docstr: A mock CI testing function which gives False for every condition
  except for the following:
      1. B ⟂ C
      2. B ⟂ D
      3. C ⟂ D
      4. A ⟂ B | C
      5. A ⟂ C | B
docstr_tok: ["A","mock","CI","testing","function","which","gives","False","for","every","condition","except","for","the","following",":","1",".","B","\u27c2","C","2",".","B","\u27c2","D","3",".","C","\u27c2","D","4",".","A","\u27c2","B","|","C","5",".","A","\u27c2","C","|","B"]
code: def fake_ci_t(X, Y, Z=[], **kwargs):
      """
      A mock CI testing function which gives False for every condition
      except for the following:
          1. B \u27C2 C
          2. B \u27C2 D
          3. C \u27C2 D
          4. A \u27C2 B | C
          5. A \u27C2 C | B
      """
      Z = list(Z)
      if X == "B":
          if Y == "C" or Y == "D":
              return True
          elif Y == "A" and Z == ["C"]:
              return True
      elif X == "C" and Y == "D" and Z == []:
          return True
      elif X == "D" and Y == "C" and Z == []:
          return True
      elif Y == "B":
          if X == "C" or X == "D":
              return True
          elif X == "A" and Z == ["C"]:
              return True
      elif X == "A" and Y == "C" and Z == ["B"]:
          return True
      elif X == "C" and Y == "A" and Z == ["B"]:
          return True
      return False
  
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 TestPCFakeCITest obj's underlying member method code with example usage: obj.fake_ci_t(X, Y, Z) and returns: False, True, True, True, True, True, True, True, True