code: def test_single_tensor_btens():
      """Testing single tensor simulations when a btensor is given"""
      gtab_lte = gradient_table(gtab.bvals, gtab.bvecs, btens="LTE")
      gtab_ste = gradient_table(gtab.bvals, gtab.bvecs, btens="STE")
  
      # Check if Signals produced with LTE btensor gives same results as
      # previous simulations not specifying b-tensor
      evecs = np.eye(3)
      evals = np.array([1.4, 0.35, 0.35]) * 10 ** (-3)
      S_ref = single_tensor(gtab, 100, evals, evecs, snr=None)
      S_btens = single_tensor(gtab_lte, 100, evals, evecs, snr=None)
      assert_array_almost_equal(S_ref, S_btens)
  
      # Check if signals produced with STE btensor gives signals that matches
      # the signal decay for mean diffusivity
      md = np.sum(evals) / 3
      S_ref = 100 * np.exp(-gtab.bvals * md)
      S_btens = single_tensor(gtab_ste, 100, evals, evecs, snr=None)
      assert_array_almost_equal(S_ref, S_btens)
  
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 11 for calling a global function with example usage: test_single_tensor_btens() without return types