wrfhydropy.Evaluation

class wrfhydropy.Evaluation(observed: Union[pandas.core.frame.DataFrame, xarray.core.dataarray.DataArray], modeled: Union[pandas.core.frame.DataFrame, xarray.core.dataarray.DataArray], join_on: Union[list, str] = None, join_how: str = 'inner')[source]

A dataset consisting of a modeled and observed dataframe. This class provides methods for calculating staistics.

Methods

brier(self, threshold, mod_col, obs_col, …) Calculate Brier score using the properscoring package.
contingency(self, threshold, str], …) Calculate contingency statistics
crps(self, mod_col, obs_col, member_col, …) Calculate CRPS (continuous ranked probability score) using the properscoring package.
event(self, threshold, str], mod_col, …) TODO: HUH? this is the same description as gof but returns a contingency table? Calculate goodness of fit statistics using the spotpy package.
gof(self, mod_col, obs_col, group_by, …) Calculate goodness of fit statistics using the spotpy package.
__init__(self, observed:Union[pandas.core.frame.DataFrame, xarray.core.dataarray.DataArray], modeled:Union[pandas.core.frame.DataFrame, xarray.core.dataarray.DataArray], join_on:Union[list, str]=None, join_how:str='inner')[source]

Instantiate analysis class by joining modeled and observed datasets. :Parameters: * observed – Dataframe containing observed data

  • modeled – Dataframe containing modelled data
  • join_on – Optional, string or list of columns names to join datasets.
  • Default is [‘feature_id’,’time’]
  • join_how – Optional, how to perform teh dataframe join. Default is
  • ‘inner’. Options
  • are ‘inner’,’left’,’right’.

Methods

__init__(self, observed, …) Instantiate analysis class by joining modeled and observed datasets.
brier(self, threshold, mod_col, obs_col, …) Calculate Brier score using the properscoring package.
contingency(self, threshold, str], …) Calculate contingency statistics
crps(self, mod_col, obs_col, member_col, …) Calculate CRPS (continuous ranked probability score) using the properscoring package.
event(self, threshold, str], mod_col, …) TODO: HUH? this is the same description as gof but returns a contingency table? Calculate goodness of fit statistics using the spotpy package.
gof(self, mod_col, obs_col, group_by, …) Calculate goodness of fit statistics using the spotpy package.