AnsbMIEstimator#
- class infomeasure.estimators.mutual_information.AnsbMIEstimator(*data, cond=None, undersampled: float = 0.1, offset: int = 0, base: int | float | str = 'e', **kwargs)[source]
Bases:
BaseAnsbMIEstimator,MutualInformationEstimatorEstimator for the Ansb mutual information.
Ansb mutual information estimator using the entropy combination formula.
- Attributes:
- *dataarray_like,
shape(n_samples,) The data used to estimate the mutual information. You can pass an arbitrary number of data arrays as positional arguments.
- undersampled
float, default=0.1 Maximum allowed ratio N/K to consider data sufficiently undersampled. A warning is issued if this threshold is exceeded.
- offset
int,optional Number of positions to shift the data arrays relative to each other. Delay/lag/shift between the variables. Default is no shift.
- *dataarray_like,
See also
infomeasure.estimators.entropy.ansb.AnsbEntropyEstimatorAnsb entropy estimator.
Notes
This estimator uses the Ansb entropy estimator to compute mutual information through the entropy combination formula.
Note that the entropy combination formula is used (_generic_mi_from_entropy) not a dedicated implementation as other MI might have.