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PyAF 5.0 Final Touches : #230 #231 #232. Added some logs
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@antoinecarme
antoinecarme committed Mar 18, 2023
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124 changes: 124 additions & 0 deletions tests/references/func/test_final_touch_1.log
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INFO:pyaf.timing:('OPERATION_START', ('TRAINING', {'Signals': ['Signal'], 'Horizons': {'Signal': 2}}))
INFO:pyaf.timing:('OPERATION_START', ('SIGNAL_TRAINING', {'Signals': ['Signal'], 'Transformations': [('Signal', 'None', '_', 'T+S+R')], 'Cores': 1}))
INFO:pyaf.timing:('OPERATION_START', ('TRAINING', {'Signal': 'Signal', 'Horizon': 2, 'Transformation': '_Signal', 'DecompositionType': 'T+S+R'}))
INFO:pyaf.timing:('OPERATION_END_ELAPSED', 0.763, ('TRAINING', {'Signal': 'Signal', 'Horizon': 2, 'Transformation': '_Signal', 'DecompositionType': 'T+S+R'}))
INFO:pyaf.timing:('OPERATION_END_ELAPSED', 0.763, ('SIGNAL_TRAINING', {'Signals': ['Signal'], 'Transformations': [('Signal', 'None', '_', 'T+S+R')], 'Cores': 1}))
INFO:pyaf.timing:('OPERATION_START', ('FINALIZE_TRAINING', {'Signals': ['Signal'], 'Transformations': [('Signal', [('Signal', 'None', '_', 'T+S+R')])], 'Cores': 1}))
INFO:pyaf.timing:('OPERATION_START', ('MODEL_SELECTION', {'Signal': 'Signal', 'Transformations': [('Signal', 'None', '_', 'T+S+R')]}))
INFO:pyaf.timing:('OPERATION_END_ELAPSED', 0.003, ('MODEL_SELECTION', {'Signal': 'Signal', 'Transformations': [('Signal', 'None', '_', 'T+S+R')]}))
INFO:pyaf.timing:('OPERATION_START', ('UPDATE_BEST_MODEL_PERFS', {'Signal': 'Signal', 'Model': '_Signal_PolyTrend_residue_zeroCycle[0.0]_residue_NoAR'}))
INFO:pyaf.timing:('OPERATION_END_ELAPSED', 0.037, ('UPDATE_BEST_MODEL_PERFS', {'Signal': 'Signal', 'Model': '_Signal_PolyTrend_residue_zeroCycle[0.0]_residue_NoAR'}))
INFO:pyaf.timing:('OPERATION_START', ('COMPUTE_PREDICTION_INTERVALS', {'Signal': 'Signal'}))
INFO:pyaf.timing:('OPERATION_END_ELAPSED', 0.089, ('COMPUTE_PREDICTION_INTERVALS', {'Signal': 'Signal'}))
INFO:pyaf.timing:('OPERATION_END_ELAPSED', 0.13, ('FINALIZE_TRAINING', {'Signals': ['Signal'], 'Transformations': [('Signal', [('Signal', 'None', '_', 'T+S+R')])], 'Cores': 1}))
INFO:pyaf.timing:('OPERATION_END_ELAPSED', 1.317, ('TRAINING', {'Signals': ['Signal'], 'Horizons': {'Signal': 2}}))
INFO:pyaf.std:TIME_DETAIL TimeVariable='Date' TimeMin=0 TimeMax=15 TimeDelta=1 Horizon=2
INFO:pyaf.std:SIGNAL_DETAIL_ORIG SignalVariable='Signal' Length=16 Min=1 Max=481 Mean=171.0 StdDev=152.276065
INFO:pyaf.std:SIGNAL_DETAIL_TRANSFORMED TransformedSignalVariable='_Signal' Min=0.0 Max=1.0 Mean=0.354167 StdDev=0.317242
INFO:pyaf.std:DECOMPOSITION_TYPE 'T+S+R'
INFO:pyaf.std:BEST_TRANSOFORMATION_TYPE '_'
