climpred.utils.convert_init_lead_to_valid_time_lead#
- climpred.utils.convert_init_lead_to_valid_time_lead(skill: Dataset | DataArray) Dataset | DataArray[source]#
Convert
data(init,lead)todata(valid_time,lead)visualizing predict barrier.- Parameters:
skill with dimensions init and lead and coordinate valid_time (
init, lead)- Returns:
skill with dimensions valid_time and lead
Examples
Calculate skill at each
init, i.e. do not reduceinitand setdim=[].>>> skill_init_lead = HindcastEnsemble.sel( ... lead=[1, 2, 3], init=slice("1990", "2000") ... ).verify(metric="rmse", comparison="e2o", dim=[], alignment="same_verifs") >>> skill_init_lead.SST <xarray.DataArray 'SST' (lead: 3, init: 11)> Size: 264B array([[ nan, nan, 0.0766808 , 0.06826988, 0.08174487, 0.06208846, 0.1537402 , 0.15632479, 0.01302786, 0.06343324, 0.13758603], [ nan, 0.07732193, 0.06369554, 0.08282175, 0.0761979 , 0.20424354, 0.18043845, 0.06553673, 0.00906034, 0.13045045, nan], [0.06212777, 0.11822992, 0.15282457, 0.05752934, 0.20133476, 0.19931679, 0.00987793, 0.06375334, 0.07705835, nan, nan]]) Coordinates: * init (init) object 88B 1990-01-01 00:00:00 ... 2000-01-01 00:00:00 * lead (lead) int32 12B 1 2 3 valid_time (lead, init) object 264B 1991-01-01 00:00:00 ... 2003-01-01 0... skill <U11 44B 'initialized' Attributes: units: C >>> climpred.utils.convert_init_lead_to_valid_time_lead(skill_init_lead).SST <xarray.DataArray 'SST' (lead: 3, valid_time: 9)> Size: 216B array([[0.0766808 , 0.06826988, 0.08174487, 0.06208846, 0.1537402 , 0.15632479, 0.01302786, 0.06343324, 0.13758603], [0.07732193, 0.06369554, 0.08282175, 0.0761979 , 0.20424354, 0.18043845, 0.06553673, 0.00906034, 0.13045045], [0.06212777, 0.11822992, 0.15282457, 0.05752934, 0.20133476, 0.19931679, 0.00987793, 0.06375334, 0.07705835]]) Coordinates: * valid_time (valid_time) object 72B 1993-01-01 00:00:00 ... 2001-01-01 00... * lead (lead) int32 12B 1 2 3 skill <U11 44B 'initialized' init (lead, valid_time) object 216B 1992-01-01 00:00:00 ... 1998-0... Attributes: units: C