OrdinalCMIEstimator

class infomeasure.estimators.mutual_information.OrdinalCMIEstimator(*data, cond=None, embedding_dim: int = None, step_size: int = 1, stable: bool = False, offset: int = 0, base: int | float | str = 'e', **kwargs)

Bases: BaseOrdinalMIEstimator, ConditionalMutualInformationEstimator

Estimator for the Ordinal conditional mutual information.

Attributes:

*dataarray_like, shape (n_samples,)

The data used to estimate the conditional mutual information. You can pass an arbitrary number of data arrays as positional arguments.

condarray_like

The conditional data used to estimate the conditional mutual information.

embedding_dimint

The size of the permutation patterns.

*symbolsarray_like, shape (n_samples,)

The symbolized data used to estimate the mutual information.

symbols_condarray_like, shape (n_samples,)

The symbolized conditional data used to estimate the conditional mutual information.

Raises:

ValueError

If the embedding_dim is negative or not an integer.

ValueError

If offset and embedding_dim are such that the data is too small.

Notes

• The order will be determined via numpy.argsort(). There is no normalize option, as this would not influence the order of the data.

• If embedding_dim is set to 1, the mutual information is always 0.