commonpower.data_forecasting.data_sources.ConstantDataSource

class ConstantDataSource(values_dict: dict, date_range: List[datetime], frequency: timedelta = datetime.timedelta(seconds=3600))

Bases: DataSource

Dummy DataSource which returns constant values.

Parameters:

• values_dict (dict) – Dict containing element names and the respective constant value that should be returned.

• date_range (List[datetime]) – Date range to simulate.

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

Methods

get_date_range	Returns the date range data is available for.
get_limits	Returns the limits for each variable in the data source.
get_variables	Returns the list of element names that data is available for.

__call__(from_time: datetime, to_time: datetime) → ndarray

Return the data in this date range.

Parameters:

• from_time (datetime) – Start time of observation.

• to_time (datetime) – End time of observation.

Returns:

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

get_date_range() → List[datetime]

Returns the date range data is available for.

Returns:

List[datetime] – [start_date, end_date]

get_limits() → dict[str, tuple[float, float]]

Returns the limits for each variable in the data source.

Returns:

dict[str, tuple[float, float]] –

{“element1”: (lower_bound, upper_bound),

”element2”: (lower_bound, upper_bound)}

get_variables() → List[str]

Returns the list of element names that data is available for.

Returns:

List[str] – List of available elements.