class_docstr: Calculates distance between two volumes.
code: def _eucl_min(self, nii1, nii2):
      from scipy.spatial.distance import cdist, euclidean
  
      origdata1 = np.asanyarray(nii1.dataobj).astype(bool)
      border1 = self._find_border(origdata1)
  
      origdata2 = np.asanyarray(nii2.dataobj).astype(bool)
      border2 = self._find_border(origdata2)
  
      set1_coordinates = self._get_coordinates(border1, nii1.affine)
  
      set2_coordinates = self._get_coordinates(border2, nii2.affine)
  
      dist_matrix = cdist(set1_coordinates.T, set2_coordinates.T)
      (point1, point2) = np.unravel_index(
          np.argmin(dist_matrix), dist_matrix.shape
      )
      return (
          euclidean(
              set1_coordinates.T[point1, :],
              set2_coordinates.T[point2, :],
          ),
          set1_coordinates.T[point1, :],
          set2_coordinates.T[point2, :],
      )
  
imports: import os
  import os.path
  import nibabel
  import numpy
  from ..None import config, logging
  from ..interfaces.base import SimpleInterface, BaseInterface, traits, TraitedSpec, File, InputMultiPath, BaseInterfaceInputSpec, isdefined
  from ..interfaces.nipy.base import NipyBaseInterface
label_desc: Use image node_id 3 for calling the Distance obj's underlying member method code with example usage: obj._eucl_min(nii1, nii2) and returns: euclidean,  set1_coordinates,  set2_coordinates