INFO:pyaf.std:BEST_DECOMPOSITION '_Signal_PolyTrend_residue_zeroCycle[0.0]_residue_NoAR' [PolyTrend + NoCycle + NoAR]
INFO:pyaf.std:TREND_DETAIL '_Signal_PolyTrend' [PolyTrend]
INFO:pyaf.std:CYCLE_DETAIL '_Signal_PolyTrend_residue_zeroCycle[0.0]' [NoCycle]
INFO:pyaf.std:AUTOREG_DETAIL '_Signal_PolyTrend_residue_zeroCycle[0.0]_residue_NoAR' [NoAR]
INFO:pyaf.std:MODEL_PERFS Fit STEP=1 {'MAPE': 0.0, 'RMSE': 0.0, 'MAE': 0.0, 'MASE': 0.0}
INFO:pyaf.std:MODEL_PERFS Forecast STEP=1 {'MAPE': 0.0, 'RMSE': 0.0, 'MAE': 0.0, 'MASE': 0.0}
INFO:pyaf.std:MODEL_PERFS Test STEP=1 {'MAPE': 0.0, 'RMSE': 0.0, 'MAE': 0.0, 'MASE': 0.0}
INFO:pyaf.std:MODEL_PERFS Fit STEP=2 {'MAPE': 0.0, 'RMSE': 0.0, 'MAE': 0.0, 'MASE': 0.0}
INFO:pyaf.std:MODEL_PERFS Forecast STEP=2 {'MAPE': 0.0, 'RMSE': 0.0, 'MAE': 0.0, 'MASE': 0.0}
INFO:pyaf.std:MODEL_PERFS Test STEP=2 {'MAPE': 0.0, 'RMSE': 0.0, 'MAE': 0.0, 'MASE': 0.0}
INFO:pyaf.std:MODEL_COMPLEXITY {'Decomposition': 'S', 'Transformation': 'S', 'Trend': 'M', 'Cycle': 'S', 'AR': 'S'} [MSSSS]
INFO:pyaf.std:SIGNAL_TRANSFORMATION_DETAIL_START
INFO:pyaf.std:SIGNAL_TRANSFORMATION_MODEL_VALUES NoTransf None
INFO:pyaf.std:SIGNAL_TRANSFORMATION_DETAIL_END
INFO:pyaf.std:TREND_DETAIL_START
INFO:pyaf.std:POLYNOMIAL_RIDGE_TREND PolyTrend (-0.0, array([0.0625, 0.9375, 0. ]))
INFO:pyaf.std:TREND_DETAIL_END
INFO:pyaf.std:CYCLE_MODEL_DETAIL_START
INFO:pyaf.std:ZERO_CYCLE_MODEL_VALUES _Signal_PolyTrend_residue_zeroCycle[0.0] 0.0 {}
INFO:pyaf.std:CYCLE_MODEL_DETAIL_END
INFO:pyaf.std:AR_MODEL_DETAIL_START
INFO:pyaf.std:AR_MODEL_DETAIL_END
INFO:pyaf.std:TRAINING_TIME_IN_SECONDS 1.123
INFO:pyaf.std:COMPETITION_DETAIL_START 'Signal'
INFO:pyaf.std:COMPETITION_DETAIL_SHORT_LIST 'Signal' 0 {'Transformation': '_Signal', 'DecompositionType': 'T+S+R', 'Model': '_Signal_PolyTrend_residue_zeroCycle[0.0]_residue_NoAR', 'Voting': 0, 'Complexity': 'MSSSS', 'Forecast_MASE_1': 0.0, 'Forecast_MASE_H': 0.0}
INFO:pyaf.std:COMPETITION_DETAIL_END 'Signal'
INFO:pyaf.timing:('OPERATION_START', ('PLOTTING', {'Signals': ['Signal']}))
INFO:pyaf.std:SAVING_PLOT ('Trend', 'outputs/FT_1_sixteen_rows__Signal_Trend_decomp_output.png')
INFO:pyaf.std:SAVING_PLOT ('Cycle', 'outputs/FT_1_sixteen_rows__Signal_Cycle_decomp_output.png')
INFO:pyaf.std:SAVING_PLOT ('AR', 'outputs/FT_1_sixteen_rows__Signal_AR_decomp_output.png')
INFO:pyaf.std:SAVING_PLOT ('TransformedForecast', 'outputs/FT_1_sixteen_rows__Signal_TransformedForecast_decomp_output.png')
INFO:pyaf.std:SAVING_PLOT ('Forecast', 'outputs/FT_1_sixteen_rows__Signal_Forecast_decomp_output.png')
INFO:pyaf.std:SAVING_PLOT ('PredictionIntervals', 'outputs/FT_1_sixteen_rows__Signal_prediction_intervals_output.png')
INFO:pyaf.std:SAVING_PLOT ('Quantiles', 'outputs/FT_1_sixteen_rows__Signal_quantiles_output.png')
INFO:pyaf.timing:('OPERATION_END_ELAPSED', 6.786, ('PLOTTING', {'Signals': ['Signal']}))
