openstef package#
Subpackages#
- openstef.data_classes package
- Submodules
- openstef.data_classes.data_prep module
- openstef.data_classes.model_specifications module
- openstef.data_classes.prediction_job module
PredictionJobDataClass
PredictionJobDataClass.Config
PredictionJobDataClass.alternative_forecast_model_pid
PredictionJobDataClass.backtest_split_func
PredictionJobDataClass.completeness_threshold
PredictionJobDataClass.data_prep_class
PredictionJobDataClass.default_modelspecs
PredictionJobDataClass.depends_on
PredictionJobDataClass.description
PredictionJobDataClass.flatliner_threshold_minutes
PredictionJobDataClass.forecast_type
PredictionJobDataClass.get()
PredictionJobDataClass.horizon_minutes
PredictionJobDataClass.hub_height
PredictionJobDataClass.id
PredictionJobDataClass.lat
PredictionJobDataClass.lon
PredictionJobDataClass.minimal_table_length
PredictionJobDataClass.model
PredictionJobDataClass.n_turbines
PredictionJobDataClass.name
PredictionJobDataClass.pipelines_to_run
PredictionJobDataClass.quantiles
PredictionJobDataClass.resolution_minutes
PredictionJobDataClass.save_train_forecasts
PredictionJobDataClass.sid
PredictionJobDataClass.train_components
PredictionJobDataClass.train_horizons_minutes
PredictionJobDataClass.train_split_func
PredictionJobDataClass.turbine_type
- openstef.data_classes.split_function module
- Module contents
- openstef.feature_engineering package
- Submodules
- openstef.feature_engineering.apply_features module
- openstef.feature_engineering.data_preparation module
- openstef.feature_engineering.feature_adder module
- openstef.feature_engineering.feature_applicator module
- openstef.feature_engineering.general module
- openstef.feature_engineering.historic_features module
- openstef.feature_engineering.holiday_features module
- openstef.feature_engineering.lag_features module
- openstef.feature_engineering.weather_features module
- Module contents
- openstef.metrics package
- openstef.model package
- Subpackages
- openstef.model.metamodels package
- openstef.model.regressors package
- Submodules
- openstef.model.regressors.arima module
- openstef.model.regressors.custom_regressor module
- openstef.model.regressors.dazls module
- openstef.model.regressors.lgbm module
- openstef.model.regressors.linear module
- openstef.model.regressors.proloaf module
- openstef.model.regressors.regressor module
- openstef.model.regressors.xgb module
- openstef.model.regressors.xgb_quantile module
- Module contents
- Submodules
- openstef.model.basecase module
- openstef.model.confidence_interval_applicator module
- openstef.model.fallback module
- openstef.model.model_creator module
- openstef.model.objective module
- openstef.model.objective_creator module
- openstef.model.serializer module
- openstef.model.standard_deviation_generator module
- Module contents
- Subpackages
- openstef.model_selection package
- openstef.monitoring package
- openstef.pipeline package
- Submodules
- openstef.pipeline.create_basecase_forecast module
- openstef.pipeline.create_component_forecast module
- openstef.pipeline.create_forecast module
- openstef.pipeline.optimize_hyperparameters module
- openstef.pipeline.train_create_forecast_backtest module
- openstef.pipeline.train_model module
- openstef.pipeline.utils module
- Module contents
- openstef.postprocessing package
- openstef.preprocessing package
- openstef.tasks package
- Subpackages
- Submodules
- openstef.tasks.calculate_kpi module
- openstef.tasks.create_basecase_forecast module
- openstef.tasks.create_components_forecast module
- openstef.tasks.create_forecast module
- openstef.tasks.create_solar_forecast module
- openstef.tasks.create_wind_forecast module
- openstef.tasks.optimize_hyperparameters module
- openstef.tasks.run_tracy module
- openstef.tasks.split_forecast module
- openstef.tasks.train_model module
- Module contents
- openstef.validation package
Submodules#
openstef.enums module#
- class openstef.enums.ForecastType(value)#
Bases:
Enum
An enumeration.
- BASECASE = 'basecase'#
- DEMAND = 'demand'#
- SOLAR = 'solar'#
- WIND = 'wind'#
- class openstef.enums.MLModelType(value)#
Bases:
Enum
An enumeration.
- ARIMA = 'arima'#
- LGB = 'lgb'#
- LINEAR = 'linear'#
- ProLoaf = 'proloaf'#
- XGB = 'xgb'#
- XGB_QUANTILE = 'xgb_quantile'#
openstef.exceptions module#
Openstef custom exceptions.
- exception openstef.exceptions.ComponentForecastTooShortHorizonError#
Bases:
Exception
Component forecasts should be available for at least 30 hours in advance.
- exception openstef.exceptions.InputDataInsufficientError#
Bases:
InputDataInvalidError
Insufficient input data.
- exception openstef.exceptions.InputDataInvalidError#
Bases:
Exception
Invalid input data.
- exception openstef.exceptions.InputDataOngoingZeroFlatlinerError#
Bases:
InputDataInvalidError
All recent load measurements are zero.
- exception openstef.exceptions.InputDataWrongColumnOrderError#
Bases:
InputDataInvalidError
Wrong column order input data.
- exception openstef.exceptions.ModelWithoutStDev#
Bases:
Exception
A machine learning model should have a valid standard deviation.
- exception openstef.exceptions.NoPredictedLoadError(pid, message='No predicted load found')#
Bases:
Exception
No predicted load for given datatime range.
- exception openstef.exceptions.NoRealisedLoadError(pid, message='No realised load found')#
Bases:
Exception
No realised load for given datetime range.
- exception openstef.exceptions.OldModelHigherScoreError#
Bases:
Exception
Old model has a higher score then new model.
- exception openstef.exceptions.PredictionJobException(metrics=None)#
Bases:
Exception
One or more prediction jobs raised an exception.
- exception openstef.exceptions.SkipSaveTrainingForecasts#
Bases:
Exception
If old model is better or too young, you don’t need to save the traing forcast.