import librosa
def get_spectrogram(waveform, fs, nfft=128, overlap_pct=0.8):
    """
    Get the spectrogram of a single channel
    Inputs:
    :param waveform: single channel temporal signal
    :param fs: the sampling frequency (Hz)
    :param nfft: number of time samples used for the STFT. Default 128
    :param overlap_pct: percentage of overlap in the spectrogram. Default 0.8
    Outputs:
    :return: a spectrogram and associated time & frequency vectors
    """

    spectrogram = np.abs(librosa.stft(
        y=waveform, n_fft=nfft,
        hop_length=int(np.floor(nfft * (1 - overlap_pct)))))

    # Axis
    height = spectrogram.shape[0]
    width = spectrogram.shape[1]

    tt = np.linspace(0, len(waveform)/fs, num=width)
    ff = np.linspace(0, fs / 2, num=height)

    p = 10 * np.log10(spectrogram * 10 ** 9)

    return p, tt, ff