entropy

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entropy#

infomeasure.entropy(data, approach: str, *args, **kwargs: any)[source]#

Calculate the entropy using a functional interface of different estimators.

Supports the following approaches:

  1. discrete: Discrete entropy estimator.

  2. kernel: Kernel entropy estimator.

  3. [metric, kl]: Kozachenko-Leonenko entropy estimator.

  4. renyi: Renyi entropy estimator.

  5. [ordinal, symbolic, permutation]: Ordinal / Permutation entropy estimator.

  6. tsallis: Tsallis entropy estimator.

Parameters:
dataarray_like

The data used to estimate the entropy.

approachstr

The name of the estimator to use.

*args: tuple

Additional arguments to pass to the estimator.

**kwargs: dict

Additional keyword arguments to pass to the estimator.

Returns:
float

The calculated entropy.

Raises:
ValueError

If the estimator is not recognized.

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