00 ~ 2022-08-04 00:00:00 有 98 个点, 填补 0 个点. - data_fill
    58. 

  58. 2025-03-25 08:48:03,029 - data_handler.py - INFO - 2022-08-04 23:15:00 ~ 2022-08-05 00:00:00 有 4 个点, 填补 0 个点. - data_fill
    59. 

  59. 2025-03-25 08:48:03,031 - data_handler.py - INFO - 2022-08-05 23:15:00 ~ 2022-08-06 00:00:00 有 4 个点, 填补 0 个点. - data_fill
    60. 

  60. 2025-03-25 08:48:03,032 - data_handler.py - INFO - 2022-08-06 23:15:00 ~ 2022-08-07 00:00:00 有 4 个点, 填补 0 个点. - data_fill
    61. 

  61. 2025-03-25 08:48:03,033 - data_handler.py - INFO - 2022-08-07 23:15:00 ~ 2022-08-07 23:45:00 有 3 个点, 填补 0 个点. - data_fill
    62. 

  62. 2025-03-25 08:48:03,033 - data_handler.py - INFO - 训练集分成了15段，实际一共补值4点 - data_fill
    63. 

  63. 2025-03-25 08:48:05,457 - data_handler.py - INFO - 特征处理-训练数据-不满足time_step - get_train_data
    64. 

  64. 2025-03-25 08:48:05,457 - data_handler.py - INFO - 特征处理-训练数据-无法进行最小分割 - get_train_data
    65. 

  65. 2025-03-25 08:48:05,457 - data_handler.py - INFO - 特征处理-训练数据-不满足time_step - get_train_data
    66. 

  66. 2025-03-25 08:48:05,457 - data_handler.py - INFO - 特征处理-训练数据-无法进行最小分割 - get_train_data
    67. 

  67. 2025-03-25 08:48:05,457 - data_handler.py - INFO - 特征处理-训练数据-不满足time_step - get_train_data
    68. 

  68. 2025-03-25 08:48:05,457 - data_handler.py - INFO - 特征处理-训练数据-无法进行最小分割 - get_train_data
    69. 

  69. 2025-03-25 08:48:05,457 - data_handler.py - INFO - 特征处理-训练数据-不满足time_step - get_train_data
    70. 

  70. 2025-03-25 08:48:05,457 - data_handler.py - INFO - 特征处理-训练数据-无法进行最小分割 - get_train_data
    71. 

  71. 2025-03-25 08:48:05,669 - dbmg.py - INFO - ⚠️ 未找到模型 'fmi' 的有效记录 - get_keras_model_from_mongo
    72. 

  72. 2025-03-25 08:48:05,670 - tf_lstm.py - INFO - 加强训练加载模型权重失败:('cannot unpack non-iterable NoneType object',) - train_init
    73. 

  73. 2025-03-25 08:48:13,323 - tf_lstm.py - INFO - -----模型训练经过28轮迭代----- - training
    74. 

  74. 2025-03-25 08:48:13,323 - tf_lstm.py - INFO - 训练集损失函数为：[0.98709 0.4857  0.38789 0.34428 0.31769 0.2972  0.28397 0.27552 0.27048
    75. 

  75.  0.26568 0.26268 0.2593  0.25744 0.25489 0.25417 0.25239 0.2496  0.25125
    76. 

  76.  0.24856 0.2473  0.24671 0.24601 0.24413 0.24449 0.24437 0.24263 0.24266
    77. 

  77.  0.24314] - training
    78. 

  78. 2025-03-25 08:48:13,323 - tf_lstm.py - INFO - 验证集损失函数为：[0.61994 0.45012 0.40129 0.37275 0.3428  0.32806 0.32041 0.3169  0.31217
    79. 

  79.  0.30889 0.30421 0.30505 0.30078 0.3012  0.29778 0.29507 0.29904 0.2944
    80. 

