code: def test_check_events():
      events = basic_paradigm()
      events_copy = check_events(events)
  
      # Check that given trial type is right
      assert_array_equal(
          events_copy["trial_type"],
          ["c0", "c0", "c0", "c1", "c1", "c1", "c2", "c2", "c2"],
      )
  
      # Check that missing modulation yields an array one ones
      assert_array_equal(
          events_copy["modulation"], np.ones(len(events))
      )
  
      # Modulation is provided
      events["modulation"] = np.ones(len(events))
      events_copy = check_events(events)
      assert_array_equal(
          events_copy["modulation"], events["modulation"]
      )
  
file_path: nilearn/nilearn/glm/tests/test_paradigm.py
imports: import os
  import numpy
  import pandas
  import pytest
  from numpy.testing import assert_array_equal
  from nilearn._utils.data_gen import basic_paradigm
  from nilearn.glm.first_level.experimental_paradigm import check_events, handle_modulation_of_duplicate_events
  from ._testing import block_paradigm, design_with_nan_durations, design_with_nan_onsets, design_with_null_durations, duplicate_events_paradigm, modulated_block_paradigm, modulated_event_paradigm
label_desc: Use image node_id 1 for calling a global function with example usage: test_check_events() without return types