code: def test_multi_tensor_btens():
      """Testing multi tensor simulations when a btensor is given"""
      mevals = np.array(
          ([0.003, 0.0002, 0.0002], [0.0015, 0.0003, 0.0003])
      )
      e0 = np.array([np.sqrt(2) / 2.0, np.sqrt(2) / 2.0, 0])
      e1 = np.array([0, np.sqrt(2) / 2.0, np.sqrt(2) / 2.0])
      mevecs = [all_tensor_evecs(e0), all_tensor_evecs(e1)]
  
      gtab_ste = gradient_table(gtab.bvals, gtab.bvecs, btens="STE")
  
      s1 = single_tensor(gtab_ste, 100, mevals[0], mevecs[0], snr=None)
      s2 = single_tensor(gtab_ste, 100, mevals[1], mevecs[1], snr=None)
  
      Ssingle = 0.5 * s1 + 0.5 * s2
  
      S, _ = multi_tensor(
          gtab_ste,
          mevals,
          S0=100,
          angles=[(90, 45), (45, 90)],
          fractions=[50, 50],
          snr=None,
      )
  
      assert_array_almost_equal(S, Ssingle)
  
file_path: dipy/dipy/sims/tests/test_voxel.py
imports: import numpy
  from numpy.testing import assert_array_equal, assert_array_almost_equal, assert_, assert_almost_equal
  from dipy.sims.voxel import _check_directions, all_tensor_evecs, add_noise, single_tensor, sticks_and_ball, multi_tensor_dki, kurtosis_element, dki_signal, multi_tensor
  from dipy.data import get_fnames
  from dipy.core.gradients import gradient_table
  from dipy.io.gradients import read_bvals_bvecs
  from dipy.testing.decorators import set_random_number_generator
label_desc: Use image node_id 12 for calling a global function with example usage: test_multi_tensor_btens() without return types