  80.  0.30124 0.30423 0.31063 0.30335 0.30427 0.3074  0.30603 0.30948 0.30855
    81. 

  81.  0.30437] - training
    82. 

  82. 2025-03-25 08:48:13,364 - dbmg.py - INFO - ✅ 模型 fmi 保存成功 | 文档ID: 67e1fd4dce6f69e640c3ad38 - insert_trained_model_into_mongo
    83. 

  83. 2025-03-25 08:48:13,394 - dbmg.py - INFO - ✅ 缩放器 fmi 保存成功 | 文档ID: 67e1fd4dce6f69e640c3ad3a - insert_scaler_model_into_mongo
    84. 

  84. 2025-03-25 08:48:41,782 - module_wrapper.py - WARNING - From E:\compete\app\model\losses.py:10: The name tf.set_random_seed is deprecated. Please use tf.compat.v1.set_random_seed instead.
    85. 

  85.  - _tfmw_add_deprecation_warning
    86. 

  86. 2025-03-25 08:48:42,030 - dbmg.py - INFO - ✅ 成功加载 fmi 的缩放器 (版本时间: 2025-03-25 08:48:13) - get_scaler_model_from_mongo
    87. 

  87. 2025-03-25 08:48:42,121 - dbmg.py - INFO - fmi 模型成功从 MongoDB 加载！ - get_keras_model_from_mongo
    88. 

  88. 2025-03-25 08:48:42,122 - dbmg.py - INFO - 🧹 已清理临时文件: C:\Users\ADMINI~1\AppData\Local\Temp\tmph1bvs151.keras - get_keras_model_from_mongo
    89. 

  89. 2025-03-25 08:48:42,429 - tf_lstm.py - INFO - 执行预测方法 - predict
    90. 

  90. 2025-03-25 09:02:04,620 - module_wrapper.py - WARNING - From E:\compete\app\model\losses.py:10: The name tf.set_random_seed is deprecated. Please use tf.compat.v1.set_random_seed instead.
    91. 

  91.  - _tfmw_add_deprecation_warning
    92. 

  92. 2025-03-25 10:11:55,993 - module_wrapper.py - WARNING - From E:\compete\app\model\losses.py:10: The name tf.set_random_seed is deprecated. Please use tf.compat.v1.set_random_seed instead.
    93. 

  93.  - _tfmw_add_deprecation_warning
    94. 

  94. 2025-03-25 10:11:56,189 - tf_lstm_train.py - INFO - Program starts execution! - model_training
    95. 

  95. 2025-03-25 10:11:56,241 - data_cleaning.py - INFO - 开始清洗：训练集…… - cleaning
    96. 

  96. 2025-03-25 10:11:56,250 - data_cleaning.py - INFO - 列清洗：清洗的列有：{'HubDireciton', 'HubSpeed'} - data_column_cleaning
    97. 

  97. 2025-03-25 10:11:56,266 - data_cleaning.py - INFO - 行清洗：清洗的行数有：881，缺失的列有： - key_field_row_cleaning
    98. 

  98. 2025-03-25 10:11:56,275 - data_handler.py - INFO - 2022-05-05 23:45:00 ~ 2022-05-09 00:00:00 - missing_time_splite
    99. 

  99. 2025-03-25 10:11:56,276 - data_handler.py - INFO - 缺失点数：288.0 - missing_time_splite
    100. 

  100. 2025-03-25 10:11:56,308 - data_handler.py - INFO - 2022-06-25 07:45:00 ~ 2022-06-25 08:15:00 - missing_time_splite
    101. 

  101. 2025-03-25 10:11:56,308 - data_handler.py - INFO - 缺失点数：1.0 - missing_time_splite
    102. 

  102. 2025-03-25 10:11:56,308 - data_handler.py - INFO - 需要补值的点数：1.0 - missing_time_splite
    103. 

  103. 2025-03-25 10:11:56,311 - data_handler.py - INFO - 2022-06-27 06:45:00 ~ 2022-06-27 07:15:00 - missing_time_splite
    104. 

