pyxpcm.stat.robustness
- pyxpcm.stat.robustness(ds, name='PCM_POST', classdimname='pcm_class', outname='PCM_ROBUSTNESS')[source]
Compute classification robustness
- Parameters:
- name: str, default is ‘PCM_POST’
Name of the
xarray.DataArray
with prediction probability (posteriors)- classdimname: str, default is ‘pcm_class’
Name of the dimension holding classes
- outname: ‘PCM_ROBUSTNESS’ or str
Name of the
xarray.DataArray
with robustness- inplace: boolean, False by default
If False, return a
xarray.DataArray
with robustness If True, return the inputxarray.Dataset
with robustness added as a newxarray.DataArray
- Returns:
xarray.Dataset
if inplace=True- or
xarray.DataArray
if inplace=False