maad.features.spectral_bandwidth

maad.features.spectral_bandwidth(s, fs, nperseg=1024, roi=None, as_pandas=False, **kwargs)[source]

Compute the bandwith of the power spectrum. If a region of interest with time and spectral limits is provided, the spectral bandwidth is computed on the selection.

Parameters:

s1D array: Input audio signal
fsfloat: Sampling frequency of audio signal
npersegint, optional: Length of segment to compute the FFT. The default is 1024.
roipandas.Series, optional: Region of interest where peak frequency will be computed. Series must have a valid input format with index: min_t, min_f, max_t, max_f. The default is None.
as_pandasbool: Return data as a pandas.Series. This is usefull when computing multiple features over a signal. Default is False.
kwargsadditional keyword arguments: If window=’hann’, additional keyword arguments to pass to sound.spectrum.

Returns:

bandwidth_50float: Bandwidth 50% of the audio
bandwidth_90float: Bandwidth 90% of the audio

Examples

>>> from maad import features, sound
>>> s, fs = sound.load('../data/spinetail.wav')
>>> bw_50, bw_90 = features.spectral_bandwidth(s, fs, nperseg=1024)
>>> print("Bandwidth 50% : {:.4f} / Bandwidth 90% : {:.4f}".format(bw_50, bw_90))
Bandwidth 50% : 473.7305 / Bandwidth 90% : 3186.9141