code: def test_als_predict_basic_for_new_user_with_new_ratings():
      u = 10
      i = 3
  
      algo = als.BiasedMF(20, iterations=10)
      algo.fit(simple_df)
  
      preds = algo.predict_for_user(u, [i])
  
      new_u_id = -1
      new_ratings = pd.Series(
          [4.0, 5.0], index=[1, 2]
      )  # items as index and ratings as values
  
      new_preds = algo.predict_for_user(new_u_id, [i], new_ratings)
  
      assert preds.loc[i] == approx(new_preds.loc[i], rel=9e-2)
  
imports: import logging
  import pickle
  from pickletools import dis
  from lenskit.algorithms import als
  from lenskit import util
  import pandas
  import numpy
  from seedbank import numpy_rng
  from pytest import approx, mark
  from lenskit.util import Stopwatch
  import lenskit.util.test
label_desc: Use image node_id 5 for calling a global function with example usage: test_als_predict_basic_for_new_user_with_new_ratings() without return types