def __plot__(self, context, bbox, palette, *args, **kwds):
    'Plots the clustering to the given Cairo context in the given\n        bounding box.\n\n        This is done by calling L{Graph.__plot__()} with the same arguments, but\n        coloring the graph vertices according to the current clustering (unless\n        overridden by the C{vertex_color} argument explicitly).\n\n        This method understands all the positional and keyword arguments that\n        are understood by L{Graph.__plot__()}, only the differences will be\n        highlighted here:\n\n          - C{mark_groups}: whether to highlight some of the vertex groups by\n            colored polygons. Besides the values accepted by L{Graph.__plot__}\n            (i.e., a dict mapping colors to vertex indices, a list containing\n            lists of vertex indices, or C{False}), the following are also\n            accepted:\n\n              - C{True}: all the groups will be highlighted, the colors matching\n                the corresponding color indices from the current palette\n                (see the C{palette} keyword argument of L{Graph.__plot__}.\n\n              - A dict mapping cluster indices or tuples of vertex indices to\n                color names.  The given clusters or vertex groups will be\n                highlighted by the given colors.\n\n              - A list of cluster indices. This is equivalent to passing a\n                dict mapping numeric color indices from the current palette\n                to cluster indices; therefore, the cluster referred to by element\n                I{i} of the list will be highlighted by color I{i} from the\n                palette.\n\n            The value of the C{plotting.mark_groups} configuration key is also\n            taken into account here; if that configuration key is C{True} and\n            C{mark_groups} is not given explicitly, it will automatically be set\n            to C{True}.\n\n            In place of lists of vertex indices, you may also use L{VertexSeq}\n            instances.\n\n            In place of color names, you may also use color indices into the\n            current palette. C{None} as a color name will mean that the\n            corresponding group is ignored.\n\n          - C{palette}: the palette used to resolve numeric color indices to RGBA\n            values. By default, this is an instance of L{ClusterColoringPalette}.\n\n        @see: L{Graph.__plot__()} for more supported keyword arguments.\n        '
    if (('edge_color' not in kwds) and ('color' not in self.graph.edge_attributes())):
        colors = ['grey20', 'grey80']
        kwds['edge_color'] = [colors[is_crossing] for is_crossing in self.crossing()]
    if (palette is None):
        palette = ClusterColoringPalette(len(self))
    if ('mark_groups' not in kwds):
        if Configuration.instance()['plotting.mark_groups']:
            kwds['mark_groups'] = ((group, color) for (color, group) in enumerate(self))
    else:
        kwds['mark_groups'] = _handle_mark_groups_arg_for_clustering(kwds['mark_groups'], self)
    if ('vertex_color' not in kwds):
        kwds['vertex_color'] = self.membership
    return self._graph.__plot__(context, bbox, palette, *args, **kwds)
Plots the clustering to the given Cairo context in the given
bounding box.

This is done by calling L{Graph.__plot__()} with the same arguments, but
coloring the graph vertices according to the current clustering (unless
overridden by the C{vertex_color} argument explicitly).

This method understands all the positional and keyword arguments that
are understood by L{Graph.__plot__()}, only the differences will be
highlighted here:

  - C{mark_groups}: whether to highlight some of the vertex groups by
    colored polygons. Besides the values accepted by L{Graph.__plot__}
    (i.e., a dict mapping colors to vertex indices, a list containing
    lists of vertex indices, or C{False}), the following are also
    accepted:

      - C{True}: all the groups will be highlighted, the colors matching
        the corresponding color indices from the current palette
        (see the C{palette} keyword argument of L{Graph.__plot__}.

      - A dict mapping cluster indices or tuples of vertex indices to
        color names.  The given clusters or vertex groups will be
        highlighted by the given colors.

      - A list of cluster indices. This is equivalent to passing a
        dict mapping numeric color indices from the current palette
        to cluster indices; therefore, the cluster referred to by element
        I{i} of the list will be highlighted by color I{i} from the
        palette.

    The value of the C{plotting.mark_groups} configuration key is also
    taken into account here; if that configuration key is C{True} and
    C{mark_groups} is not given explicitly, it will automatically be set
    to C{True}.

    In place of lists of vertex indices, you may also use L{VertexSeq}
    instances.

    In place of color names, you may also use color indices into the
    current palette. C{None} as a color name will mean that the
    corresponding group is ignored.

  - C{palette}: the palette used to resolve numeric color indices to RGBA
    values. By default, this is an instance of L{ClusterColoringPalette}.

@see: L{Graph.__plot__()} for more supported keyword arguments.
def __plot__(self, context, bbox, palette, *args, **kwds):
    'Plots the clustering to the given Cairo context in the given\n        bounding box.\n\n        This is done by calling L{Graph.__plot__()} with the same arguments, but\n        coloring the graph vertices according to the current clustering (unless\n        overridden by the C{vertex_color} argument explicitly).\n\n        This method understands all the positional and keyword arguments that\n        are understood by L{Graph.__plot__()}, only the differences will be\n        highlighted here:\n\n          - C{mark_groups}: whether to highlight some of the vertex groups by\n            colored polygons. Besides the values accepted by L{Graph.__plot__}\n            (i.e., a dict mapping colors to vertex indices, a list containing\n            lists of vertex indices, or C{False}), the following are also\n            accepted:\n\n              - C{True}: all the groups will be highlighted, the colors matching\n                the corresponding color indices from the current palette\n                (see the C{palette} keyword argument of L{Graph.__plot__}.\n\n              - A dict mapping cluster indices or tuples of vertex indices to\n                color names.  The given clusters or vertex groups will be\n                highlighted by the given colors.\n\n              - A list of cluster indices. This is equivalent to passing a\n                dict mapping numeric color indices from the current palette\n                to cluster indices; therefore, the cluster referred to by element\n                I{i} of the list will be highlighted by color I{i} from the\n                palette.\n\n            The value of the C{plotting.mark_groups} configuration key is also\n            taken into account here; if that configuration key is C{True} and\n            C{mark_groups} is not given explicitly, it will automatically be set\n            to C{True}.\n\n            In place of lists of vertex indices, you may also use L{VertexSeq}\n            instances.\n\n            In place of color names, you may also use color indices into the\n            current palette. C{None} as a color name will mean that the\n            corresponding group is ignored.\n\n          - C{palette}: the palette used to resolve numeric color indices to RGBA\n            values. By default, this is an instance of L{ClusterColoringPalette}.\n\n        @see: L{Graph.__plot__()} for more supported keyword arguments.\n        '
    if (('edge_color' not in kwds) and ('color' not in self.graph.edge_attributes())):
        colors = ['grey20', 'grey80']
        kwds['edge_color'] = [colors[is_crossing] for is_crossing in self.crossing()]
    if (palette is None):
        palette = ClusterColoringPalette(len(self))
    if ('mark_groups' not in kwds):
        if Configuration.instance()['plotting.mark_groups']:
            kwds['mark_groups'] = ((group, color) for (color, group) in enumerate(self))
    else:
        kwds['mark_groups'] = _handle_mark_groups_arg_for_clustering(kwds['mark_groups'], self)
    if ('vertex_color' not in kwds):
        kwds['vertex_color'] = self.membership
    return self._graph.__plot__(context, bbox, palette, *args, **kwds)