class_docstr: Interface for executable reg_measure from NiftyReg platform.
  
  Given two input images, compute the specified measure(s) of similarity
  
  `Source code <https://cmiclab.cs.ucl.ac.uk/mmodat/niftyreg>`_
  
  Examples
  --------
  >>> from nipype.interfaces import niftyreg
  >>> node = niftyreg.RegMeasure()
  >>> node.inputs.ref_file = 'im1.nii'
  >>> node.inputs.flo_file = 'im2.nii'
  >>> node.inputs.measure_type = 'lncc'
  >>> node.inputs.omp_core_val = 4
  >>> node.cmdline
  'reg_measure -flo im2.nii -lncc -omp 4 -out im2_lncc.txt -ref im1.nii'
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code: def _overload_extension(self, value, name=None):
      path, base, _ = split_filename(value)
      suffix = self.inputs.measure_type
      return os.path.join(path, f"{base}_{suffix}.txt")
  
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 RegMeasure obj's underlying member method code with example usage: obj._overload_extension(value, name) and returns: os