code: def test_tree_numbers_after_multiple_updates(n_trees):
      trees_after_update = max(1, int(np.round(n_trees / 3)))
  
      nnd = NNDescent(np.array([[1.0]]), n_neighbors=1, n_trees=n_trees)
  
      assert (
          nnd.n_trees == n_trees
      ), "NN-descent update changed the number of trees"
      assert (
          nnd.n_trees_after_update == trees_after_update
      ), "The value of the n_trees_after_update in NN-descent after update(s) is wrong"
      for i in range(5):
          nnd.update(xs_fresh=np.array([[i]], dtype=np.float64))
          assert (
              nnd.n_trees == trees_after_update
          ), "The value of the n_trees in NN-descent after update(s) is wrong"
          assert (
              nnd.n_trees_after_update == trees_after_update
          ), "The value of the n_trees_after_update in NN-descent after update(s) is wrong"
  
imports: import os
  import io
  import re
  import pytest
  from contextlib import redirect_stdout
  import numpy
  from sklearn.neighbors import KDTree
  from sklearn.neighbors import NearestNeighbors
  from sklearn.preprocessing import normalize
  import pickle
  import joblib
  import scipy
  from pynndescent import NNDescent, PyNNDescentTransformer
label_desc: Use image node_id 28 for calling a global function with example usage: test_tree_numbers_after_multiple_updates(n_trees) without return types