class_docstr: Calculates the diffusion tensor model parameters
  
  Example
  -------
  
  >>> import nipype.interfaces.dipy as dipy
  >>> dti = dipy.DTI()
  >>> dti.inputs.in_file = 'diffusion.nii'
  >>> dti.inputs.in_bvec = 'bvecs'
  >>> dti.inputs.in_bval = 'bvals'
  >>> dti.run()                                   # doctest: +SKIP
class_docstr_tok: ["Calculates","the","diffusion","tensor","model","parameters","Example","--","--","--","-",">",">",">","import","nipype.interfaces.dipy","as","dipy",">",">",">","dti","=","dipy.DTI","(",")",">",">",">","dti.inputs.in_file","=","'diffusion.nii'",">",">",">","dti.inputs.in_bvec","=","'bvecs'",">",">",">","dti.inputs.in_bval","=","'bvals'",">",">",">","dti.run","(",")","#","doctest",":","+SKIP"]
code: def _list_outputs(self):
      outputs = self._outputs().get()
      outputs["out_file"] = self._gen_filename("dti")
  
      for metric in ["fa", "md", "rd", "ad", "color_fa"]:
          outputs[f"{metric}_file"] = self._gen_filename(metric)
  
      return outputs
  
imports: import numpy
  import nibabel
  from ...None import logging
  from ..base import TraitedSpec, File, isdefined
  from .base import DipyDiffusionInterface, DipyBaseInterfaceInputSpec
label_desc: Use image node_id 2 for calling the DTI obj's underlying member method code with example usage: obj._list_outputs() and returns: outputs