librosa.core.hybrid_cqt¶

librosa.core.hybrid_cqt(y, sr=22050, hop_length=512, fmin=None, n_bins=84, bins_per_octave=12, tuning=0.0, filter_scale=1, norm=1, sparsity=0.01, window=’hann’, scale=True, pad_mode=’reflect’)[source]¶

Compute the hybrid constant-Q transform of an audio signal.

Here, the hybrid CQT uses the pseudo CQT for higher frequencies where the hop_length is longer than half the filter length and the full CQT for lower frequencies.

Parameters:	y : np.ndarray [shape=(n,)] audio time series sr : number > 0 [scalar] sampling rate of y hop_length : int > 0 [scalar] number of samples between successive CQT columns. fmin : float > 0 [scalar] Minimum frequency. Defaults to C1 ~= 32.70 Hz n_bins : int > 0 [scalar] Number of frequency bins, starting at fmin bins_per_octave : int > 0 [scalar] Number of bins per octave tuning : None or float in [-0.5, 0.5) Tuning offset in fractions of a bin (cents). If None, tuning will be automatically estimated from the signal. filter_scale : float > 0 Filter filter_scale factor. Larger values use longer windows. sparsity : float in [0, 1) Sparsify the CQT basis by discarding up to sparsity fraction of the energy in each basis. Set sparsity=0 to disable sparsification. window : str, tuple, number, or function Window specification for the basis filters. See filters.get_window for details. pad_mode : string Padding mode for centered frame analysis. See also: `librosa.core.stft` and np.pad.
Returns:	CQT : np.ndarray [shape=(n_bins, t), dtype=np.float] Constant-Q energy for each frequency at each time.
Raises:	ParameterError If hop_length is not an integer multiple of 2(n_bins / bins_per_octave) Or if y is too short to support the frequency range of the CQT.