class_docstr: A class to represent a generic intensity-based image registration
  algorithm.
class_docstr_tok: ["A","class","to","represent","a","generic","intensity-based","image","registration","algorithm","."]
code: def _slicer(self, corner, size, spacing):
      return tuple(
          slice(
              int(corner[i]), int(size[i] + corner[i]), int(spacing[i])
          )
          for i in range(3)
      )
  
imports: import numpy
  import scipy.ndimage
  from ...core.image.image_spaces import as_xyz_image, make_xyz_image, xyz_affine
  from ._registration import _joint_histogram
  from .affine import affine_transforms, inverse_affine, subgrid_affine
  from .chain_transform import ChainTransform
  from .optimizer import configure_optimizer
  from .similarity_measures import similarity_measures
label_desc: Use image node_id 4 for calling the HistogramRegistration obj's underlying member method code with example usage: obj._slicer(corner, size, spacing) and returns: tuple