def METHOD_NAME():
    if(len(sys.argv) != 3):
        print('Usage: 2d_plots.py [run number 1] [run number 2]')
        sys.exit()
    with open("runDB.json") as f:
        runDB = json.load(f)
    tier_dir = os.path.expandvars(runDB["tier_dir"])
    meta_dir = os.path.expandvars(runDB["meta_dir"])
    df = pd.read_hdf('{}/t2_run{}.h5'.format(tier_dir,sys.argv[1]))
    df['e_cal'] = pd.read_hdf('{}/Spectrum_{}_2.hdf5'.format(meta_dir,sys.argv[1]))['e_cal']
    df['rise'] = df['tp100'] - df['t0']
    df_2 = pd.read_hdf('{}/t2_run{}.h5'.format(tier_dir,sys.argv[2]))
    df_2['e_cal'] = pd.read_hdf('{}/Spectrum_{}_2.hdf5'.format(meta_dir,sys.argv[2]))['e_cal']
    df_2['rise'] = df_2['tp100'] - df_2['t0']
    xlo, xhi, xpb = 0, 50, 2
    ylo, yhi, ypb = 0, 1400, 10
    nxbins = int((xhi-xlo)/xpb)
    nybins = int((yhi-ylo)/ypb)
    hist1, xbins, ybins = np.histogram2d(df['e_cal'], df['rise'], [nxbins,nybins], [[xlo,xhi], [ylo,yhi]])
    hist2, xbins, ybins = np.histogram2d(df_2['e_cal'], df_2['rise'], [nxbins,nybins], [[xlo,xhi], [ylo,yhi]])
    #hist_diff = hist2 - hist1
    hist2 = hist2.T
    xbins = xbins[0:(len(xbins)-1)]
    ybins = ybins[0:(len(ybins)-1)]
    plt.hist2d(hist2[0],hist2[1], [xbins, ybins])
    plt.xlim(xlo, xhi)
    plt.ylim(ylo, yhi)
    plt.xlabel('Energy (keV)', ha='right', x=1.0)
    plt.ylabel('tp100 - t0', ha='right', y=1.0)
    cbar = plt.colorbar()
    cbar.ax.set_ylabel('Counts')
    plt.tight_layout()
    plt.show()