  104. 2025-03-25 10:11:56,311 - data_handler.py - INFO - 缺失点数：1.0 - missing_time_splite
    105. 

  105. 2025-03-25 10:11:56,311 - data_handler.py - INFO - 需要补值的点数：1.0 - missing_time_splite
    106. 

  106. 2025-03-25 10:11:56,314 - data_handler.py - INFO - 2022-07-01 06:30:00 ~ 2022-07-01 23:45:00 - missing_time_splite
    107. 

  107. 2025-03-25 10:11:56,314 - data_handler.py - INFO - 缺失点数：68.0 - missing_time_splite
    108. 

  108. 2025-03-25 10:11:56,320 - data_handler.py - INFO - 2022-07-08 06:15:00 ~ 2022-07-08 23:45:00 - missing_time_splite
    109. 

  109. 2025-03-25 10:11:56,320 - data_handler.py - INFO - 缺失点数：69.0 - missing_time_splite
    110. 

  110. 2025-03-25 10:11:56,321 - data_handler.py - INFO - 2022-07-09 06:15:00 ~ 2022-07-09 23:45:00 - missing_time_splite
    111. 

  111. 2025-03-25 10:11:56,321 - data_handler.py - INFO - 缺失点数：69.0 - missing_time_splite
    112. 

  112. 2025-03-25 10:11:56,322 - data_handler.py - INFO - 2022-07-10 06:15:00 ~ 2022-07-10 23:45:00 - missing_time_splite
    113. 

  113. 2025-03-25 10:11:56,322 - data_handler.py - INFO - 缺失点数：69.0 - missing_time_splite
    114. 

  114. 2025-03-25 10:11:56,323 - data_handler.py - INFO - 2022-07-11 06:00:00 ~ 2022-07-11 23:45:00 - missing_time_splite
    115. 

  115. 2025-03-25 10:11:56,323 - data_handler.py - INFO - 缺失点数：70.0 - missing_time_splite
    116. 

  116. 2025-03-25 10:11:56,324 - data_handler.py - INFO - 2022-07-12 06:00:00 ~ 2022-07-12 23:45:00 - missing_time_splite
    117. 

  117. 2025-03-25 10:11:56,324 - data_handler.py - INFO - 缺失点数：70.0 - missing_time_splite
    118. 

  118. 2025-03-25 10:11:56,325 - data_handler.py - INFO - 2022-07-13 06:00:00 ~ 2022-07-13 23:45:00 - missing_time_splite
    119. 

  119. 2025-03-25 10:11:56,325 - data_handler.py - INFO - 缺失点数：70.0 - missing_time_splite
    120. 

  120. 2025-03-25 10:11:56,326 - data_handler.py - INFO - 2022-07-14 23:00:00 ~ 2022-07-14 23:45:00 - missing_time_splite
    121. 

  121. 2025-03-25 10:11:56,326 - data_handler.py - INFO - 缺失点数：2.0 - missing_time_splite
    122. 

  122. 2025-03-25 10:11:56,326 - data_handler.py - INFO - 需要补值的点数：2.0 - missing_time_splite
    123. 

  123. 2025-03-25 10:11:56,339 - data_handler.py - INFO - 2022-08-01 20:00:00 ~ 2022-08-01 23:45:00 - missing_time_splite
    124. 

  124. 2025-03-25 10:11:56,339 - data_handler.py - INFO - 缺失点数：14.0 - missing_time_splite
    125. 

  125. 2025-03-25 10:11:56,341 - data_handler.py - INFO - 2022-08-02 21:00:00 ~ 2022-08-02 23:45:00 - missing_time_splite
    126. 

  126. 2025-03-25 10:11:56,341 - data_handler.py - INFO - 缺失点数：10.0 - missing_time_splite
    127. 

  127. 2025-03-25 10:11:56,342 - data_handler.py - INFO - 2022-08-04 00:00:00 ~ 2022-08-04 23:15:00 - missing_time_splite
    128. 

