code: def test_five_components():
      """
      Assert that components computed are identical to the original version for n dimensions.
      """
  
      n_components = 5
  
      lda = preprocessing.LDA(
          n_components=n_components,
          number_of_documents=60,
          maximum_size_vocabulary=100,
          alpha_beta=100,
          alpha_theta=0.5,
          seed=42,
      )
  
      components_list = []
  
      for document in DOC_SET:
          tokens = {token: 1 for token in document.split(" ")}
          components_list.append(lda.learn_transform_one(tokens))
  
      for index, component in enumerate(components_list):
          assert np.array_equal(
              a1=list(component.values()),
              a2=REFERENCE_FIVE_COMPONENTS[index],
          )
  
file_path: river/river/preprocessing/test_lda.py
imports: from __future__ import annotations
  import numpy
  from river import preprocessing
label_desc: Use image node_id 4 for calling a global function with example usage: test_five_components() without return types