docs: def get_tables(self):
          """
          Returns list of tuple of child variable and CPD in case of Bayesian
          and list of tuple of scope of variables and values in case of Markov.
  
          Returns
          -------
          list : list of tuples of child variable and values in Bayesian
              list of tuples of scope of variables and values in case of Markov.
  
          Example
          -------
          >>> reader = UAIReader('TestUAI.uai')
          >>> reader.get_tables()
          [(['var_0', 'var_1'], ['4.000', '2.400', '1.000', '0.000']),
           (['var_0', 'var_1', 'var_2'],
            ['2.2500', '3.2500', '3.7500', '0.0000', '0.0000', '10.0000',
             '1.8750', '4.0000', '3.3330', '2.0000', '2.0000', '3.4000'])]
          """
          tables = []
          for function in range(0, self.no_functions):
              function_variables = self.grammar.parseString(self.network)['fun_' + str(function)]
              if isinstance(function_variables, int):
                  function_variables = [function_variables]
              if self.network_type == 'BAYES':
                  child_var = "var_" + str(function_variables[-1])
                  values = self.grammar.parseString(self.network)['fun_values_' + str(function)]
                  tables.append((child_var, list(values)))
              elif self.network_type == "MARKOV":
                  function_variables = ["var_" + str(var) for var in function_variables]
                  values = self.grammar.parseString(self.network)['fun_values_' + str(function)]
                  tables.append((function_variables, list(values)))
          return tables