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