code: def test_generate_random_spd_matrix():
      """Test function for sampling outliers"""
      n_matrices, n_dim, sigma = 5, 4, 1.0
      mean = generate_random_spd_matrix(n_dim)
      X = make_outliers(
          n_matrices=n_matrices,
          mean=mean,
          sigma=sigma,
          outlier_coeff=10,
          random_state=None,
      )
      assert X.shape == (n_matrices, n_dim, n_dim)  # X shape mismatch
      assert is_spd(X)
  
file_path: pyRiemann/tests/test_simulated.py
imports: import pytest
  import numpy
  from numpy.testing import assert_array_almost_equal
  from pyriemann.datasets.sampling import generate_random_spd_matrix
  from pyriemann.datasets.simulated import make_covariances, make_matrices, make_masks, make_gaussian_blobs, make_outliers
  from pyriemann.utils.test import is_real, is_sym_pos_def, is_sym_pos_semi_def, is_herm_pos_def, is_herm_pos_semi_def
label_desc: Use image node_id 6 for calling a global function with example usage: test_generate_random_spd_matrix() without return types