code: def _linear_selection(self, non_empty_slices, num_slices):
          
  
          num_non_empty = len(non_empty_slices)
  
          # # trying to skip 5% slices at the tails (bottom clipping at 0)
          # skip_count = max(0, np.around(num_non_empty * 0.05).astype('int16'))
          # # only when possible
          # if skip_count > 0 and (num_non_empty - 2 * skip_count > num_slices):
          #     non_empty_slices = non_empty_slices[skip_count: -skip_count]
          #     num_non_empty = len(non_empty_slices)
  
          sampled_indices = np.linspace(0, num_non_empty, num=min(num_non_empty, num_slices),
                                        endpoint=False)
          slices_in_dim = non_empty_slices[np.around(sampled_indices).astype('int64')]
  
          return slices_in_dim
docs: Selects linearly spaced slices in given