  128. 2025-03-25 10:11:56,342 - data_handler.py - INFO - 缺失点数：92.0 - missing_time_splite
    129. 

  129. 2025-03-25 10:11:56,343 - data_handler.py - INFO - 2022-08-05 00:00:00 ~ 2022-08-05 23:15:00 - missing_time_splite
    130. 

  130. 2025-03-25 10:11:56,343 - data_handler.py - INFO - 缺失点数：92.0 - missing_time_splite
    131. 

  131. 2025-03-25 10:11:56,344 - data_handler.py - INFO - 2022-08-06 00:00:00 ~ 2022-08-06 23:15:00 - missing_time_splite
    132. 

  132. 2025-03-25 10:11:56,344 - data_handler.py - INFO - 缺失点数：92.0 - missing_time_splite
    133. 

  133. 2025-03-25 10:11:56,345 - data_handler.py - INFO - 2022-08-07 00:00:00 ~ 2022-08-07 23:15:00 - missing_time_splite
    134. 

  134. 2025-03-25 10:11:56,345 - data_handler.py - INFO - 缺失点数：92.0 - missing_time_splite
    135. 

  135. 2025-03-25 10:11:56,346 - data_handler.py - INFO - 数据总数：8207, 时序缺失的间隔：3, 其中，较长的时间间隔：14 - missing_time_splite
    136. 

  136. 2025-03-25 10:11:56,348 - data_handler.py - INFO - 需要补值的总点数：4.0 - missing_time_splite
    137. 

  137. 2025-03-25 10:11:56,348 - data_handler.py - INFO - 再次测算，需要插值的总点数为：4.0 - fill_train_data
    138. 

  138. 2025-03-25 10:11:56,350 - data_handler.py - INFO - 2022-05-02 08:00:00 ~ 2022-05-05 23:45:00 有 352 个点, 填补 0 个点. - data_fill
    139. 

  139. 2025-03-25 10:11:56,353 - data_handler.py - INFO - 2022-05-09 00:00:00 ~ 2022-07-01 06:30:00 有 5115 个点, 填补 2 个点. - data_fill
    140. 

  140. 2025-03-25 10:11:56,354 - data_handler.py - INFO - 2022-07-01 23:45:00 ~ 2022-07-08 06:15:00 有 603 个点, 填补 0 个点. - data_fill
    141. 

  141. 2025-03-25 10:11:56,355 - data_handler.py - INFO - 2022-07-08 23:45:00 ~ 2022-07-09 06:15:00 有 27 个点, 填补 0 个点. - data_fill
    142. 

  142. 2025-03-25 10:11:56,356 - data_handler.py - INFO - 2022-07-09 23:45:00 ~ 2022-07-10 06:15:00 有 27 个点, 填补 0 个点. - data_fill
    143. 

  143. 2025-03-25 10:11:56,357 - data_handler.py - INFO - 2022-07-10 23:45:00 ~ 2022-07-11 06:00:00 有 26 个点, 填补 0 个点. - data_fill
    144. 

  144. 2025-03-25 10:11:56,359 - data_handler.py - INFO - 2022-07-11 23:45:00 ~ 2022-07-12 06:00:00 有 26 个点, 填补 0 个点. - data_fill
    145. 

  145. 2025-03-25 10:11:56,360 - data_handler.py - INFO - 2022-07-12 23:45:00 ~ 2022-07-13 06:00:00 有 26 个点, 填补 0 个点. - data_fill
    146. 

  146. 2025-03-25 10:11:56,362 - data_handler.py - INFO - 2022-07-13 23:45:00 ~ 2022-08-01 20:00:00 有 1810 个点, 填补 2 个点. - data_fill
    147. 

  147. 2025-03-25 10:11:56,363 - data_handler.py - INFO - 2022-08-01 23:45:00 ~ 2022-08-02 21:00:00 有 86 个点, 填补 0 个点. - data_fill
    148. 

