code: def test_foldnorm(self):
      # Can't guarantee that all distributions will fit all data with
      # arbitrary bounds. This distribution just happens to fail above.
      # Try something slightly different.
      N = 1000
      rng = np.random.default_rng(self.seed)
      dist = stats.foldnorm
      shapes = (1.952125337355587, 2.0, 3.0)
      data = dist.rvs(*shapes, size=N, random_state=rng)
      shape_bounds = {
          "c": (0.1, 10),
          "loc": (0.1, 10),
          "scale": (0.1, 10),
      }
      res = stats.fit(dist, data, shape_bounds, optimizer=self.opt)
  
      assert_nlff_less_or_close(
          dist, data, res.params, shapes, **self.tols
      )
  
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 11 for calling the TestFit obj's underlying member method code with example usage: obj.test_foldnorm() without return types