code: def test_create_calibration(
      onset,
      model,
      eye,
      avg_error,
      max_error,
      positions,
      offsets,
      gaze,
      screen_size,
      screen_distance,
      screen_resolution,
  ):
      """Test creating a Calibration object."""
      kwargs = dict(
          onset=onset,
          model=model,
          eye=eye,
          avg_error=avg_error,
          max_error=max_error,
          positions=positions,
          offsets=offsets,
          gaze=gaze,
          screen_size=screen_size,
          screen_distance=screen_distance,
          screen_resolution=screen_resolution,
      )
      cal = Calibration(**kwargs)
      assert cal["onset"] == onset
      assert cal["model"] == model
      assert cal["eye"] == eye
      assert cal["avg_error"] == avg_error
      assert cal["max_error"] == max_error
      if positions is not None:
          assert isinstance(cal["positions"], np.ndarray)
          assert np.array_equal(cal["positions"], np.array(POSITIONS))
      else:
          assert cal["positions"] is None
      if offsets is not None:
          assert isinstance(cal["offsets"], np.ndarray)
          assert np.array_equal(cal["offsets"], np.array(OFFSETS))
      if gaze is not None:
          assert isinstance(cal["gaze"], np.ndarray)
          assert np.array_equal(cal["gaze"], np.array(GAZES))
      assert cal["screen_size"] == screen_size
      assert cal["screen_distance"] == screen_distance
      assert cal["screen_resolution"] == screen_resolution
      # test copy method
      copied_obj = cal.copy()
      # Check if the copied object is an instance of Calibration
      assert isinstance(copied_obj, Calibration)
      # Check if the an attribute of the copied object is equal to the original object
      assert copied_obj["onset"] == cal["onset"]
      # Modify the copied object and check if it is independent from the original object
      copied_obj["onset"] = 20
      assert copied_obj["onset"] != cal["onset"]
      # test __repr__
      if cal["onset"] is not None:
          assert repr(cal) == EXPECTED_REPR
  
imports: import numpy
  import pytest
  from mne.datasets.testing import data_path, requires_testing_data
  from ..calibration import Calibration, read_eyelink_calibration
label_desc: Use image node_id 1 for calling a global function with example usage: test_create_calibration(onset, model, eye, avg_error, max_error, positions, offsets, gaze, screen_size, screen_distance, screen_resolution) without return types