  148. 2025-03-25 10:11:56,364 - data_handler.py - INFO - 2022-08-02 23:45:00 ~ 2022-08-04 00:00:00 有 98 个点, 填补 0 个点. - data_fill
    149. 

  149. 2025-03-25 10:11:56,365 - data_handler.py - INFO - 2022-08-04 23:15:00 ~ 2022-08-05 00:00:00 有 4 个点, 填补 0 个点. - data_fill
    150. 

  150. 2025-03-25 10:11:56,366 - data_handler.py - INFO - 2022-08-05 23:15:00 ~ 2022-08-06 00:00:00 有 4 个点, 填补 0 个点. - data_fill
    151. 

  151. 2025-03-25 10:11:56,367 - data_handler.py - INFO - 2022-08-06 23:15:00 ~ 2022-08-07 00:00:00 有 4 个点, 填补 0 个点. - data_fill
    152. 

  152. 2025-03-25 10:11:56,367 - data_handler.py - INFO - 2022-08-07 23:15:00 ~ 2022-08-07 23:45:00 有 3 个点, 填补 0 个点. - data_fill
    153. 

  153. 2025-03-25 10:11:56,367 - data_handler.py - INFO - 训练集分成了15段，实际一共补值4点 - data_fill
    154. 

  154. 2025-03-25 10:11:58,824 - data_handler.py - INFO - 特征处理-训练数据-不满足time_step - get_train_data
    155. 

  155. 2025-03-25 10:11:58,824 - data_handler.py - INFO - 特征处理-训练数据-无法进行最小分割 - get_train_data
    156. 

  156. 2025-03-25 10:11:58,825 - data_handler.py - INFO - 特征处理-训练数据-不满足time_step - get_train_data
    157. 

  157. 2025-03-25 10:11:58,825 - data_handler.py - INFO - 特征处理-训练数据-无法进行最小分割 - get_train_data
    158. 

  158. 2025-03-25 10:11:58,825 - data_handler.py - INFO - 特征处理-训练数据-不满足time_step - get_train_data
    159. 

  159. 2025-03-25 10:11:58,825 - data_handler.py - INFO - 特征处理-训练数据-无法进行最小分割 - get_train_data
    160. 

  160. 2025-03-25 10:11:58,825 - data_handler.py - INFO - 特征处理-训练数据-不满足time_step - get_train_data
    161. 

  161. 2025-03-25 10:11:58,825 - data_handler.py - INFO - 特征处理-训练数据-无法进行最小分割 - get_train_data
    162. 

  162. 2025-03-25 10:11:59,017 - dbmg.py - INFO - ⚠️ 未找到模型 'fmi' 的有效记录 - get_keras_model_from_mongo
    163. 

  163. 2025-03-25 10:11:59,017 - tf_lstm.py - INFO - 加强训练加载模型权重失败:('cannot unpack non-iterable NoneType object',) - train_init
    164. 

  164. 2025-03-25 10:12:22,986 - module_wrapper.py - WARNING - From E:\compete\app\model\losses.py:10: The name tf.set_random_seed is deprecated. Please use tf.compat.v1.set_random_seed instead.
    165. 

  165.  - _tfmw_add_deprecation_warning
    166. 

  166. 2025-03-25 10:12:23,176 - tf_lstm_train.py - INFO - Program starts execution! - model_training
    167. 

  167. 2025-03-25 10:12:23,229 - data_cleaning.py - INFO - 开始清洗：训练集…… - cleaning
    168. 

  168. 2025-03-25 10:12:23,238 - data_cleaning.py - INFO - 列清洗：清洗的列有：{'HubDireciton', 'HubSpeed'} - data_column_cleaning
    169. 

  169. 2025-03-25 10:12:23,253 - data_cleaning.py - INFO - 行清洗：清洗的行数有：881，缺失的列有： - key_field_row_cleaning
    170. 

