5fcaac3beb4fd536604b7d99b02165a8919978d6,librosa/feature/spectral.py,,logfsgram,#Any#Any#Any#Any#Any#,554

Before Change

    """

    // If we don"t have a spectrogram, build one
    if S is None:
        // By default, use a power spectrogram
        S = np.abs(stft(y, n_fft=n_fft, hop_length=hop_length))**2

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

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

After Change

        `P[f, t]` contains the energy at pitch bin `f`, frame `t`.
    """

    S, n_fft = __get_spec(y=y, sr=sr, S=S, n_fft=n_fft, hop_length=hop_length,
                          power=2)

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

Instances