How to use the blimpy.utils.rebin function in blimpy

#prepare font
    matplotlib.rc('font', **font)

    #Load in the data from fil
    plot_f, plot_data = fil.grab_data(f_start=f_start, f_stop=f_stop)

    #Make sure waterfall plot is under 4k*4k
    dec_fac_x, dec_fac_y = 1, 1

    #rebinning data to plot correctly with fewer points
    if plot_data.shape[0] > MAX_IMSHOW_POINTS[0]:
        dec_fac_x = plot_data.shape[0] / MAX_IMSHOW_POINTS[0]
    if plot_data.shape[1] > MAX_IMSHOW_POINTS[1]:
        dec_fac_y =  int(np.ceil(plot_data.shape[1] /  MAX_IMSHOW_POINTS[1]))
    plot_data = rebin(plot_data, dec_fac_x, dec_fac_y)

    #fix case where frequencies are reversed by fil.grab_data() # Shane Smith PR #82
    if plot_f[-1] < plot_f[0]:
        plot_f = plot_f[::-1]

    #determine extent of the plotting panel for imshow
    extent=(plot_f[0], plot_f[-1], (fil.timestamps[-1]-fil.timestamps[0])*24.*60.*60, 0.0)

    #plot and scale intensity (log vs. linear)
    kwargs['cmap'] = kwargs.get('cmap', 'viridis')
    kwargs['logged'] = True
    if kwargs['logged'] == True:
        plot_data = 10*np.log10(plot_data)
        kwargs.pop('logged')

    #get normalization parameters

#set up the sub-plots
    n_plots = len(fil_file_list)
    fig = plt.subplots(n_plots, sharex=True, sharey=True,figsize=(10, 2*n_plots))

    #read in data for the first panel
    fil1 = bl.Waterfall(fil_file_list[0], f_start=f_start, f_stop=f_stop)
    t0 = fil1.header['tstart']
    dummy, plot_data1 = fil1.grab_data()

    #rebin data to plot correctly with fewer points
    dec_fac_x, dec_fac_y = 1, 1
    if plot_data1.shape[0] > MAX_IMSHOW_POINTS[0]:
        dec_fac_x = plot_data1.shape[0] / MAX_IMSHOW_POINTS[0]
    if plot_data1.shape[1] > MAX_IMSHOW_POINTS[1]:
        dec_fac_y =  int(np.ceil(plot_data1.shape[1] /  MAX_IMSHOW_POINTS[1]))
    plot_data1 = rebin(plot_data1, dec_fac_x, dec_fac_y)

    #define more plot parameters
    ### never used: delta_f = 0.000250
    mid_f = np.abs(f_start+f_stop)/2.

    subplots = []

    #Fill in each subplot for the full plot
    for i,filename in enumerate(fil_file_list):
        #identify panel
        subplot = plt.subplot(n_plots,1,i+1)
        subplots.append(subplot)

        #read in data
        fil = bl.Waterfall(filename, f_start=f_start, f_stop=f_stop)
        #make plot with plot_waterfall