code: def test_geometric_mean_properties():
      n_matrices = 40
      n_features = 15
      spds = [
          random_spd(n_features, eig_min=1.0, cond=10.0, random_state=0)
          for _ in range(n_matrices)
      ]
      input_spds = copy.copy(spds)
  
      gmean = _geometric_mean(spds)
  
      # Generic
      assert isinstance(spds, list)
      for spd, input_spd in zip(spds, input_spds):
          assert_array_equal(spd, input_spd)
      assert is_spd(gmean, decimal=7)
  
imports: import copy
  import warnings
  from math import cosh, exp, log, sinh, sqrt
  import numpy
  import pytest
  from numpy.testing import assert_array_almost_equal, assert_array_equal
  from pandas import DataFrame
  from scipy import linalg
  from sklearn.covariance import EmpiricalCovariance, LedoitWolf
  from nilearn._utils.extmath import is_spd
  from nilearn.connectome.connectivity_matrices import ConnectivityMeasure, _check_spd, _check_square, _form_symmetric, _geometric_mean, _map_eigenvalues, prec_to_partial, sym_matrix_to_vec, vec_to_sym_matrix
  from nilearn.tests.test_signal import generate_signals
label_desc: Use image node_id 14 for calling a global function with example usage: test_geometric_mean_properties() without return types