pyhctsa.operations.entropy.multi_scale_entropy¶

pyhctsa.operations.entropy.multi_scale_entropy(y, scale_range=None, m=2, r=0.15, pre_process_how=None)¶

Compute multiscale entropy (MSE) of a time series using sample entropy across multiple scales.

Parameters:¶

y : array-like¶

Input time series (list or NumPy array).

scale_range : list or range, optional¶

List or range of scales (window sizes) to use for coarse-graining. Default is range(1, 11).

m : int, optional¶

Embedding dimension for sample entropy (default: 2).

r : float, optional¶

Similarity threshold for sample entropy (default: 0.15).

pre_process_how : str, optional¶

Preprocessing method. Supported:

• ’diff1’: Use z-scored first differences.

• ’rescale_tau’: Rescale using autocorrelation time.

Returns:¶

Dictionary containing sample entropy at each scale and summary statistics.

Return type:¶

dict