code: def test_mode(X, axis, expected):
      actual = _mode_2d(X, axis=axis)
      assert_array_equal(actual, expected)
  
      if np.issubdtype(X.dtype, np.number):
          sp, _ = mode(X, axis=axis)
          assert_array_equal(actual, sp.ravel())
  
imports: import pickle
  import numpy
  from numpy.testing import assert_array_equal
  import pytest
  from pytest import approx
  from scipy.stats import mode
  from sklearn.dummy import DummyClassifier
  from conftest import get_distances, get_means, get_metrics
  from pyriemann.estimation import Covariances
  from pyriemann.utils.kernel import kernel
  from pyriemann.utils.mean import mean_covariance
  from pyriemann.classification import _mode_2d, MDM, FgMDM, KNearestNeighbor, TSclassifier, SVC, MeanField, class_distinctiveness
label_desc: Use image node_id 1 for calling a global function with example usage: test_mode(X, axis, expected) without return types