#! /usr/bin/env python import sys, os.pathfrom aubio import pvoc, source, float_typefrom numpy import zeros, log10, vstackimport matplotlib.pyplot as plt def get_spectrogram(filename, samplerate = 0):    win_s = 512                                        # fft window size    hop_s = win_s // 2                                 # hop size    fft_s = win_s // 2 + 1                             # spectrum bins     a = source(filename, samplerate, hop_s)            # source file    if samplerate == 0: samplerate = a.samplerate    pv = pvoc(win_s, hop_s)                            # phase vocoder    specgram = zeros([0, fft_s], dtype=float_type)     # numpy array to store spectrogram     # analysis    while True:        samples, read = a()                              # read file        specgram = vstack((specgram,pv(samples).norm))   # store new norm vector        if read < a.hop_size: break     # plotting    fig = plt.imshow(log10(specgram.T + .001), origin = 'bottom', aspect = 'auto', cmap=plt.cm.gray_r)    ax = fig.axes    ax.axis([0, len(specgram), 0, len(specgram[0])])    # show axes in Hz and seconds    time_step = hop_s / float(samplerate)    total_time = len(specgram) * time_step    outstr = "total time: %0.2fs" % total_time    print(outstr + ", samplerate: %.2fkHz" % (samplerate / 1000.))    n_xticks = 10    n_yticks = 10     def get_rounded_ticks( top_pos, step, n_ticks ):        top_label = top_pos * step        # get the first label        ticks_first_label = top_pos * step / n_ticks        # round to the closest .1        ticks_first_label = round ( ticks_first_label * 10. ) / 10.        # compute all labels from the first rounded one        ticks_labels = [ ticks_first_label * n for n in range(n_ticks) ] + [ top_label ]        # get the corresponding positions        ticks_positions = [ ticks_labels[n] / step for n in range(n_ticks) ] + [ top_pos ]        # convert to string        ticks_labels = [  "%.1f" % x for x in ticks_labels ]        # return position, label tuple to use with x/yticks        return ticks_positions, ticks_labels      # apply to the axis    x_ticks, x_labels = get_rounded_ticks ( len(specgram), time_step, n_xticks )    y_ticks, y_labels = get_rounded_ticks ( len(specgram[0]), (samplerate / 1000. / 2.) / len(specgram[0]), n_yticks )    ax.set_xticks( x_ticks )    ax.set_yticks ( y_ticks )    ax.set_xticklabels( x_labels )    ax.set_yticklabels ( y_labels )    ax.set_ylabel('Frequency (kHz)')    ax.set_xlabel('Time (s)')    ax.set_title(os.path.basename(filename))    for item in ([ax.title, ax.xaxis.label, ax.yaxis.label] +            ax.get_xticklabels() + ax.get_yticklabels()):        item.set_fontsize('x-small')    return fig if __name__ == '__main__':    if len(sys.argv) < 2:        print("Usage: %s <filename>" % sys.argv[0])    else:        for soundfile in sys.argv[1:]:            fig = get_spectrogram(soundfile)            # display graph            plt.show()            #outimage = os.path.basename(soundfile) + '.png'            #print ("writing: " + outimage)            #plt.savefig(outimage)            plt.close()