xskillscore.mae

xskillscore.mae(a, b, dim=None, weights=None, skipna=False, keep_attrs=False)

Mean Absolute Error.

\[\mathrm{MAE} = \frac{1}{n}\sum_{i=1}^{n}\vert a - b\vert\]
Parameters

  • a (xarray.Dataset or xarray.DataArray) – Labeled array(s) over which to apply the function.

  • b (xarray.Dataset or xarray.DataArray) – Labeled array(s) over which to apply the function.

  • dim (str, list) – The dimension(s) to apply the mae along. Note that this dimension will be reduced as a result. Defaults to None reducing all dimensions.

  • weights (xarray.Dataset or xarray.DataArray or None) – Weights matching dimensions of dim to apply during the function.

  • skipna (bool) – If True, skip NaNs when computing function.

  • keep_attrs (bool) – If True, the attributes (attrs) will be copied from the first input to the new one. If False (default), the new object will be returned without attributes.

Returns

Mean Absolute Error.

Return type

xarray.Dataset or xarray.DataArray

See also

sklearn.metrics.mean_absolute_error()

References

https://en.wikipedia.org/wiki/Mean_absolute_error

Examples

>>> import numpy as np
>>> import xarray as xr
>>> from xskillscore import mae
>>> a = xr.DataArray(np.random.rand(5, 3, 3),
                    dims=['time', 'x', 'y'])
>>> b = xr.DataArray(np.random.rand(5, 3, 3),
                    dims=['time', 'x', 'y'])
>>> mae(a, b, dim='time')