code: def test_rule_class(self):
      rule1 = Rule(
          0, [("x1", "<=", 6), ("x2", "<=", 100), ("x1", ">", 1)], 0
      )
      rule2 = Rule(
          1, [("x1", "<=", 9), ("x2", ">", 100), ("x1", ">", 3)], 1
      )
      rule3 = Rule(2, [("x1", "<=", 2), ("x2", "<=", 90)], 1)
  
      rule31 = Rule(
          31, [("x2", "<=", 90), ("x1", ">", 1), ("x1", "<=", 2)], 1
      )
      rule2_ = Rule(
          100, [("x1", ">", 3), ("x2", ">", 100), ("x1", "<=", 9)], -1
      )
  
      self.assertTrue(
          rule31.check_equal_preds(rule1.intersection(rule3)),
          "check rule1 intersection rule3 predicate equivalence",
      )
      self.assertTrue(
          rule2.check_equal_preds(rule2_),
          "check rule2 and rule2_ predicate equivalence",
      )
  
      self.assertEqual(
          rule1.as_dict(), {"x1": [1, 6], "x2": [np.NINF, 100]}
      )
      self.assertEqual(
          rule2.as_dict(), {"x1": [3, 9], "x2": [100, np.inf]}
      )
      self.assertEqual(
          rule3.as_dict(), {"x1": [np.NINF, 2], "x2": [np.NINF, 90]}
      )
      self.assertEqual(
          rule3.intersection(rule1).as_dict(),
          {"x1": [1, 2], "x2": [np.NINF, 90]},
      )
      self.assertEqual(rule1.intersection(rule2).as_dict(), {})
  
file_path: AIX360/tests/imd/test_imd.py
imports: import unittest
  import numpy
  from sklearn.model_selection import train_test_split
  from sklearn.linear_model import LogisticRegression
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.tree import DecisionTreeClassifier
  from sklearn.naive_bayes import GaussianNB
  from sklearn.metrics import accuracy_score
  from aix360.algorithms.imd.utils import load_bc_dataset
  from aix360.algorithms.imd.rule import Rule
  from aix360.algorithms.imd.imd import IMDExplainer
  from aix360.algorithms.imd.utils import visualize_jst
label_desc: Use image node_id 1 for calling the TestIMDExplainer obj's underlying member method code with example usage: obj.test_rule_class() without return types