  170. 2025-03-25 10:12:23,263 - data_handler.py - INFO - 2022-05-05 23:45:00 ~ 2022-05-09 00:00:00 - missing_time_splite
    171. 

  171. 2025-03-25 10:12:23,263 - data_handler.py - INFO - 缺失点数：288.0 - missing_time_splite
    172. 

  172. 2025-03-25 10:12:23,296 - data_handler.py - INFO - 2022-06-25 07:45:00 ~ 2022-06-25 08:15:00 - missing_time_splite
    173. 

  173. 2025-03-25 10:12:23,297 - data_handler.py - INFO - 缺失点数：1.0 - missing_time_splite
    174. 

  174. 2025-03-25 10:12:23,297 - data_handler.py - INFO - 需要补值的点数：1.0 - missing_time_splite
    175. 

  175. 2025-03-25 10:12:23,299 - data_handler.py - INFO - 2022-06-27 06:45:00 ~ 2022-06-27 07:15:00 - missing_time_splite
    176. 

  176. 2025-03-25 10:12:23,299 - data_handler.py - INFO - 缺失点数：1.0 - missing_time_splite
    177. 

  177. 2025-03-25 10:12:23,299 - data_handler.py - INFO - 需要补值的点数：1.0 - missing_time_splite
    178. 

  178. 2025-03-25 10:12:23,302 - data_handler.py - INFO - 2022-07-01 06:30:00 ~ 2022-07-01 23:45:00 - missing_time_splite
    179. 

  179. 2025-03-25 10:12:23,302 - data_handler.py - INFO - 缺失点数：68.0 - missing_time_splite
    180. 

  180. 2025-03-25 10:12:23,308 - data_handler.py - INFO - 2022-07-08 06:15:00 ~ 2022-07-08 23:45:00 - missing_time_splite
    181. 

  181. 2025-03-25 10:12:23,308 - data_handler.py - INFO - 缺失点数：69.0 - missing_time_splite
    182. 

  182. 2025-03-25 10:12:23,309 - data_handler.py - INFO - 2022-07-09 06:15:00 ~ 2022-07-09 23:45:00 - missing_time_splite
    183. 

  183. 2025-03-25 10:12:23,309 - data_handler.py - INFO - 缺失点数：69.0 - missing_time_splite
    184. 

  184. 2025-03-25 10:12:23,310 - data_handler.py - INFO - 2022-07-10 06:15:00 ~ 2022-07-10 23:45:00 - missing_time_splite
    185. 

  185. 2025-03-25 10:12:23,310 - data_handler.py - INFO - 缺失点数：69.0 - missing_time_splite
    186. 

  186. 2025-03-25 10:12:23,311 - data_handler.py - INFO - 2022-07-11 06:00:00 ~ 2022-07-11 23:45:00 - missing_time_splite
    187. 

  187. 2025-03-25 10:12:23,311 - data_handler.py - INFO - 缺失点数：70.0 - missing_time_splite
    188. 

  188. 2025-03-25 10:12:23,312 - data_handler.py - INFO - 2022-07-12 06:00:00 ~ 2022-07-12 23:45:00 - missing_time_splite
    189. 

  189. 2025-03-25 10:12:23,312 - data_handler.py - INFO - 缺失点数：70.0 - missing_time_splite
    190. 

  190. 2025-03-25 10:12:23,313 - data_handler.py - INFO - 2022-07-13 06:00:00 ~ 2022-07-13 23:45:00 - missing_time_splite
    191. 

  191. 2025-03-25 10:12:23,313 - data_handler.py - INFO - 缺失点数：70.0 - missing_time_splite
    192. 

  192. 2025-03-25 10:12:23,314 - data_handler.py - INFO - 2022-07-14 23:00:00 ~ 2022-07-14 23:45:00 - missing_time_splite
    193. 

  193. 2025-03-25 10:12:23,314 - data_handler.py - INFO - 缺失点数：2.0 - missing_time_splite
    194. 

