code: def test_is_spd_with_non_symmetrical_matrix():
      matrix = np.arange(4).reshape(4, 1)
      assert not is_spd(matrix, verbose=0)
  
      matrix = np.array([[1, 1e-3 + 9e-19], [1e-3, 1]])
      assert is_spd(matrix, verbose=0)
  
      matrix = np.array([[1, 1e-3 + 1e-18], [1e-3, 1]])
      assert not is_spd(matrix, verbose=0)
  
      matrix = np.array([[1, 1e-3 + 9e-8], [1e-3, 1]])
      assert is_spd(matrix, decimal=4, verbose=0)
  
      matrix = np.array([[1, 1e-3 + 1e-7], [1e-3, 1]])
      assert not is_spd(matrix, decimal=4, verbose=0)
  
imports: import numpy
  from nilearn._utils.extmath import fast_abs_percentile, is_spd
label_desc: Use image node_id 2 for calling a global function with example usage: test_is_spd_with_non_symmetrical_matrix() without return types