code: def test_build_dag(self):
      for variant in ["orig", "stable", "parallel"]:
          np.random.seed(42)
          data = pd.DataFrame(
              np.random.randn(10000, 3), columns=list("XYZ")
          )
          data["sum"] = data.sum(axis=1)
          est = PC(data=data)
          dag = est.estimate(
              variant=variant,
              ci_test="pearsonr",
              return_type="dag",
              n_jobs=2,
              show_progress=False,
          )
  
          expected_edges = {("Z", "sum"), ("X", "sum"), ("Y", "sum")}
          self.assertEqual(set(dag.edges()), expected_edges)
  
imports: import unittest
  import networkx
  import numpy
  import pandas
  from joblib.externals.loky import get_reusable_executor
  from pgmpy.estimators import PC
  from pgmpy.independencies import Independencies
  from pgmpy.models import BayesianNetwork
  from pgmpy.sampling import BayesianModelSampling
  from pgmpy.utils import get_example_model
label_desc: Use image node_id 2 for calling the TestPCEstimatorFromContinuousData obj's underlying member method code with example usage: obj.test_build_dag() without return types