code: def test_random_von_mises_fisher_sample_kappa(
      self,
      n_samples,
      atol,
      max_iter=100,
  ):
      kappa = 1.0
  
      try:
          X = self.space.random_von_mises_fisher(
              n_samples=n_samples, kappa=kappa, max_iter=max_iter
          )
      except NotImplementedError:
          return
  
      kappa_estimate = _estimate_von_mises_kappa(X, n_steps=100)
      self.assertAllClose(kappa_estimate, gs.array(kappa), atol=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 6 for calling the HypersphereExtrinsicTestCase obj's underlying member method code with example usage: obj.test_random_von_mises_fisher_sample_kappa(n_samples, atol, max_iter) without return types