How to use the visualqc.config.default_num_slices function in VisualQC

outliers.add_argument("-olt", "--outlier_feat_types", action="store",
                          dest="outlier_feat_types",
                          default=cfg.t1_mri_features_OLD, required=False,
                          help=help_text_outlier_feat_types)

    outliers.add_argument("-old", "--disable_outlier_detection", action="store_true",
                          dest="disable_outlier_detection",
                          required=False, help=help_text_disable_outlier_detection)

    layout = parser.add_argument_group('Layout options', ' ')
    layout.add_argument("-w", "--views", action="store", dest="views",
                        default=cfg.default_views, required=False, nargs='+',
                        help=help_text_views)

    layout.add_argument("-s", "--num_slices", action="store", dest="num_slices",
                        default=cfg.default_num_slices, required=False,
                        help=help_text_num_slices)

    layout.add_argument("-r", "--num_rows", action="store", dest="num_rows",
                        default=cfg.default_num_rows, required=False,
                        help=help_text_num_rows)

    wf_args = parser.add_argument_group('Workflow', 'Options related to workflow '
                                                    'e.g. to pre-compute resource-intensive features, '
                                                    'and pre-generate all the visualizations required')
    wf_args.add_argument("-p", "--prepare_first", action="store_true",
                         dest="prepare_first",
                         help=help_text_prepare)

    return parser

This must be a set of two values (between 0 and 1.0) separated by a space e.g. --alphas 0.7 0.5. 

    Default: {} {}.  Play with these values to find something that works for you and the dataset.
    \n""".format(cfg.default_alpha_mri, cfg.default_alpha_seg))

    help_text_views = textwrap.dedent("""
    Specifies the set of views to display - could be just 1 view, or 2 or all 3.
    Example: --views 0 (typically sagittal) or --views 1 2 (axial and coronal)
    Default: {} {} {} (show all the views in the selected segmentation)
    \n""".format(cfg.default_views[0], cfg.default_views[1], cfg.default_views[2]))

    help_text_num_slices = textwrap.dedent("""
    Specifies the number of slices to display per each view. 
    This must be even to facilitate better division.
    Default: {}.
    \n""".format(cfg.default_num_slices))

    help_text_num_rows = textwrap.dedent("""
    Specifies the number of rows to display per each axis. 
    Default: {}.
    \n""".format(cfg.default_num_rows))

    help_text_no_surface_vis = textwrap.dedent("""
    This flag disables batch-generation of 3d surface visualizations, which are shown along with cross-sectional overlays. This is not recommended, but could be used in situations where you do not have Freesurfer installed or want to focus solely on cross-sectional views.

    Default: False (required visualizations are generated at the beginning, which can take 5-10 seconds for each subject).
    \n""")

    help_text_outlier_detection_method = textwrap.dedent("""
    Method used to detect the outliers.

    For more info, read http://scikit-learn.org/stable/modules/outlier_detection.html

Make sure to choose the right vis_type. 

    Default: {} (within the mri folder of Freesurfer format).
    \n""".format(default_seg_name))

    help_text_views = textwrap.dedent("""
    Specifies the set of views to display - could be just 1 view, or 2 or all 3.
    Example: --views 0 (typically sagittal) or --views 1 2 (axial and coronal)
    Default: {} {} {} (show all the views in the selected segmentation)
    \n""".format(default_views[0], default_views[1], default_views[2]))

    help_text_num_slices = textwrap.dedent("""
    Specifies the number of slices to display per each view. 
    This must be even to facilitate better division.
    Default: {}.
    \n""".format(default_num_slices))

    help_text_num_rows = textwrap.dedent("""
    Specifies the number of rows to display per each axis. 
    Default: {}.
    \n""".format(default_num_rows))

    help_text_contour_color = textwrap.dedent("""
    Specifies the color to use for the contours overlaid on MRI (when vis_type requested prescribes contours). 
    Color can be specified in many ways as documented in https://matplotlib.org/users/colors.html
    Default: {}.
    \n""".format(cfg.default_contour_face_color))

    help_text_outlier_detection_method = textwrap.dedent("""
    Method used to detect the outliers.
    
    For more info, read http://scikit-learn.org/stable/modules/outlier_detection.html

Specifies the delay in animation of the display of two images (like in a GIF).
    
    Default: {} (units in seconds).
    \n""".format(cfg.delay_in_animation))

    help_text_views = textwrap.dedent("""
    Specifies the set of views to display - could be just 1 view, or 2 or all 3.
    Example: --views 0 (typically sagittal) or --views 1 2 (axial and coronal)
    Default: {} {} {} (show all the views in the selected segmentation)
    \n""".format(cfg.default_views[0], cfg.default_views[1], cfg.default_views[2]))

    help_text_num_slices = textwrap.dedent("""
    Specifies the number of slices to display per each view. 
    This must be even to facilitate better division.
    Default: {}.
    \n""".format(cfg.default_num_slices))

    help_text_num_rows = textwrap.dedent("""
    Specifies the number of rows to display per each axis. 
    Default: {}.
    \n""".format(cfg.default_num_rows))

    help_text_prepare = textwrap.dedent("""
    This flag does the heavy preprocessing first, prior to starting any review and rating operations.
    Heavy processing can include computation of registration quality metrics and outlier detection etc. 
    This makes the switch from one subject to the next, even more seamless (saving few seconds :) ).

