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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def make_model(self, grounding_ontology='UN', grounding_threshold=None):
 """Return a networkx MultiDiGraph representing a causal analysis graph. Parameters grounding_ontology : Optional[str] The ontology from which the grounding should be taken (e.g. UN, FAO) grounding_threshold : Optional[float] Minimum threshold score for Eidos grounding. Returns ------- nx.MultiDiGraph The assembled CAG. """

        if grounding_threshold is not None:
            self.grounding_threshold = grounding_threshold

        self.grounding_ontology = grounding_ontology

        # Filter to Influence Statements which are currently supported
        statements = [stmt for stmt in self.statements if
                      isinstance(stmt, Influence)]

        # Initialize graph
        self.CAG = nx.MultiDiGraph()

        # Add nodes and edges to the graph
        for s in statements:
            # Get standardized name of subject and object
            # subj, obj = (self._node_name(s.subj), self._node_name(s.obj))

            # See if both subject and object have polarities given
            has_both_polarity = (s.subj.delta['polarity'] is not None and
                                 s.obj.delta['polarity'] is not None)

            # Add the nodes to the graph
            for node, delta in zip((s.subj.concept, s.obj.concept),
                                   (s.subj.delta, s.obj.delta)):
                self.CAG.add_node(self._node_name(node),
                                  simulable=has_both_polarity,
                                  mods=delta['adjectives'])

            # Edge is solid if both nodes have polarity given
            linestyle = 'solid' if has_both_polarity else 'dotted'
            if has_both_polarity:
                same_polarity = (s.subj.delta['polarity'] ==
                                 s.obj.delta['polarity'])
                if same_polarity:
                    target_arrow_shape, linecolor = ('circle', 'green')
                else:
                    target_arrow_shape, linecolor = ('tee', 'maroon')
            else:
                target_arrow_shape, linecolor = ('triangle', 'maroon')

            # Add edge to the graph with metadata from statement
            provenance = []
            if s.evidence:
                provenance = s.evidence[0].annotations.get('provenance', [])
                if provenance:
                    provenance[0]['text'] = s.evidence[0].text
            self.CAG.add_edge(
                    self._node_name(s.subj.concept),
                    self._node_name(s.obj.concept),
                    subj_polarity=s.subj.delta['polarity'],
                    subj_adjectives=s.subj.delta['adjectives'],
                    obj_polarity=s.obj.delta['polarity'],
                    obj_adjectives=s.obj.delta['adjectives'],
                    linestyle=linestyle,
                    linecolor=linecolor,
                    targetArrowShape=target_arrow_shape,
                    provenance=provenance,
                )

        return self.CAG