code: def test_sym_matrix_to_vec():
      sym = np.ones((3, 3))
      sqrt2 = 1.0 / sqrt(2.0)
      vec = np.array([sqrt2, 1.0, sqrt2, 1.0, 1.0, sqrt2])
  
      assert_array_almost_equal(sym_matrix_to_vec(sym), vec)
  
      vec = np.array([1.0, 1.0, 1.0])
  
      assert_array_almost_equal(
          sym_matrix_to_vec(sym, discard_diagonal=True), vec
      )
  
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 23 for calling a global function with example usage: test_sym_matrix_to_vec() without return types