cdt/causality/graph/CCDr.py
def create_graph_from_data(self, data, **kwargs):
        """Apply causal discovery on observational data using CCDr.

        Args:
            data (pandas.DataFrame): DataFrame containing the data

        Returns:
            networkx.DiGraph: Solution given by the CCDR algorithm.
        """
        # Building setup w/ arguments.
        self.arguments['{VERBOSE}'] = str(self.verbose).upper()
        results = self._run_ccdr(data, verbose=self.verbose)
        return nx.relabel_nodes(nx.DiGraph(results),
                                {idx: i for idx, i in enumerate(data.columns)})
def create_graph_from_data(self, data, **kwargs):
        """Apply causal discovery on observational data using CCDr.

        Args:
            data (pandas.DataFrame): DataFrame containing the data

        Returns:
            networkx.DiGraph: Solution given by the CCDR algorithm.
        """
        # Building setup w/ arguments.
        self.arguments['{VERBOSE}'] = str(self.verbose).upper()
        results = self._run_ccdr(data, verbose=self.verbose)
        return nx.relabel_nodes(nx.DiGraph(results),
                                {idx: i for idx, i in enumerate(data.columns)})
def create_graph_from_data ( self , data , * * kwargs ) : # Building setup w/ arguments. self . arguments [ '{VERBOSE}' ] = str ( self . verbose ) . upper ( ) results = self . _run_ccdr ( data , verbose = self . verbose ) return nx . relabel_nodes ( nx . DiGraph ( results ) , { idx : i for idx , i in enumerate ( data . columns ) } )
Apply causal discovery on observational data using CCDr.

        Args:
            data (pandas.DataFrame): DataFrame containing the data

        Returns:
            networkx.DiGraph: Solution given by the CCDR algorithm.
Apply causal discovery on observational data using CCDr .