pyhctsa.operations.entropy.sample_entropy¶

pyhctsa.operations.entropy.sample_entropy(y, m=2, r=None, pre_process_how=None)¶

Compute Sample Entropy (SampEn) of a time series.

This function calculates SampEn for embedding dimensions from 0 to m. The implementation uses the PhysioNet C code (sampen.c by Doug Lake) [1] for efficiency and accuracy. Can specify to first apply an incremental differencing of the time series thus yielding the ‘Control Entropy’ [2].

References

Parameters:¶

y : array-like¶

Input time series.

m : int, optional¶

Maximum embedding dimension. Default is 2.

r : float, optional¶

Similarity threshold. If None, set to 0.1 * std(y). Default is None.

pre_process_how : str, optional¶

Preprocessing method:

• ’diff1’: Use first differences

• None: No pre-processing.

Default is None.

Returns:¶

Dictionary containing:

• ’sampen{m}’: Sample entropy for each m from 0 to M

• ’quadSampEn{m}’: Quadratic sample entropy for each m

• ’meanchsampen’: Mean change in sample entropy values

Return type:¶

dict