code: def test_leapfrog_methods(self):
      (
          new_pos,
          new_momentum,
          new_grad,
      ) = self.test_with_grad_log.get_proposed_values()
      np.testing.assert_almost_equal(
          new_pos, np.array([-0.35634146, -0.25609756, -0.33])
      )
      np.testing.assert_almost_equal(
          new_momentum, np.array([-1.3396624, -0.70344884, -1.16963415])
      )
      np.testing.assert_almost_equal(
          new_grad, np.array([-1.0123835, 1.00139798, -0.46422764])
      )
      (
          new_pos,
          new_momentum,
          new_grad,
      ) = self.test_without_grad_log.get_proposed_values()
      np.testing.assert_almost_equal(
          new_pos, np.array([-0.5001626, -0.32195122, -0.45333333])
      )
      np.testing.assert_almost_equal(
          new_momentum,
          np.array([-1.42947981, -0.60709102, -1.21246612]),
      )
      np.testing.assert_almost_equal(
          new_grad, np.array([-0.89536651, 0.98893516, -0.39566396])
      )
  
imports: import unittest
  import numpy
  from pgmpy.factors.distributions import GaussianDistribution
  from pgmpy.sampling import LeapFrog, ModifiedEuler, GradLogPDFGaussian
label_desc: Use image node_id 3 for calling the TestLeapFrog obj's underlying member method code with example usage: obj.test_leapfrog_methods() without return types