wrfhydropy.Evaluation.event

Evaluation.event(threshold: float | str, mod_col: str = 'modeled', obs_col: str = 'observed', group_by: list | str | None = None, decimals: int = 2)

TODO: HUH? this is the same description as gof but returns a contingency table? Calculate goodness of fit statistics using the spotpy package. See :py:fun:`calculate_all_functions() <calculate_all_functions>` in spotpy. :Parameters: * mod_col – Column name of modelled data

• obs_col – Column name of observed data

• group_by – Column names to group by prior to calculating statistics

• decimals – round stats to specified decimal places

• threshold – Threshold value for high flow event or

• column name containing threshold value.

dataframe :returns: Pandas dataframe containing contingency table