code: def test_copy(self):
      cpd = LinearGaussianCPD(
          "y", [0.67, 1, 4.56, 8], 2, ["x1", "x2", "x3"]
      )
      copy = cpd.copy()
  
      self.assertEqual(cpd.variable, copy.variable)
      self.assertEqual(cpd.beta_0, copy.beta_0)
      self.assertEqual(cpd.variance, copy.variance)
      np_test.assert_array_equal(cpd.beta_vector, copy.beta_vector)
      self.assertEqual(cpd.evidence, copy.evidence)
  
      cpd.variable = "z"
      self.assertEqual(copy.variable, "y")
      cpd.variance = 0
      self.assertEqual(copy.variance, 2)
      cpd.beta_0 = 1
      self.assertEqual(copy.beta_0, 0.67)
      cpd.evidence = ["p", "q", "r"]
      self.assertEqual(copy.evidence, ["x1", "x2", "x3"])
      cpd.beta_vector = [2, 2, 2]
      np_test.assert_array_equal(copy.beta_vector, [1, 4.56, 8])
  
      copy = cpd.copy()
  
      copy.variable = "k"
      self.assertEqual(cpd.variable, "z")
      copy.variance = 0.3
      self.assertEqual(cpd.variance, 0)
      copy.beta_0 = 1.5
      self.assertEqual(cpd.beta_0, 1)
      copy.evidence = ["a", "b", "c"]
      self.assertEqual(cpd.evidence, ["p", "q", "r"])
      copy.beta_vector = [2.2, 2.2, 2.2]
      np_test.assert_array_equal(cpd.beta_vector, [2, 2, 2])
  
file_path: pgmpy/pgmpy/tests/test_factors/test_continuous/test_Linear_Gaussian_CPD.py
imports: import unittest
  import numpy.testing
  import pandas
  import numpy
  from pgmpy.factors.continuous import LinearGaussianCPD
label_desc: Use image node_id 4 for calling the TestLGCPD obj's underlying member method code with example usage: obj.test_copy() without return types