wrfhydropy.Evaluation.event

Evaluation.event(self, threshold:Union[float, str], mod_col:str='modeled', obs_col:str='observed', group_by:Union[list, str]=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