code: def test_against_filliben_norm(self):
      # Test against `stats.fit` ref. [7] Section 8 "Example"
      rng = np.random.default_rng(8024266430745011915)
      y = [6, 1, -4, 8, -2, 5, 0]
      known_params = {"loc": 0, "scale": 1}
      res = stats.goodness_of_fit(
          stats.norm,
          y,
          known_params=known_params,
          statistic="filliben",
          random_state=rng,
      )
      # Slight discrepancy presumably due to roundoff in Filliben's
      # calculation. Using exact order statistic medians instead of
      # Filliben's approximation doesn't account for it.
      assert_allclose(res.statistic, 0.98538, atol=1e-4)
      assert 0.75 < res.pvalue < 0.9
  
      # Using R's ppcc library:
      # library(ppcc)
      # options(digits=16)
      # x < - c(6, 1, -4, 8, -2, 5, 0)
      # set.seed(100)
      # ppccTest(x, "qnorm", ppos="Filliben")
      # Discrepancy with
      assert_allclose(res.statistic, 0.98540957187084, rtol=2e-5)
      assert_allclose(res.pvalue, 0.8875, rtol=2e-3)
  
imports: import os
  import numpy
  import numpy.testing
  from numpy.testing import assert_allclose, assert_equal
  import pytest
  from scipy import stats
  from scipy.optimize import differential_evolution
  from .test_continuous_basic import distcont
  from scipy.stats._distn_infrastructure import FitError
  from scipy.stats._distr_params import distdiscrete
  from scipy.stats import goodness_of_fit
label_desc: Use image node_id 10 for calling the TestGoodnessOfFit obj's underlying member method code with example usage: obj.test_against_filliben_norm() without return types