comparison.VerticalAccessor
comparison.VerticalAccessor(comparer)Methods
| Name | Description |
|---|---|
| max | Aggregate the comparison vertically using a specified aggregation function. |
| mean | Aggregate the comparison vertically using a specified aggregation function. |
| min | Aggregate the comparison vertically using a specified aggregation function. |
| skill | Compute skill metrics as a function of depth using depth bins. |
max
comparison.VerticalAccessor.max()Aggregate the comparison vertically using a specified aggregation function.
mean
comparison.VerticalAccessor.mean()Aggregate the comparison vertically using a specified aggregation function.
min
comparison.VerticalAccessor.min()Aggregate the comparison vertically using a specified aggregation function.
skill
comparison.VerticalAccessor.skill(bins=5, metrics=None, n_min=None)Compute skill metrics as a function of depth using depth bins.
This method computes metrics directly on binned long-format data (similar to Comparer.gridded_skill) and returns an xarray-backed SkillProfile.
Parameters
| Name | Type | Description | Default |
|---|---|---|---|
| bins | int or sequence | Depth bins, passed directly to xarray.Dataset.groupby_bins. See xarray.Dataset.groupby_bins(bins=...) for full details. - If int: number of equal-width bins. - If sequence: explicit bin edges. |
5 |
| metrics | (list, str, callable) | Metrics to compute. | None |
| n_min | int | Minimum number of observations in a depth bin; bins with fewer observations get metric values of np.nan. |
None |
Returns
| Name | Type | Description |
|---|---|---|
| SkillProfile | Depth-binned skill metrics. |