code: def _compartments_eigenvalues(cdt):
      """Helper function that computes the eigenvalues of a tissue sub
      compartment given its individual diffusion tensor
  
      Parameters
      ----------
      cdt : ndarray (..., 6)
          Diffusion tensors elements of the tissue compartment stored in lower
          triangular order.
  
      Returns
      -------
      eval : ndarry (..., 3)
          Eigenvalues of the tissue compartment
      """
      evals, evecs = decompose_tensor(from_lower_triangular(cdt))
      return evals
  
imports: import numpy
  from dipy.reconst.dti import lower_triangular, from_lower_triangular, decompose_tensor, trace, mean_diffusivity, radial_diffusivity, axial_diffusivity, MIN_POSITIVE_SIGNAL
  from dipy.reconst.dki import split_dki_param, _positive_evals, directional_kurtosis, directional_diffusion, kurtosis_maximum, DiffusionKurtosisModel, DiffusionKurtosisFit
  from dipy.reconst.dti import design_matrix
  from dipy.core.ndindex import ndindex
  from dipy.reconst.vec_val_sum import vec_val_vect
  from dipy.data import get_sphere
  import dipy.core.sphere
label_desc: Use image node_id 5 for calling a global function with example usage: _compartments_eigenvalues(cdt) and returns: evals