code: def get_simpson_model(self):
      simpson_model = BayesianNetwork(
          [("S", "T"), ("T", "C"), ("S", "C")]
      )
      cpd_s = TabularCPD(
          variable="S",
          variable_card=2,
          values=[[0.5], [0.5]],
          state_names={"S": ["m", "f"]},
      )
      cpd_t = TabularCPD(
          variable="T",
          variable_card=2,
          values=[[0.25, 0.75], [0.75, 0.25]],
          evidence=["S"],
          evidence_card=[2],
          state_names={"S": ["m", "f"], "T": [0, 1]},
      )
      cpd_c = TabularCPD(
          variable="C",
          variable_card=2,
          values=[[0.3, 0.4, 0.7, 0.8], [0.7, 0.6, 0.3, 0.2]],
          evidence=["S", "T"],
          evidence_card=[2, 2],
          state_names={"S": ["m", "f"], "T": [0, 1], "C": [0, 1]},
      )
      simpson_model.add_cpds(cpd_s, cpd_t, cpd_c)
  
      return simpson_model
  
imports: import unittest
  import numpy
  import numpy.testing
  import pandas
  from pgmpy.factors.discrete import TabularCPD
  from pgmpy.inference.CausalInference import CausalInference
  from pgmpy.models import BayesianNetwork
label_desc: Use image node_id 2 for calling the TestDoQuery obj's underlying member method code with example usage: obj.get_simpson_model() and returns: simpson_model