code: def test_order_handling(self, start, end, t_func):
      # geometric_slerp() should handle scenarios with
      # ascending and descending t value arrays gracefully;
      # results should simply be reversed
  
      # for scrambled / unsorted parameters, the same values
      # should be returned, just in scrambled order
  
      num_t_vals = 20
      np.random.seed(789)
      forward_t_vals = t_func(0, 10, num_t_vals)
      # normalize to max of 1
      forward_t_vals /= forward_t_vals.max()
      reverse_t_vals = np.flipud(forward_t_vals)
      shuffled_indices = np.arange(num_t_vals)
      np.random.shuffle(shuffled_indices)
      scramble_t_vals = forward_t_vals.copy()[shuffled_indices]
  
      forward_results = geometric_slerp(
          start=start, end=end, t=forward_t_vals
      )
      reverse_results = geometric_slerp(
          start=start, end=end, t=reverse_t_vals
      )
      scrambled_results = geometric_slerp(
          start=start, end=end, t=scramble_t_vals
      )
  
      # check fidelity to input order
      assert_allclose(forward_results, np.flipud(reverse_results))
      assert_allclose(
          forward_results[shuffled_indices], scrambled_results
      )
  
imports: import numpy
  from numpy.testing import assert_allclose
  import pytest
  from scipy.spatial import geometric_slerp
label_desc: Use image node_id 13 for calling the TestGeometricSlerp obj's underlying member method code with example usage: obj.test_order_handling(start, end, t_func) without return types