code: def test_normed_stress(k):
      """Test that non-metric MDS normalized stress is scale-invariant."""
      sim = np.array(
          [[0, 5, 3, 4], [5, 0, 2, 2], [3, 2, 0, 1], [4, 2, 1, 0]]
      )
  
      X1, stress1 = mds.smacof(
          sim, metric=False, max_iter=5, random_state=0
      )
      X2, stress2 = mds.smacof(
          k * sim, metric=False, max_iter=5, random_state=0
      )
  
      assert_allclose(stress1, stress2, rtol=1e-5)
      assert_allclose(X1, X2, rtol=1e-5)
  
file_path: scikit-learn/sklearn/manifold/tests/test_mds.py
imports: from unittest.mock import Mock
  import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_array_almost_equal
  from sklearn.manifold import _mds
  from sklearn.metrics import euclidean_distances
label_desc: Use image node_id 4 for calling a global function with example usage: test_normed_stress(k) without return types