commonpower.data_forecasting.forecasters.PerfectKnowledgeForecaster

class PerfectKnowledgeForecaster(frequency: timedelta = datetime.timedelta(seconds=3600), horizon: timedelta = datetime.timedelta(days=1))

Bases: Forecaster

This forecaster perfectly predicts future values. This means all time steps in the prediction horizon must be present in the data source.

Parameters:

• frequency (timedelta, optional) – Frequency of generated forecasts. Defaults to timedelta(hours=1).

• horizon (timedelta, optional) – Horizon to generate forecasts for. Defaults to timedelta(hours=24).

Methods

Attributes

input_range	Returns the min and max timedelta of observations which are required for the prediction.
is_uncertain

__call__(data: ndarray) → ndarray

Returns the forecast based on this data.

Parameters:

data (np.ndarray) – Data to use for the forecast.

Returns:

np.ndarray – Forecast of shape (n_horizon, n_vars)

property input_range: tuple[timedelta]

Returns the min and max timedelta of observations which are required for the prediction. To indicate a timestamp before the current time, the timedelta must be negative. The default is (-self.look_back, 0).

Returns:

tuple[timedelta] – (td before, td after)