solarforecastarbiter.datamodel.ForecastAggregate

class solarforecastarbiter.datamodel.ForecastAggregate(forecast: solarforecastarbiter.datamodel.Forecast, aggregate: solarforecastarbiter.datamodel.Aggregate, reference_forecast: Optional[solarforecastarbiter.datamodel.Forecast] = None, normalization: Optional[float] = None, uncertainty: Optional[float] = None, cost: Optional[str] = None)[source]

Class for pairing Forecast and Aggregate objects for evaluation.

Parameters:
__init__(forecast: solarforecastarbiter.datamodel.Forecast, aggregate: solarforecastarbiter.datamodel.Aggregate, reference_forecast: Optional[solarforecastarbiter.datamodel.Forecast] = None, normalization: Optional[float] = None, uncertainty: Optional[float] = None, cost: Optional[str] = None) → None

Methods

__init__(forecast, aggregate, …)
from_dict(input_dict[, raise_on_extra]) Construct a dataclass from the given dict, matching keys with the class fields.
replace(**kwargs) Convience wrapper for dataclasses.replace() to create a new dataclasses from the old with the given keys replaced.
to_dict() Convert the dataclass into a dictionary suitable for uploading to the API.

Attributes

cost
normalization
reference_forecast
uncertainty