code: def test_random_von_mises_fisher_belongs(
      self, n_points, random_mu, atol, max_iter=100
  ):
      mu = self.space.random_point() if random_mu else None
      kappa = self._get_random_kappa()
  
      try:
          point = self.space.random_von_mises_fisher(
              n_samples=n_points, mu=mu, kappa=kappa, max_iter=max_iter
          )
      except NotImplementedError:
          return
  
      expected = gs.ones(n_points, dtype=bool)
      self.test_belongs(point, expected, atol)
  
imports: import random
  import pytest
  import scipy
  import geomstats.backend
  from geomstats.learning.frechet_mean import FrechetMean
  from geomstats.test.random import EmbeddedSpaceRandomDataGenerator, HypersphereIntrinsicRandomDataGenerator
  from geomstats.test.test_case import TestCase
  from geomstats.test.vectorization import generate_vectorization_data
  from geomstats.test_cases.geometry.base import LevelSetTestCase
  from geomstats.test_cases.geometry.manifold import ManifoldTestCase
  from geomstats.vectorization import get_batch_shape
label_desc: Use image node_id 7 for calling the HypersphereExtrinsicTestCase obj's underlying member method code with example usage: obj.test_random_von_mises_fisher_belongs(n_points, random_mu, atol, max_iter) without return types