isclusters#

er_evaluation.data_structures.isclusters(obj)[source]#

Check if given object is a clusters dictionary.

Clusters dictionary:

A clusters dictionary is a Python dict with keys corresponding to cluster identifiers and values being list of cluster elements. Example:

{'c1': array([0, 1, 2]), 'c2': array([3, 4]), 'c3': array([5])}
Returns:

True if clusters dictionary, False otherwise.

Return type:

bool

Examples

>>> from numpy import array
>>> obj = {'c1': array([0, 1, 2]), 'c2': array([3, 4]), 'c3': array([5])}
>>> isclusters(obj)
True

Dictionary values should be numpy arrays:

>>> obj = {'c1': [0, 1, 2], 'c2': [3, 4], 'c3': [5]}
>>> isclusters(obj)
False

⚠️ Warning: Clustering validity is not checked.

>>> import pandas as pd
>>> obj = {'c1': array([pd.NA]), 'c2': array([pd.NA])}
>>> isclusters(obj)
True

Notes

  • This function does not verify that clusters are non-overlapping with unique non-NaN elements.