librosax.feature.hybrid_tempogram

hybrid_tempogram(*, y: ndarray | None = None, sr: float = 22050, onset_envelope: ndarray | None = None, hop_length: int = 512, win_length: int = 384, center: bool = True, window: str = 'hann', **kwargs: Any) → ndarray

Compute a hybrid tempogram.

The Fourier tempogram and the autocorrelation tempogram are resampled onto a common frequency grid and merged with a geometric mean.

This is a wrapper around librosa.feature.hybrid_tempogram.

Parameters

ynp.ndarray [shape=(…, n)] or None

Audio time series. Required if onset_envelope is not provided.

srfloat > 0

Sampling rate of the audio time series

onset_envelopenp.ndarray [shape=(…, n)] or None

Optional pre-computed onset strength envelope

hop_lengthint > 0

Number of audio samples between successive onset measurements

win_lengthint > 0

Length of the analysis window (in frames/onset measurements)

centerbool

If True, analysis windows are centered. If False, windows are left-aligned.

windowstr, tuple, number, callable, or list-like

A window specification as in get_window

**kwargs

Additional keyword arguments passed to scipy.interpolate.interp1d

Returns

hybridnp.ndarray [shape=(…, win_length // 2 + 1, n)]

The hybrid tempogram

See Also

tempogram fourier_tempogram librosa.feature.hybrid_tempogram