How to use the autoarray.util.plotter_util.get_subplot_rows_columns_figsize function in autoarray

cb_pad=0.01,
    cb_tick_values=None,
    cb_tick_labels=None,
    titlesize=10,
    xlabelsize=10,
    ylabelsize=10,
    xyticksize=10,
    mask_pointsize=10,
    position_pointsize=10,
    grid_pointsize=1,
    output_path=None,
    output_filename="fit_real_space",
    output_format="show",
):

    rows, columns, figsize_tool = plotter_util.get_subplot_rows_columns_figsize(
        number_subplots=2
    )

    if figsize is None:
        figsize = figsize_tool

    unit_label, unit_conversion_factor = lens_plotter_util.get_unit_label_and_unit_conversion_factor(
        obj=fit.tracer.image_plane, plot_in_kpc=plot_in_kpc
    )

    image_plane_pix_grid = lens_plotter_util.get_image_plane_pix_grid_from_fit(
        include_image_plane_pix=include_image_plane_pix, fit=fit
    )

    real_space_mask = plotter_util.get_real_space_mask_from_fit(fit=fit, mask=mask)

Parameters
    -----------
    fit : autolens.lens.fitting.Fitter
        Class containing fit between the model datas_ and observed lens datas_ (including residual_map, chi_squared_map etc.)
    output_path : str
        The path where the datas_ is output if the output_type is a file format (e.g. png, fits)
    output_filename : str
        The name of the file that is output, if the output_type is a file format (e.g. png, fits)
    output_format : str
        How the datas_ is output. File formats (e.g. png, fits) output the datas_ to harddisk. 'show' displays the datas_ \
        in the python interpreter window.
    """

    output_filename += "_" + str(plane_index)

    rows, columns, figsize_tool = plotter_util.get_subplot_rows_columns_figsize(
        number_subplots=4
    )

    mask = plotter_util.get_mask_from_fit(fit=fit, mask=mask)

    if figsize is None:
        figsize = figsize_tool

    unit_label, unit_conversion_factor = lens_plotter_util.get_unit_label_and_unit_conversion_factor(
        obj=fit.tracer.planes[plane_index], plot_in_kpc=plot_in_kpc
    )

    plt.figure(figsize=figsize)

    image_plane_pix_grid = lens_plotter_util.get_image_plane_pix_grid_from_fit(
        include_image_plane_pix=include_image_plane_pix, fit=fit

cb_fraction=0.047,
    cb_pad=0.01,
    cb_tick_values=None,
    cb_tick_labels=None,
    titlesize=10,
    xlabelsize=10,
    ylabelsize=10,
    xyticksize=10,
    mask_pointsize=10,
    position_pointsize=10,
    output_path=None,
    output_format="show",
    output_filename="hyper_galaxies",
):

    rows, columns, figsize_tool = plotter_util.get_subplot_rows_columns_figsize(
        number_subplots=6
    )

    if figsize is None:
        figsize = figsize_tool

    plt.figure(figsize=figsize)

    plt.subplot(rows, columns, 1)

    hyper_galaxy_image(
        hyper_galaxy_image=hyper_galaxy_image_sub,
        mask=mask,
        as_subplot=True,
        unit_label=unit_label,
        kpc_per_arcsec=kpc_per_arcsec,

def image_and_source_plane_subplot(
    image_plane,
    source_plane,
    grid,
    points=None,
    include_critical_curves=False,
    include_caustics=False,
    axis_limits=None,
    plot_in_kpc=False,
    output_path=None,
    output_format="show",
    output_filename="image_and_source_plane_grids",
):

    rows, columns, figsize = plotter_util.get_subplot_rows_columns_figsize(
        number_subplots=2
    )

    lines = lens_plotter_util.get_critical_curves_and_caustics_from_lensing_object(
        obj=image_plane, include_critical_curves=True, include_caustics=True
    )

    if include_critical_curves:
        critical_curves = [lines[0]]
    else:
        critical_curves = None

    if include_caustics:
        caustics = [lines[1]]
    else:
        caustics = None

cb_fraction=0.047,
    cb_pad=0.01,
    cb_tick_values=None,
    cb_tick_labels=None,
    titlesize=10,
    xlabelsize=10,
    ylabelsize=10,
    xyticksize=10,
    mask_pointsize=10,
    position_pointsize=10,
    output_path=None,
    output_filename="hyper_galaxy_images",
    output_format="show",
):

    rows, columns, figsize_tool = plotter_util.get_subplot_rows_columns_figsize(
        number_subplots=len(hyper_galaxy_image_path_dict)
    )

    if not mask:
        mask = False

    if figsize is None:
        figsize = figsize_tool

    plt.figure(figsize=figsize)

    hyper_index = 0

    for path, hyper_galaxy_image_sub in hyper_galaxy_image_path_dict.items():

        hyper_index += 1