(self, context, bbox, palette, *args, **kwds)
return self._graph.__plot__(context, bbox, palette, *args, **kwds)
Plots the cover to the given Cairo context in the given
        bounding box.

        This is done by calling L{Graph.__plot__()} with the same arguments, but
        drawing nice colored blobs around the vertex groups.

        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 the vertex clusters 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 clusters 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.
Plots the cover to the given Cairo context in the given
        bounding box.
Plots the cover to the given Cairo context in the given bounding box .
def __plot__(self, context, bbox, palette, *args, **kwds):
        """Plots the cover to the given Cairo context in the given
        bounding box.

        This is done by calling L{Graph.__plot__()} with the same arguments, but
        drawing nice colored blobs around the vertex groups.

        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 the vertex clusters 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 clusters 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.
        """
        if "edge_color" not in kwds and "color" not in self.graph.edge_attributes():
            # Set up a default edge coloring based on internal vs external edges
            colors = ["grey20", "grey80"]
            kwds["edge_color"] = [
                colors[is_crossing] for is_crossing in self.crossing()
            ]

        if "palette" in kwds:
            palette = kwds["palette"]
        else:
            palette = ClusterColoringPalette(len(self))

        if "mark_groups" not in kwds:
            if Configuration.instance()["plotting.mark_groups"]:
                kwds["mark_groups"] = self
        else:
            kwds["mark_groups"] = _handle_mark_groups_arg_for_clustering(
                kwds["mark_groups"], self
            )

        return self._graph.__plot__(context, bbox, palette, *args, **kwds)
def __plot__ ( self , context , bbox , palette , * args , * * kwds ) : if "edge_color" not in kwds and "color" not in self . graph . edge_attributes ( ) : # Set up a default edge coloring based on internal vs external edges colors = [ "grey20" , "grey80" ] kwds [ "edge_color" ] = [ colors [ is_crossing ] for is_crossing in self . crossing ( ) ] if "palette" in kwds : palette = kwds [ "palette" ] else : palette = ClusterColoringPalette ( len ( self ) ) if "mark_groups" not in kwds : if Configuration . instance ( ) [ "plotting.mark_groups" ] : kwds [ "mark_groups" ] = self else : kwds [ "mark_groups" ] = _handle_mark_groups_arg_for_clustering ( kwds [ "mark_groups" ] , self ) return self . _graph . __plot__ ( context , bbox , palette , * args , * * kwds )