code: def test_cholesky_functions():
      S, dt, kt = multi_tensor_dki(
          gtab,
          mevals,
          S0=100,
          angles=[(45.0, 45.0), (45.0, 45.0)],
          fractions=[80, 20],
      )
      R = lower_triangular_to_cholesky(dt)
      tensor = cholesky_to_lower_triangular(R)
      assert_array_almost_equal(dt, tensor)
  
imports: import numpy
  import dipy.reconst.dti
  import dipy.reconst.fwdti
  from dipy.reconst.fwdti import fwdti_prediction
  from numpy.testing import assert_array_almost_equal, assert_almost_equal, assert_raises
  from dipy.reconst.dti import from_lower_triangular, decompose_tensor, fractional_anisotropy
  from dipy.reconst.fwdti import lower_triangular_to_cholesky, cholesky_to_lower_triangular, nls_fit_tensor, wls_fit_tensor
  from dipy.sims.voxel import multi_tensor, single_tensor, all_tensor_evecs, multi_tensor_dki
  from dipy.io.gradients import read_bvals_bvecs
  from dipy.core.gradients import gradient_table
  from dipy.data import get_fnames
label_desc: Use image node_id 8 for calling a global function with example usage: test_cholesky_functions() without return types