code: def test_class_init(self):
      phi1 = GD(
          ["x1", "x2", "x3"],
          np.array([[1], [-3], [4]]),
          np.array([[4, 2, -2], [2, 5, -5], [-2, -5, 8]]),
      )
      self.assertEqual(phi1.variables, ["x1", "x2", "x3"])
      np_test.assert_array_equal(
          phi1.mean, np.asarray([[1], [-3], [4]], dtype=float)
      )
      np_test.assert_array_equal(
          phi1.covariance,
          np.asarray(
              [[4, 2, -2], [2, 5, -5], [-2, -5, 8]], dtype=float
          ),
      )
      self.assertEqual(phi1._precision_matrix, None)
  
      phi2 = GD(
          ["x1", "x2", "x3"],
          [1, 2, 5],
          np.array([[4, 2, -2], [2, 5, -5], [-2, -5, 8]]),
      )
      self.assertEqual(phi2.variables, ["x1", "x2", "x3"])
      np_test.assert_array_equal(
          phi2.mean, np.asarray([[1], [2], [5]], dtype=float)
      )
      np_test.assert_array_equal(
          phi2.covariance,
          np.asarray(
              [[4, 2, -2], [2, 5, -5], [-2, -5, 8]], dtype=float
          ),
      )
      self.assertEqual(phi2._precision_matrix, None)
  
      phi3 = GD(["x"], [0], [[1]])
      self.assertEqual(phi3.variables, ["x"])
      np_test.assert_array_equal(
          phi3.mean, np.asarray([[0]], dtype=float)
      )
      np_test.assert_array_equal(
          phi3.covariance, np.asarray([[1]], dtype=float)
      )
      self.assertEqual(phi3._precision_matrix, None)
  
      phi1 = GD(
          ["1", 2, (1, 2, "x")],
          np.array([[1], [-3], [4]]),
          np.array([[4, 2, -2], [2, 5, -5], [-2, -5, 8]]),
      )
      self.assertEqual(phi1.variables, ["1", 2, (1, 2, "x")])
      np_test.assert_array_equal(
          phi1.mean, np.asarray([[1], [-3], [4]], dtype=float)
      )
      np_test.assert_array_equal(
          phi1.covariance,
          np.asarray(
              [[4, 2, -2], [2, 5, -5], [-2, -5, 8]], dtype=float
          ),
      )
      self.assertEqual(phi1._precision_matrix, None)
  
      phi2 = GD(
          ["1", 7, (1, 2, "x")],
          [1, 2, 5],
          np.array([[4, 2, -2], [2, 5, -5], [-2, -5, 8]]),
      )
      self.assertEqual(phi2.variables, ["1", 7, (1, 2, "x")])
      np_test.assert_array_equal(
          phi2.mean, np.asarray([[1], [2], [5]], dtype=float)
      )
      np_test.assert_array_equal(
          phi2.covariance,
          np.asarray(
              [[4, 2, -2], [2, 5, -5], [-2, -5, 8]], dtype=float
          ),
      )
      self.assertEqual(phi2._precision_matrix, None)
  
      phi3 = GD([23], [0], [[1]])
      self.assertEqual(phi3.variables, [23])
      np_test.assert_array_equal(
          phi3.mean, np.asarray([[0]], dtype=float)
      )
      np_test.assert_array_equal(
          phi3.covariance, np.asarray([[1]], dtype=float)
      )
      self.assertEqual(phi3._precision_matrix, None)
  
imports: import unittest
  import numpy
  import numpy.testing
  from pgmpy.factors.distributions import GaussianDistribution
label_desc: Use image node_id 1 for calling the TestGDInit obj's underlying member method code with example usage: obj.test_class_init() without return types