    Default: False.
    \n""")

    help_text_outlier_detection_method = textwrap.dedent("""
    Method used to detect the outliers.

outliers.add_argument("-olt", "--outlier_feat_types", action="store",
                          dest="outlier_feat_types",
                          default=cfg.t1_mri_features_OLD, required=False,
                          help=help_text_outlier_feat_types)

    outliers.add_argument("-old", "--disable_outlier_detection", action="store_true",
                          dest="disable_outlier_detection",
                          required=False, help=help_text_disable_outlier_detection)

    layout = parser.add_argument_group('Layout options', ' ')
    layout.add_argument("-w", "--views", action="store", dest="views",
                        default=cfg.default_views, required=False, nargs='+',
                        help=help_text_views)

    layout.add_argument("-s", "--num_slices", action="store", dest="num_slices",
                        default=cfg.default_num_slices, required=False,
                        help=help_text_num_slices)

    layout.add_argument("-r", "--num_rows", action="store", dest="num_rows",
                        default=cfg.default_num_rows, required=False,
                        help=help_text_num_rows)

    wf_args = parser.add_argument_group('Workflow', 'Options related to workflow '
                                                    'e.g. to pre-compute resource-intensive features, '
                                                    'and pre-generate all the visualizations required')
    wf_args.add_argument("-p", "--prepare_first", action="store_true",
                         dest="prepare_first",
                         help=help_text_prepare)

    return parser

#                       required=False, help=help_text_disable_outlier_detection)

    # TODO re-enable it when OLD is ready for DWI
    outliers.add_argument("-old", "--disable_outlier_detection", action="store_false",
                          dest="disable_outlier_detection",
                          required=False, help=help_text_disable_outlier_detection)

    layout = parser.add_argument_group('Layout options',
                                       'Slice layout arragement when zooming in on a time point,\n'
                                       ' or show to the std. dev plot.')
    layout.add_argument("-w", "--views", action="store", dest="views",
                        default=cfg.default_views, required=False, nargs='+',
                        help=help_text_views)

    layout.add_argument("-s", "--num_slices", action="store", dest="num_slices",
                        default=cfg.default_num_slices, required=False,
                        help=help_text_num_slices)

    layout.add_argument("-r", "--num_rows", action="store", dest="num_rows",
                        default=cfg.default_num_rows, required=False,
                        help=help_text_num_rows)

    _wf_descr = 'Options related to workflow e.g. to pre-compute resource-intensive features,  ' \
                'and pre-generate all the visualizations required before initiating the review.'
    wf_args = parser.add_argument_group('Workflow', _wf_descr)
    wf_args.add_argument("-p", "--prepare_first", action="store_true",
                         dest="prepare_first",
                         help=help_text_prepare)

    return parser

Specifies the delay in animation of the display of two images (like in a GIF).

    Default: {} (units in seconds).
    \n""".format(cfg.delay_in_animation))

    help_text_views = textwrap.dedent("""
    Specifies the set of views to display - could be just 1 view, or 2 or all 3.
    Example: --views 0 (typically sagittal) or --views 1 2 (axial and coronal)
    Default: {} {} {} (show all the views in the selected segmentation)
    \n""".format(cfg.default_views[0], cfg.default_views[1], cfg.default_views[2]))

    help_text_num_slices = textwrap.dedent("""
    Specifies the number of slices to display per each view. 
    This must be even to facilitate better division.
    Default: {}.
    \n""".format(cfg.default_num_slices))

    help_text_num_rows = textwrap.dedent("""
    Specifies the number of rows to display per each axis. 
    Default: {}.
    \n""".format(cfg.default_num_rows))

    help_text_prepare = textwrap.dedent("""
    This flag does the heavy preprocessing first, prior to starting any review and 
    rating operations.
    Heavy processing can include computation of registration quality metrics and 
    outlier detection etc. 
    This makes the switch from one subject to the next, even more seamless (saving 
    few seconds :) ).

    Default: False.
    \n""")

If the images are already preprocessed elsewhere, use this flag ``--apply_preproc``

    Default is NOT to apply any preprocessing (detrending etc) before showing images for review.
    \n""")

    help_text_views = textwrap.dedent("""
    Specifies the set of views to display - could be just 1 view, or 2 or all 3.
    Example: --views 0 (typically sagittal) or --views 1 2 (axial and coronal)
    Default: {} {} {} (show all the views in the selected segmentation)
    \n""".format(cfg.default_views[0], cfg.default_views[1], cfg.default_views[2]))

    help_text_num_slices = textwrap.dedent("""
    Specifies the number of slices to display per each view.
    This must be even to facilitate better division.
    Default: {}.
    \n""".format(cfg.default_num_slices))

    help_text_num_rows = textwrap.dedent("""
    Specifies the number of rows to display per each axis.
    Default: {}.
    \n""".format(cfg.default_num_rows))

    help_text_prepare = textwrap.dedent("""
    This flag enables batch-generation of 3d surface visualizations, prior to starting any review and rating operations.

    This makes the switch from one subject to the next, even more seamless (saving few seconds :) ).

    Default: False (required visualizations are generated only on demand, which can take 5-10 seconds for each subject).
    \n""")

    help_text_outlier_detection_method = textwrap.dedent("""
    Method used to detect the outliers.