flexmeasures.data.models.forecasting.pipelines.train_predict

Classes

class flexmeasures.data.models.forecasting.pipelines.train_predict.TrainPredictPipeline(sensors: dict[str, int], regressors: list[str], future_regressors: list[str], target: str, model_save_dir: str, output_path: str, start_date: datetime, end_date: datetime, train_period_in_hours: int, sensor_to_save: Sensor, predict_start: datetime, predict_period_in_hours: int, max_forecast_horizon: int = 48, forecast_frequency: int = 1, probabilistic: bool = False, delete_model: bool = False)

__init__(sensors: dict[str, int], regressors: list[str], future_regressors: list[str], target: str, model_save_dir: str, output_path: str, start_date: datetime, end_date: datetime, train_period_in_hours: int, sensor_to_save: Sensor, predict_start: datetime, predict_period_in_hours: int, max_forecast_horizon: int = 48, forecast_frequency: int = 1, probabilistic: bool = False, delete_model: bool = False)

run_cycle(train_start: datetime, train_end: datetime, predict_start: datetime, predict_end: datetime, counter: int, multiplier: int, **kwargs)

Runs a single training and prediction cycle.