pyhctsa.operations.nonlinearity.nsamdf¶

pyhctsa.operations.nonlinearity.nsamdf(x, fs=1.0, win_len_rel=14, shift_len_rel=0.5, lag_rel=1, degree=7)¶

Computes the nonlinearity measure L through nsAMDF (nonlinear average magnitude difference function), developed by Ozkurt et al. [1].

This function was authored by Tolga Esat Ozkurt, 2020. (tolgaozkurt@gmail.com). Edits by Ben Fulcher for incorporating into hctsa and Joshua Moore for incorporating into pyhctsa.

References

Parameters:¶

x : array-like¶

Input time series.

fs : float or int¶

Sampling frequency in Hz. Default is 1.0.

win_len_rel : float or int¶

Window length (a long enough segment is important to estimate the nonlinearity). Default is 14.

shift_len_rel : float or int¶

This amounts to window length - overlap length btw windows. Default is 0.5.

lag_rel : float or int¶

TMaximum lag for nsAMDF, we chose it as 1. Default is 1.

degree : The chosen degree p should ideally be large enough to capture the¶

highest order of nonlinearity within the data. Default is 7.

Returns:¶

The nsAMDF nonlinearity measure L.

Return type:¶

float