pyxpcm.pcm.score

pcm.score(self, ds, features=None, dim=None)

Compute the per-sample average log-likelihood of the given data

Parameters:

ds: :class:`xarray.Dataset`

The dataset to work with

features: dict()

Definitions of PCM features in the input xarray.Dataset. If not specified or set to None, features are identified using xarray.DataArray attributes ‘feature_name’.

dim: str

Name of the vertical dimension in the input xarray.Dataset

Returns:

log_likelihood: float

In the case of a GMM classifier, this is the Log likelihood of the Gaussian mixture given data