  194. 2025-03-25 10:12:23,314 - data_handler.py - INFO - 需要补值的点数：2.0 - missing_time_splite
    195. 

  195. 2025-03-25 10:12:23,328 - data_handler.py - INFO - 2022-08-01 20:00:00 ~ 2022-08-01 23:45:00 - missing_time_splite
    196. 

  196. 2025-03-25 10:12:23,328 - data_handler.py - INFO - 缺失点数：14.0 - missing_time_splite
    197. 

  197. 2025-03-25 10:12:23,329 - data_handler.py - INFO - 2022-08-02 21:00:00 ~ 2022-08-02 23:45:00 - missing_time_splite
    198. 

  198. 2025-03-25 10:12:23,329 - data_handler.py - INFO - 缺失点数：10.0 - missing_time_splite
    199. 

  199. 2025-03-25 10:12:23,331 - data_handler.py - INFO - 2022-08-04 00:00:00 ~ 2022-08-04 23:15:00 - missing_time_splite
    200. 

  200. 2025-03-25 10:12:23,331 - data_handler.py - INFO - 缺失点数：92.0 - missing_time_splite
    201. 

  201. 2025-03-25 10:12:23,332 - data_handler.py - INFO - 2022-08-05 00:00:00 ~ 2022-08-05 23:15:00 - missing_time_splite
    202. 

  202. 2025-03-25 10:12:23,332 - data_handler.py - INFO - 缺失点数：92.0 - missing_time_splite
    203. 

  203. 2025-03-25 10:12:23,333 - data_handler.py - INFO - 2022-08-06 00:00:00 ~ 2022-08-06 23:15:00 - missing_time_splite
    204. 

  204. 2025-03-25 10:12:23,333 - data_handler.py - INFO - 缺失点数：92.0 - missing_time_splite
    205. 

  205. 2025-03-25 10:12:23,334 - data_handler.py - INFO - 2022-08-07 00:00:00 ~ 2022-08-07 23:15:00 - missing_time_splite
    206. 

  206. 2025-03-25 10:12:23,334 - data_handler.py - INFO - 缺失点数：92.0 - missing_time_splite
    207. 

  207. 2025-03-25 10:12:23,335 - data_handler.py - INFO - 数据总数：8207, 时序缺失的间隔：3, 其中，较长的时间间隔：14 - missing_time_splite
    208. 

  208. 2025-03-25 10:12:23,335 - data_handler.py - INFO - 需要补值的总点数：4.0 - missing_time_splite
    209. 

  209. 2025-03-25 10:12:23,336 - data_handler.py - INFO - 再次测算，需要插值的总点数为：4.0 - fill_train_data
    210. 

  210. 2025-03-25 10:12:23,337 - data_handler.py - INFO - 2022-05-02 08:00:00 ~ 2022-05-05 23:45:00 有 352 个点, 填补 0 个点. - data_fill
    211. 

  211. 2025-03-25 10:12:23,341 - data_handler.py - INFO - 2022-05-09 00:00:00 ~ 2022-07-01 06:30:00 有 5115 个点, 填补 2 个点. - data_fill
    212. 

  212. 2025-03-25 10:12:23,343 - data_handler.py - INFO - 2022-07-01 23:45:00 ~ 2022-07-08 06:15:00 有 603 个点, 填补 0 个点. - data_fill
    213. 

  213. 2025-03-25 10:12:23,344 - data_handler.py - INFO - 2022-07-08 23:45:00 ~ 2022-07-09 06:15:00 有 27 个点, 填补 0 个点. - data_fill
    214. 

  214. 2025-03-25 10:12:23,345 - data_handler.py - INFO - 2022-07-09 23:45:00 ~ 2022-07-10 06:15:00 有 27 个点, 填补 0 个点. - data_fill
    215. 

