skdh.features.Autocorrelation#

class skdh.features.Autocorrelation(lag=1, normalize=True)#

The similarity in profile between the signal and a time shifted version of the signal.

Parameters:
lagint, optional

Amount of lag (in samples) to use for the autocorrelation. Default is 1 sample.

normalizebool, optional

Normalize the result using the mean/std. deviation. Default is True

Attributes:
lag
normalize

Methods

compute(signal, *[, axis])

Compute the autocorrelation

compute(signal, *, axis=-1)#

Compute the autocorrelation

Parameters:
signalarray-like

Array-like containing values to compute the autocorrelation for.

axisint, optional

Axis along which the signal entropy will be computed. Ignored if signal is a pandas.DataFrame. Default is last (-1).

Returns:
acnumpy.ndarray

Signal autocorrelation.