5fcaac3beb4fd536604b7d99b02165a8919978d6,librosa/feature/spectral.py,,chromagram,#,634

Before Change

    n_chroma = kwargs.get("n_chroma", 12)

    // Build the power spectrogram if unspecified
    if S is None:
        S = np.abs(stft(y, n_fft=n_fft, hop_length=hop_length))**2
    else:
        n_fft = (S.shape[0] - 1) * 2

    if tuning is None:
        tuning = estimate_tuning(S=S, sr=sr, bins_per_octave=n_chroma)

    // Get the filter bank

After Change

        Vector normalization
    

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

    n_chroma = kwargs.get("n_chroma", 12)

    if tuning is None:

Instances