code: def test_copy(self):
      copy1 = self.phi1.copy()
      copy2 = self.phi3.copy()
  
      copy4 = copy1.copy()
      copy5 = copy2.copy()
  
      self.assertEqual(copy1.variables, copy4.variables)
      self.assertEqual(copy1._pdf, copy4._pdf)
      self.assertEqual(copy2.variables, copy5.variables)
      self.assertEqual(copy2._pdf, copy5._pdf)
  
      copy1.variables = ["A", "B"]
      self.assertEqual(copy4.variables, self.phi1.variables)
  
      def pdf(a, b):
          return (a + b) / (a * a + b * b)
  
      copy1._pdf = pdf
      copy1_pdf = pdf
      self.assertEqual(copy4._pdf, self.phi1._pdf)
      copy4.variables = ["X", "Y"]
      self.assertEqual(copy1.variables, ["A", "B"])
      copy4._pdf = lambda a, b: a + b
      for inp in np.random.rand(4, 2):
          self.assertEqual(
              copy1._pdf(inp[0], inp[1]), copy1_pdf(inp[0], inp[1])
          )
  
      copy2.reduce([("x", 7.7)])
  
      def reduced_pdf(y, z):
          return z * (np.power(7.7, 1) * np.power(y, 2)) / beta(7.7, y)
  
      self.assertEqual(copy5.variables, self.phi3.variables)
      self.assertEqual(copy5._pdf, self.phi3._pdf)
      copy5.reduce([("x", 11), ("z", 13)])
      self.assertEqual(copy2.variables, ["y", "z"])
      for inp in np.random.rand(4, 2):
          self.assertEqual(
              copy2._pdf(inp[0], inp[1]), reduced_pdf(inp[0], inp[1])
          )
  
imports: import unittest
  import numpy
  import numpy.testing
  from scipy.special import beta
  from scipy.stats import multivariate_normal
  from pgmpy.factors.distributions import CustomDistribution
label_desc: Use image node_id 15 for calling the TestCustomDistributionMethods obj's underlying member method code with example usage: obj.test_copy() and returns: unknown, unknown