# solarforecastarbiter.metrics.deterministic.cost¶

solarforecastarbiter.metrics.deterministic.cost(obs, fx, cost_params, error_fnc=<function error>)[source]

Compute the cost for forecast errors according to cost_params. cost_params.type determines which cost function of constant_cost(), time_of_day_cost(), datetime_cost(), or error_band_cost() will be used.

In general, the cost is calculated as

$\text{cost} = \sum_{i=1}^n C_i(S(\text{obs}_i, \text{fx}_i))$

where $$C_i$$ is determined by the cost function and $$S$$ is the error function.

Parameters: obs ((n,) pandas.Series) – Observed values fx ((n,) pandas.Series) – Forecasted values cost_params (solarforecastarbiter.datamodel.Cost) – Parameters that the define the cost value along with how to aggregate the costs. error_fnc (function) – A function that returns the error, default fx - obs. First argument is obs, second argument is fx. cost (float) – The cost of the forecast errors.