85e89ae2495998ae69ab34abf5400164f909a548,librosa/core.py,,cqt,#,435

Before Change

        r_power  = np.abs(scipy.signal.fftconvolve(y, filt, mode="same"))**2
        cqt_power.append(feature.sync(r_power, samples, aggregate=aggregate))
    
    return np.asarray(cqt_power).squeeze()

def logamplitude(S, ref_power=1.0, amin=1e-10, top_db=80.0):
    Log-scale the amplitude of a spectrogram.

After Change

    else:
        samples    = np.asarray([samples]).flatten()

    cqt_power = np.empty((len(basis), len(y)), dtype=np.float32)
    
    for i, filt in enumerate(basis):
        cqt_power[i]  = np.abs(scipy.signal.fftconvolve(y, filt, mode="same"))**2

Instances