b4cdf54ccb68bec84ed374f98fc7f52fb06359e5,librosa/core/harmonic.py,,salience,#,13

Before Change

        peak_mask = np.ones(S_harm.shape)
        peak_mask[:, S_peaks[0], S_peaks[1]] = 0
    else:
        peak_mask = np.zeros(S_harm.shape)

    S_mask = np.ma.masked_array(S_harm, mask=peak_mask)

    if aggregate is np.ma.average:

After Change

    if filter_peaks:
        S_peaks = scipy.signal.argrelmax(S, axis=0)
        S_out = np.empty(S.shape)
        S_out.fill(fill_value)
        S_out[S_peaks[0], S_peaks[1]] = S_sal[S_peaks[0], S_peaks[1]]

        S_sal = S_out

Instances