  215. 2025-03-25 10:12:23,346 - data_handler.py - INFO - 2022-07-10 23:45:00 ~ 2022-07-11 06:00:00 有 26 个点, 填补 0 个点. - data_fill
    216. 

  216. 2025-03-25 10:12:23,347 - data_handler.py - INFO - 2022-07-11 23:45:00 ~ 2022-07-12 06:00:00 有 26 个点, 填补 0 个点. - data_fill
    217. 

  217. 2025-03-25 10:12:23,348 - data_handler.py - INFO - 2022-07-12 23:45:00 ~ 2022-07-13 06:00:00 有 26 个点, 填补 0 个点. - data_fill
    218. 

  218. 2025-03-25 10:12:23,349 - data_handler.py - INFO - 2022-07-13 23:45:00 ~ 2022-08-01 20:00:00 有 1810 个点, 填补 2 个点. - data_fill
    219. 

  219. 2025-03-25 10:12:23,350 - data_handler.py - INFO - 2022-08-01 23:45:00 ~ 2022-08-02 21:00:00 有 86 个点, 填补 0 个点. - data_fill
    220. 

  220. 2025-03-25 10:12:23,352 - data_handler.py - INFO - 2022-08-02 23:45:00 ~ 2022-08-04 00:00:00 有 98 个点, 填补 0 个点. - data_fill
    221. 

  221. 2025-03-25 10:12:23,353 - data_handler.py - INFO - 2022-08-04 23:15:00 ~ 2022-08-05 00:00:00 有 4 个点, 填补 0 个点. - data_fill
    222. 

  222. 2025-03-25 10:12:23,354 - data_handler.py - INFO - 2022-08-05 23:15:00 ~ 2022-08-06 00:00:00 有 4 个点, 填补 0 个点. - data_fill
    223. 

  223. 2025-03-25 10:12:23,355 - data_handler.py - INFO - 2022-08-06 23:15:00 ~ 2022-08-07 00:00:00 有 4 个点, 填补 0 个点. - data_fill
    224. 

  224. 2025-03-25 10:12:23,356 - data_handler.py - INFO - 2022-08-07 23:15:00 ~ 2022-08-07 23:45:00 有 3 个点, 填补 0 个点. - data_fill
    225. 

  225. 2025-03-25 10:12:23,356 - data_handler.py - INFO - 训练集分成了15段，实际一共补值4点 - data_fill
    226. 

  226. 2025-03-25 10:12:25,819 - data_handler.py - INFO - 特征处理-训练数据-不满足time_step - get_train_data
    227. 

  227. 2025-03-25 10:12:25,819 - data_handler.py - INFO - 特征处理-训练数据-无法进行最小分割 - get_train_data
    228. 

  228. 2025-03-25 10:12:25,820 - data_handler.py - INFO - 特征处理-训练数据-不满足time_step - get_train_data
    229. 

  229. 2025-03-25 10:12:25,820 - data_handler.py - INFO - 特征处理-训练数据-无法进行最小分割 - get_train_data
    230. 

  230. 2025-03-25 10:12:25,820 - data_handler.py - INFO - 特征处理-训练数据-不满足time_step - get_train_data
    231. 

  231. 2025-03-25 10:12:25,820 - data_handler.py - INFO - 特征处理-训练数据-无法进行最小分割 - get_train_data
    232. 

  232. 2025-03-25 10:12:25,820 - data_handler.py - INFO - 特征处理-训练数据-不满足time_step - get_train_data
    233. 

  233. 2025-03-25 10:12:25,820 - data_handler.py - INFO - 特征处理-训练数据-无法进行最小分割 - get_train_data
    234. 

  234. 2025-03-25 10:12:26,012 - dbmg.py - INFO - ⚠️ 未找到模型 'fmi' 的有效记录 - get_keras_model_from_mongo
    235. 

  235. 2025-03-25 10:12:26,012 - tf_lstm.py - INFO - 加强训练加载模型权重失败:('cannot unpack non-iterable NoneType object',) - train_init
    236.