INFO:pyaf.timing:('OPERATION_START', ('FORECASTING', {'Signals': ['Signal'], 'Horizon': 2}))
INFO:pyaf.timing:('OPERATION_END_ELAPSED', 0.214, ('FORECASTING', {'Signals': ['Signal'], 'Horizon': 2}))
Date Signal
0 0 1
1 1 5
2 2 13
3 3 25
4 4 41
5 5 61
6 6 85
7 7 113
8 8 145
9 9 181
10 10 221
11 11 265
12 12 313
13 13 365
14 14 421
15 15 481
Index(['Split', 'Transformation', 'DecompositionType', 'Model',
'DetailedFormula', 'Category', 'Complexity', 'Fit_MASE_1', 'Fit_MASE_H',
'Forecast_MASE_1', 'Forecast_MASE_H', 'Test_MASE_1', 'Test_MASE_H',
'Voting'],
dtype='object')
[['_Signal_PolyTrend_residue_zeroCycle[0.0]_residue_NoAR' 0.0 0.0]]
Index(['Date', 'Signal', 'row_number', 'Date_Normalized', 'scaled_Signal',
'_Signal', 'Date_Normalized_^2', 'Date_Normalized_^3',
'_Signal_PolyTrend', '_Signal_PolyTrend_residue',
'_Signal_PolyTrend_residue_zeroCycle[0.0]',
'_Signal_PolyTrend_residue_zeroCycle[0.0]_residue',
'_Signal_PolyTrend_residue_zeroCycle[0.0]_residue_NoAR',
'_Signal_PolyTrend_residue_zeroCycle[0.0]_residue_NoAR_residue',
'Signal_Transformed', '_Signal_Trend', '_Signal_Trend_residue',
'_Signal_Cycle', '_Signal_Cycle_residue', '_Signal_AR',
'_Signal_AR_residue', '_Signal_TransformedForecast', 'Signal_Forecast',
'_Signal_TransformedResidue', 'Signal_Residue',
'Signal_Forecast_Lower_Bound', 'Signal_Forecast_Upper_Bound',
'Signal_Forecast_Quantile_25', 'Signal_Forecast_Quantile_50',
'Signal_Forecast_Quantile_75'],
dtype='object')
CHECK_COLUMN_DATA 0 Date int64 [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]
CHECK_COLUMN_DATA 1 Signal float64 [1.0, 5.0, 13.0, 25.0, 41.0, 61.0, 85.0, 113.0, 145.0, 181.0, 221.0, 265.0, 313.0, 365.0, 421.0, 481.0, nan, nan]
CHECK_COLUMN_DATA 2 row_number int64 [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]
CHECK_COLUMN_DATA 3 Date_Normalized float64 [0.0, 0.067, 0.133, 0.2, 0.267, 0.333, 0.4, 0.467, 0.533, 0.6, 0.667, 0.733, 0.8, 0.867, 0.933, 1.0, 1.067, 1.133]
CHECK_COLUMN_DATA 4 scaled_Signal float64 [0.0, 0.008, 0.025, 0.05, 0.083, 0.125, 0.175, 0.233, 0.3, 0.375, 0.458, 0.55, 0.65, 0.758, 0.875, 1.0, 1.133, 1.133]
CHECK_COLUMN_DATA 5 _Signal float64 [0.0, 0.008, 0.025, 0.05, 0.083, 0.125, 0.175, 0.233, 0.3, 0.375, 0.458, 0.55, 0.65, 0.758, 0.875, 1.0, nan, nan]
CHECK_COLUMN_DATA 6 Date_Normalized_^2 float64 [0.0, 0.004, 0.018, 0.04, 0.071, 0.111, 0.16, 0.218, 0.284, 0.36, 0.444, 0.538, 0.64, 0.751, 0.871, 1.0, 1.138, 1.284]
CHECK_COLUMN_DATA 7 Date_Normalized_^3 float64 [0.0, 0.0, 0.002, 0.008, 0.019, 0.037, 0.064, 0.102, 0.152, 0.216, 0.296, 0.394, 0.512, 0.651, 0.813, 1.0, 1.214, 1.456]
CHECK_COLUMN_DATA 8 _Signal_PolyTrend float64 [-0.0, 0.008, 0.025, 0.05, 0.083, 0.125, 0.175, 0.233, 0.3, 0.375, 0.458, 0.55, 0.65, 0.758, 0.875, 1.0, 1.133, 1.275]
CHECK_COLUMN_DATA 9 _Signal_PolyTrend_residue float64 [0.0, 0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.0, -0.0, nan, nan]
