weatherbench2.evaluation.evaluate_in_memory
- weatherbench2.evaluation.evaluate_in_memory(data_config, eval_configs, skipna=False)
Run evaluation in memory.
Will save a separate results NetCDF file for each config.Eval. An example for a results dataset with the respective dimensions is given below. Note that region and level are optional.
``` <xarray.Dataset> Dimensions: (lead_time: 21, region: 3, level: 3, metric: 2) Coordinates:
lead_time (lead_time) timedelta64[ns] 0 days 00:00:00 …
region (region) object ‘global’ ‘tropics’ ‘extra-tropics’
level (level) int32 500 700 850
metric (metric) object ‘rmse’ ‘acc’
- Data variables:
geopotential (metric, region, lead_time, level) float64 … 2m_temperature (metric, region, lead_time) float64 0.6337 …
- Parameters:
data_config (Data) – config.Data instance.
eval_configs (dict[str, weatherbench2.config.Eval]) – Dictionary of config.Eval instances.
skipna (bool) – Whether to skip NaN values in both forecasts and observations during evaluation.
- Return type:
None