IncrementalEntropy

class eyefeatures.features.measures.IncrementalEntropy(x=None, y=None, aoi=None, pk=None, return_df=True, ignore_errors=False)[source]

Bases: MeasureTransformer

Incremental Entropy.

Measures the average entropy of the fixation distribution as it evolves over time. It calculates the Shannon entropy of the coordinate distribution at each step $i$ (using fixations $1$ to $i$) and then averages these values. This captures how the spatial distribution complexity changes as more of the visual stimulus is explored.

Parameters:

  • x (str) – X coordinate column name.

  • y (str) – Y coordinate column name.

  • aoi (str) – Area Of Interest column name(-s).

  • pk (list[str]) – primary key.

  • return_df (bool) – whether to return output as DataFrame or numpy array.

  • ignore_errors (bool) – If True, return NaN when feature computation fails; otherwise raise.