code: def test_sigma_gaussian_spd(n_jobs):
      """Test sigma parameter from Riemannian Gaussian sampling."""
      n_matrices, n_dim, sig_1, sig_2 = 5, 4, 1.0, 2.0
      mean = np.eye(n_dim)
      X1 = sample_gaussian_spd(
          n_matrices, mean, sig_1, random_state=42, n_jobs=n_jobs
      )
      X2 = sample_gaussian_spd(
          n_matrices, mean, sig_2, random_state=66, n_jobs=n_jobs
      )
      avg_d1 = np.mean([distance_riemann(X1_i, mean) for X1_i in X1])
      avg_d2 = np.mean([distance_riemann(X2_i, mean) for X2_i in X2])
      assert avg_d1 < avg_d2
  
file_path: pyRiemann/tests/test_sampling.py
imports: import pytest
  import numpy
  from pyriemann.datasets.sampling import sample_gaussian_spd, generate_random_spd_matrix
  from pyriemann.utils.distance import distance_riemann
  from pyriemann.utils.test import is_sym_pos_def
label_desc: Use image node_id 5 for calling a global function with example usage: test_sigma_gaussian_spd(n_jobs) without return types