def METHOD_NAME(dir_path, config):
    """ Plots a graph of all intensity sums from FS*.bin files in the given directory. 
    Arguments:
        dir_path: [str] Path to the directory which containes the FS*.bin files.
        config: [Config structure] Configuration.
    Return:
        None
    """
    time_data = []
    intensity_data_peak = []
    intensity_data_avg = []
    # Get all fieldsum files in the directory
    for file_name in sorted(os.listdir(dir_path)):
        # Check if it is the fieldsum file
        if ('FS' in file_name) and ('_fieldsum.bin' in file_name):
            # Try reading the intensities sum, because the file might be corrupted
            try:
                # Read the field sums
                _, intensity_array = readFieldIntensitiesBin(dir_path, file_name)
            except TypeError:
                print('File {:s} is corrupted!'.format(file_name))
            # Extract the date and time from the FF file
            dt = filenameToDatetime(file_name)
            # Take the peak intensity value
            intensity_data_peak.append(np.max(intensity_array))
            # Take the average intensity value
            intensity_data_avg.append(np.mean(intensity_array))
            time_data.append(dt)
    # If there are no fieldsums, do nothing
    if not time_data:
        return False
    # Plot the raw intensity over time ###
    ##########################################################################################################
    plt.figure()
    # Plot peak intensitites
    plt.plot(time_data, intensity_data_peak, color='r', linewidth=0.5, zorder=3, label='Peak')
    # Plot average intensitites
    plt.plot(time_data, intensity_data_avg, color='k', linewidth=0.5, zorder=3, label='Average')
    plt.gca().set_yscale('log')
    plt.xlim(np.min(time_data), np.max(time_data))
    plt.ylim(np.min(intensity_data_avg), np.max(intensity_data_peak))
    plt.xlabel('Time')
    plt.ylabel('ADU')
    # Rotate x ticks so they do not overlap
    plt.xticks(rotation=30)
    plt.grid(color='0.9', which='both')
    plt.title('Peak field sums for ' + os.path.basename(dir_path))
    plt.tight_layout()
    plt.legend()
    # Only add the station ID if the dir name already doesn't start with it
    dir_name = os.path.basename(os.path.abspath(dir_path))
    if dir_name.startswith(config.stationID):
        prefix = dir_name
    else:
        prefix = "{:s}_{:s}".format(config.stationID, dir_name)
    img_name = "{:s}_fieldsums.png".format(prefix)
    plt.savefig(os.path.join(dir_path, img_name), dpi=300)
    plt.clf()
    plt.close()
    ##########################################################################################################
    ### Plot intensities without the average value
    ##########################################################################################################
    intensity_data_peak = np.array(intensity_data_peak)
    intensity_data_avg = np.array(intensity_data_avg)
    # Calculate the difference between the peak values and the average values per every FF file
    intensity_data_noavg = intensity_data_peak - intensity_data_avg
    plt.figure()
    plt.plot(time_data, intensity_data_noavg, color='k', linewidth=0.5, zorder=3)
    plt.gca().set_yscale('log')
    plt.xlim(np.min(time_data), np.max(time_data))
    plt.xlabel('Time')
    plt.ylabel('Peak ADU - average')
    # Rotate x ticks so they do not overlap
    plt.xticks(rotation=30)
    plt.grid(color='0.9', which='both')
    plt.title('Deaveraged field sums for ' + os.path.basename(dir_path))
    plt.tight_layout()
    img_name = "{:s}_fieldsums_noavg.png".format(prefix)
    plt.savefig(os.path.join(dir_path, img_name), dpi=300)
    plt.clf()
    plt.close()
    ##########################################################################################################