b7c2f6e9ccd65a53d8ae9aa0d3ee287ce9c93019,librosa/feature.py,,logfsgram,#Any#Any#Any#Any#Any#,10

Before Change

        // If the user didn"t specify tuning, do it ourselves
        if "tuning" not in kwargs:
            pitches, magnitudes, S = ifptrack(y, sr, n_fft=n_fft, hop_length=hop_length)
            pitches = pitches[magnitudes > np.median(magnitudes)]
            del magnitudes

            bins_per_octave = kwargs.get("bins_per_octave", 12)
            kwargs["tuning"] = estimate_tuning(pitches, bins_per_octave=bins_per_octave)

After Change

        n_fft       = (S.shape[0] -1 ) * 2

    // If we don"t have tuning already, grab it from S
    if "tuning" not in kwargs:
        kwargs["tuning"] = estimate_tuning(S=S,
                                           sr=sr, 
                                           bins_per_octave=kwargs.get("bins_per_octave", 12))

    // Build the CQ basis
    cq_basis = librosa.filters.logfrequency(sr, n_fft=n_fft, **kwargs)
    
    return cq_basis.dot(S)

Instances