def orient_undirected_graph(self, data, graph, **kwargs):
        """Run PC on an undirected graph.

        Args:
            data (pandas.DataFrame): DataFrame containing the data
            graph (networkx.Graph): Skeleton of the graph to orient

        Returns:
            networkx.DiGraph: Solution given by PC on the given skeleton.
        """
        # Building setup w/ arguments.
        self.arguments['{CITEST}'] = self.dir_CI_test[self.CI_test]
        self.arguments['{METHOD_INDEP}'] = self.dir_method_indep[self.method_indep]
        self.arguments['{DIRECTED}'] = 'TRUE'
        self.arguments['{ALPHA}'] = str(self.alpha)
        self.arguments['{NJOBS}'] = str(self.nb_jobs)
        self.arguments['{VERBOSE}'] = str(self.verbose).upper()

        fe = DataFrame(nx.adj_matrix(graph, weight=None).todense())
        fg = DataFrame(1 - fe.values)

        results = self._run_pc(data, fixedEdges=fe, fixedGaps=fg, verbose=self.verbose)

        return nx.relabel_nodes(nx.DiGraph(results),
                                {idx: i for idx, i in enumerate(data.columns)})
def orient_undirected_graph(self, data, graph, **kwargs):
        """Run PC on an undirected graph.

        Args:
            data (pandas.DataFrame): DataFrame containing the data
            graph (networkx.Graph): Skeleton of the graph to orient

        Returns:
            networkx.DiGraph: Solution given by PC on the given skeleton.
        """
        # Building setup w/ arguments.
        self.arguments['{CITEST}'] = self.dir_CI_test[self.CI_test]
        self.arguments['{METHOD_INDEP}'] = self.dir_method_indep[self.method_indep]
        self.arguments['{DIRECTED}'] = 'TRUE'
        self.arguments['{ALPHA}'] = str(self.alpha)
        self.arguments['{NJOBS}'] = str(self.nb_jobs)
        self.arguments['{VERBOSE}'] = str(self.verbose).upper()

        fe = DataFrame(nx.adj_matrix(graph, weight=None).todense())
        fg = DataFrame(1 - fe.values)

        results = self._run_pc(data, fixedEdges=fe, fixedGaps=fg, verbose=self.verbose)

        return nx.relabel_nodes(nx.DiGraph(results),
                                {idx: i for idx, i in enumerate(data.columns)})
def orient_undirected_graph ( self , data , graph , * * kwargs ) : # Building setup w/ arguments. self . arguments [ '{CITEST}' ] = self . dir_CI_test [ self . CI_test ] self . arguments [ '{METHOD_INDEP}' ] = self . dir_method_indep [ self . method_indep ] self . arguments [ '{DIRECTED}' ] = 'TRUE' self . arguments [ '{ALPHA}' ] = str ( self . alpha ) self . arguments [ '{NJOBS}' ] = str ( self . nb_jobs ) self . arguments [ '{VERBOSE}' ] = str ( self . verbose ) . upper ( ) fe = DataFrame ( nx . adj_matrix ( graph , weight = None ) . todense ( ) ) fg = DataFrame ( 1 - fe . values ) results = self . _run_pc ( data , fixedEdges = fe , fixedGaps = fg , verbose = self . verbose ) return nx . relabel_nodes ( nx . DiGraph ( results ) , { idx : i for idx , i in enumerate ( data . columns ) } )
Run PC on an undirected graph.

        Args:
            data (pandas.DataFrame): DataFrame containing the data
            graph (networkx.Graph): Skeleton of the graph to orient

        Returns:
            networkx.DiGraph: Solution given by PC on the given skeleton.
Run PC on an undirected graph .