class_docstr: Interface for executable reg_aladin from NiftyReg platform.
  
  Block Matching algorithm for symmetric global registration.
  Based on Modat et al., "Global image registration using
  asymmetric block-matching approach"
  J. Med. Img. 1(2) 024003, 2014, doi: 10.1117/1.JMI.1.2.024003
  
  `Source code <https://cmiclab.cs.ucl.ac.uk/mmodat/niftyreg>`_
  
  Examples
  --------
  >>> from nipype.interfaces import niftyreg
  >>> node = niftyreg.RegAladin()
  >>> node.inputs.ref_file = 'im1.nii'
  >>> node.inputs.flo_file = 'im2.nii'
  >>> node.inputs.rmask_file = 'mask.nii'
  >>> node.inputs.omp_core_val = 4
  >>> node.cmdline
  'reg_aladin -aff im2_aff.txt -flo im2.nii -omp 4 -ref im1.nii -res im2_res.nii.gz -rmask mask.nii'
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code: def _list_outputs(self):
      outputs = super()._list_outputs()
  
      # Make a list of the linear transformation file and the input image
      aff = os.path.abspath(outputs["aff_file"])
      flo = os.path.abspath(self.inputs.flo_file)
      outputs["avg_output"] = f"{aff} {flo}"
      return outputs
  
file_path: nipype/nipype/interfaces/niftyreg/reg.py
imports: import os
  from ..base import TraitedSpec, File, traits, isdefined
  from .base import get_custom_path, NiftyRegCommand, NiftyRegCommandInputSpec
  from ...utils.filemanip import split_filename
label_desc: Use image node_id 1 for calling the RegAladin obj's underlying member method code with example usage: obj._list_outputs() and returns: outputs