CHECK_COLUMN_DATA 10 _Signal_PolyTrend_residue_zeroCycle[0.0] float64 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
CHECK_COLUMN_DATA 11 _Signal_PolyTrend_residue_zeroCycle[0.0]_residue float64 [0.0, 0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.0, -0.0, nan, nan]
CHECK_COLUMN_DATA 12 _Signal_PolyTrend_residue_zeroCycle[0.0]_residue_NoAR float64 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
CHECK_COLUMN_DATA 13 _Signal_PolyTrend_residue_zeroCycle[0.0]_residue_NoAR_residue float64 [0.0, 0.008, 0.025, 0.05, 0.083, 0.125, 0.175, 0.233, 0.3, 0.375, 0.458, 0.55, 0.65, 0.758, 0.875, 1.0, nan, nan]
CHECK_COLUMN_DATA 14 Signal_Transformed float64 [0.0, 0.008, 0.025, 0.05, 0.083, 0.125, 0.175, 0.233, 0.3, 0.375, 0.458, 0.55, 0.65, 0.758, 0.875, 1.0, nan, nan]
CHECK_COLUMN_DATA 15 _Signal_Trend float64 [-0.0, 0.008, 0.025, 0.05, 0.083, 0.125, 0.175, 0.233, 0.3, 0.375, 0.458, 0.55, 0.65, 0.758, 0.875, 1.0, 1.133, 1.275]
CHECK_COLUMN_DATA 16 _Signal_Trend_residue float64 [0.0, 0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.0, -0.0, nan, nan]
CHECK_COLUMN_DATA 17 _Signal_Cycle float64 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
CHECK_COLUMN_DATA 18 _Signal_Cycle_residue float64 [0.0, 0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.0, -0.0, nan, nan]
CHECK_COLUMN_DATA 19 _Signal_AR float64 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
CHECK_COLUMN_DATA 20 _Signal_AR_residue float64 [0.0, 0.008, 0.025, 0.05, 0.083, 0.125, 0.175, 0.233, 0.3, 0.375, 0.458, 0.55, 0.65, 0.758, 0.875, 1.0, nan, nan]
CHECK_COLUMN_DATA 21 _Signal_TransformedForecast float64 [-0.0, 0.008, 0.025, 0.05, 0.083, 0.125, 0.175, 0.233, 0.3, 0.375, 0.458, 0.55, 0.65, 0.758, 0.875, 1.0, 1.133, 1.275]
CHECK_COLUMN_DATA 22 Signal_Forecast float64 [1.0, 5.0, 13.0, 25.0, 41.0, 61.0, 85.0, 113.0, 145.0, 181.0, 221.0, 265.0, 313.0, 365.0, 421.0, 481.0, 545.0, 613.0]
CHECK_COLUMN_DATA 23 _Signal_TransformedResidue float64 [0.0, 0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.0, -0.0, nan, nan]
CHECK_COLUMN_DATA 24 Signal_Residue float64 [0.0, 0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.0, -0.0, nan, nan]
CHECK_COLUMN_DATA 25 Signal_Forecast_Lower_Bound float64 [nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 545.0, 613.0]
CHECK_COLUMN_DATA 26 Signal_Forecast_Upper_Bound float64 [nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 545.0, 613.0]
CHECK_COLUMN_DATA 27 Signal_Forecast_Quantile_25 float64 [nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 545.0, 613.0]
CHECK_COLUMN_DATA 28 Signal_Forecast_Quantile_50 float64 [nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 545.0, 613.0]
CHECK_COLUMN_DATA 29 Signal_Forecast_Quantile_75 float64 [nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 545.0, 613.0]
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