code: def test_grad_fun1_fd(self):
      for test_params in self.params:
          # gtrue = self.x.sum(0)
          gtrue = self.gradtrue(test_params)
          fun = self.fun()
          epsilon = 1e-6
          gfd = numdiff.approx_fprime(
              test_params, fun, epsilon=epsilon, args=self.args
          )
          gfd += numdiff.approx_fprime(
              test_params, fun, epsilon=-epsilon, args=self.args
          )
          gfd /= 2.0
          assert_almost_equal(gtrue, gfd, decimal=DEC6)
  
imports: import numpy
  from numpy.testing import assert_allclose, assert_almost_equal
  import statsmodels.api
  from statsmodels.tools import numdiff
  from statsmodels.tools.numdiff import approx_fprime, approx_fprime_cs, approx_hess_cs, _approx_fprime_scalar, _approx_fprime_cs_scalar
label_desc: Use image node_id 3 for calling the CheckDerivativeMixin obj's underlying member method code with example usage: obj.test_grad_fun1_fd() without return types