def dependency_graph(self):
        r"""
        Returns a NetworkX graph object of the dependencies

        See Also
        --------
        dependency_list
        dependency_map

        Notes
        -----
        To visualize the dependencies, the following NetworkX function and
        settings is helpful:

        nx.draw_spectral(d, arrowsize=50, font_size=32, with_labels=True,
                         node_size=2000, width=3.0, edge_color='lightgrey',
                         font_weight='bold')

        """
        dtree = nx.DiGraph()
        for propname in self.keys():
            dtree.add_node(propname)
            for dependency in self[propname].values():
                if dependency in list(self.keys()):
                    dtree.add_edge(dependency, propname)
        return dtree
def dependency_graph ( self ) : dtree = nx . DiGraph ( ) for propname in self . keys ( ) : dtree . add_node ( propname ) for dependency in self [ propname ] . values ( ) : if dependency in list ( self . keys ( ) ) : dtree . add_edge ( dependency , propname ) return dtree
r"""
        Returns a NetworkX graph object of the dependencies

        See Also
        --------
        dependency_list
        dependency_map

        Notes
        -----
        To visualize the dependencies, the following NetworkX function and
        settings is helpful:

        nx.draw_spectral(d, arrowsize=50, font_size=32, with_labels=True,
                         node_size=2000, width=3.0, edge_color='lightgrey',
                         font_weight='bold')