code: def test_compability_with_gcm(self):
      data = pd.DataFrame({"X": [0], "Y": [0], "Z": [0]})
      model = CausalModel(
          data=data,
          treatment="Y",
          outcome="Z",
          graph=StructuralCausalModel(
              nx.DiGraph([("X", "Y"), ("Y", "Z")])
          ),
      )
  
      assert set(model._graph._graph.nodes) == {"X", "Y", "Z"}
      assert set(model._graph._graph.edges) == {("X", "Y"), ("Y", "Z")}
  
      causal_graph = CausalGraph(
          "Y",
          "Z",
          graph=StructuralCausalModel(
              nx.DiGraph([("X", "Y"), ("Y", "Z")])
          ),
      )
      assert set(causal_graph._graph.nodes) == {"X", "Y", "Z"}
      assert set(causal_graph._graph.edges) == {("X", "Y"), ("Y", "Z")}
  
      pcm = ProbabilisticCausalModel(model)
      assert set(pcm.graph.nodes) == {"X", "Y", "Z"}
      assert set(pcm.graph.edges) == {("X", "Y"), ("Y", "Z")}
  
      pcm = ProbabilisticCausalModel(model._graph)
      assert set(pcm.graph.nodes) == {"X", "Y", "Z"}
      assert set(pcm.graph.edges) == {("X", "Y"), ("Y", "Z")}
  
imports: import networkx
  import pandas
  import pytest
  from flaky import flaky
  from pytest import mark
  from sklearn import linear_model
  import dowhy
  import dowhy.datasets
  from dowhy import CausalModel
  from dowhy.causal_graph import CausalGraph
  from dowhy.gcm import ProbabilisticCausalModel, StructuralCausalModel
  from dowhy.utils.graph_operations import daggity_to_dot
label_desc: Use image node_id 11 for calling the TestCausalModel obj's underlying member method code with example usage: obj.test_compability_with_gcm() without return types