bulum.clim.clim module
- apply_transformation_curves(tranformation_curves: dict, series: Series) Series
Applies seasonal transformation curves to an input series. Refer to the function derive_transformation_curves.
- Parameters:
tranformation_curves (dict)
series (pd.Series)
- Return type:
pd.Series
- apply_transformation_factors(transformation_factors: dict, series: Series) Series
Applies seasonal transformation factors to an input series. Refer to the function derive_transformation_curves.
- Parameters:
transformation_curves (dict)
series (pd.Series)
- derive_transformation_curves(original_ts: Series, augmented_ts: Series, season_start_months=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], epsilon=0.001) dict
Returns a dictionary of exceedence-based transformation curves - one for each season with the season’s start month as the key. These are tables that map from exceedance (cunnane plotting position as a fraction) to a scaling factor. These are intended to be used to effectively summarise climate-change adjustments, and allow them to be transported from one timeseries to another.
- Parameters:
original_ts (pd.Series)
augmented_ts (pd.Series)
season_start_months (list, optional) – Defaults to [1,2,3,4,5,6,7,8,9,10,11,12].
- derive_transformation_factors(original_ts: Series, augmented_ts: Series, season_start_months=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], epsilon=0.001) dict
Returns a dictionary of transformation factors - one for each season with the season’s start month as the key. These scaling factors are intended to be used to effectively summarise climate-change adjustments, and allow them to be transported from one timeseries to another.